A comparative study of CERBER, MAKTUB and LOCKY Ransomware using a Hybridised-Malware analysis
- Authors: Schmitt, Veronica
- Date: 2019
- Subjects: Microsoft Windows (Computer file) , Data protection , Computer crimes -- Prevention , Computer security , Computer networks -- Security measures , Computers -- Access control , Malware (Computer software)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/92313 , vital:30702
- Description: There has been a significant increase in the prevalence of Ransomware attacks in the preceding four years to date. This indicates that the battle has not yet been won defending against this class of malware. This research proposes that by identifying the similarities within the operational framework of Ransomware strains, a better overall understanding of their operation and function can be achieved. This, in turn, will aid in a quicker response to future attacks. With the average Ransomware attack taking two hours to be identified, it shows that there is not yet a clear understanding as to why these attacks are so successful. Research into Ransomware is limited by what is currently known on the topic. Due to the limitations of the research the decision was taken to only examined three samples of Ransomware from different families. This was decided due to the complexities and comprehensive nature of the research. The in depth nature of the research and the time constraints associated with it did not allow for proof of concept of this framework to be tested on more than three families, but the exploratory work was promising and should be further explored in future research. The aim of the research is to follow the Hybrid-Malware analysis framework which consists of both static and the dynamic analysis phases, in addition to the digital forensic examination of the infected system. This allows for signature-based findings, along with behavioural and forensic findings all in one. This information allows for a better understanding of how this malware is designed and how it infects and remains persistent on a system. The operating system which has been chosen is the Microsoft Window 7 operating system which is still utilised by a significant proportion of Windows users especially in the corporate environment. The experiment process was designed to enable the researcher the ability to collect information regarding the Ransomware and every aspect of its behaviour and communication on a target system. The results can be compared across the three strains to identify the commonalities. The initial hypothesis was that Ransomware variants are all much like an instant cake box consists of specific building blocks which remain the same with the flavouring of the cake mix being the unique feature.
- Full Text:
- Date Issued: 2019
- Authors: Schmitt, Veronica
- Date: 2019
- Subjects: Microsoft Windows (Computer file) , Data protection , Computer crimes -- Prevention , Computer security , Computer networks -- Security measures , Computers -- Access control , Malware (Computer software)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/92313 , vital:30702
- Description: There has been a significant increase in the prevalence of Ransomware attacks in the preceding four years to date. This indicates that the battle has not yet been won defending against this class of malware. This research proposes that by identifying the similarities within the operational framework of Ransomware strains, a better overall understanding of their operation and function can be achieved. This, in turn, will aid in a quicker response to future attacks. With the average Ransomware attack taking two hours to be identified, it shows that there is not yet a clear understanding as to why these attacks are so successful. Research into Ransomware is limited by what is currently known on the topic. Due to the limitations of the research the decision was taken to only examined three samples of Ransomware from different families. This was decided due to the complexities and comprehensive nature of the research. The in depth nature of the research and the time constraints associated with it did not allow for proof of concept of this framework to be tested on more than three families, but the exploratory work was promising and should be further explored in future research. The aim of the research is to follow the Hybrid-Malware analysis framework which consists of both static and the dynamic analysis phases, in addition to the digital forensic examination of the infected system. This allows for signature-based findings, along with behavioural and forensic findings all in one. This information allows for a better understanding of how this malware is designed and how it infects and remains persistent on a system. The operating system which has been chosen is the Microsoft Window 7 operating system which is still utilised by a significant proportion of Windows users especially in the corporate environment. The experiment process was designed to enable the researcher the ability to collect information regarding the Ransomware and every aspect of its behaviour and communication on a target system. The results can be compared across the three strains to identify the commonalities. The initial hypothesis was that Ransomware variants are all much like an instant cake box consists of specific building blocks which remain the same with the flavouring of the cake mix being the unique feature.
- Full Text:
- Date Issued: 2019
A development method for deriving reusable concurrent programs from verified CSP models
- Authors: Dibley, James
- Date: 2019
- Subjects: CSP (Computer program language) , Sequential processing (Computer science) , Go (Computer program language) , CSPIDER (Open source tool)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/72329 , vital:30035
- Description: This work proposes and demonstrates a novel method for software development that applies formal verification techniques to the design and implementation of concurrent programs. This method is supported by a new software tool, CSPIDER, which translates machine-readable Communicating Sequential Processes (CSP) models into encapsulated, reusable components coded in the Go programming language. In relation to existing CSP implementation techniques, this work is only the second to implement a translator and it provides original support for some CSP language constructs and modelling approaches. The method is evaluated through three case studies: a concurrent sorting array, a trialdivision prime number generator, and a component node for the Ricart-Agrawala distributed mutual exclusion algorithm. Each of these case studies presents the formal verification of safety and functional requirements through CSP model-checking, and it is shown that CSPIDER is capable of generating reusable implementations from each model. The Ricart-Agrawala case study demonstrates the application of the method to the design of a protocol component. This method maintains full compatibility with the primary CSP verification tool. Applying the CSPIDER tool requires minimal commitment to an explicitly defined modelling style and a very small set of pre-translation annotations, but all of these measures can be instated prior to verification. The Go code that CSPIDER produces requires no intervention before it may be used as a component within a larger development. The translator provides a traceable, structured implementation of the CSP model, automatically deriving formal parameters and a channel-based client interface from its interpretation of the CSP model. Each case study demonstrates the use of the translated component within a simple test development.
- Full Text:
- Date Issued: 2019
- Authors: Dibley, James
- Date: 2019
- Subjects: CSP (Computer program language) , Sequential processing (Computer science) , Go (Computer program language) , CSPIDER (Open source tool)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/72329 , vital:30035
- Description: This work proposes and demonstrates a novel method for software development that applies formal verification techniques to the design and implementation of concurrent programs. This method is supported by a new software tool, CSPIDER, which translates machine-readable Communicating Sequential Processes (CSP) models into encapsulated, reusable components coded in the Go programming language. In relation to existing CSP implementation techniques, this work is only the second to implement a translator and it provides original support for some CSP language constructs and modelling approaches. The method is evaluated through three case studies: a concurrent sorting array, a trialdivision prime number generator, and a component node for the Ricart-Agrawala distributed mutual exclusion algorithm. Each of these case studies presents the formal verification of safety and functional requirements through CSP model-checking, and it is shown that CSPIDER is capable of generating reusable implementations from each model. The Ricart-Agrawala case study demonstrates the application of the method to the design of a protocol component. This method maintains full compatibility with the primary CSP verification tool. Applying the CSPIDER tool requires minimal commitment to an explicitly defined modelling style and a very small set of pre-translation annotations, but all of these measures can be instated prior to verification. The Go code that CSPIDER produces requires no intervention before it may be used as a component within a larger development. The translator provides a traceable, structured implementation of the CSP model, automatically deriving formal parameters and a channel-based client interface from its interpretation of the CSP model. Each case study demonstrates the use of the translated component within a simple test development.
- Full Text:
- Date Issued: 2019
A framework for scoring and tagging NetFlow data
- Authors: Sweeney, Michael John
- Date: 2019
- Subjects: NetFlow , Big data , High performance computing , Event processing (Computer science)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/65022 , vital:28654
- Description: With the increase in link speeds and the growth of the Internet, the volume of NetFlow data generated has increased significantly over time and processing these volumes has become a challenge, more specifically a Big Data challenge. With the advent of technologies and architectures designed to handle Big Data volumes, researchers have investigated their application to the processing of NetFlow data. This work builds on prior work wherein a scoring methodology was proposed for identifying anomalies in NetFlow by proposing and implementing a system that allows for automatic, real-time scoring through the adoption of Big Data stream processing architectures. The first part of the research looks at the means of event detection using the scoring approach and implementing as a number of individual, standalone components, each responsible for detecting and scoring a single type of flow trait. The second part is the implementation of these scoring components in a framework, named Themis1, capable of handling high volumes of data with low latency processing times. This was tackled using tools, technologies and architectural elements from the world of Big Data stream processing. The performance of the framework on the stream processing architecture was shown to demonstrate good flow throughput at low processing latencies on a single low end host. The successful demonstration of the framework on a single host opens the way to leverage the scaling capabilities afforded by the architectures and technologies used. This gives weight to the possibility of using this framework for real time threat detection using NetFlow data from larger networked environments.
- Full Text:
- Date Issued: 2019
- Authors: Sweeney, Michael John
- Date: 2019
- Subjects: NetFlow , Big data , High performance computing , Event processing (Computer science)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/65022 , vital:28654
- Description: With the increase in link speeds and the growth of the Internet, the volume of NetFlow data generated has increased significantly over time and processing these volumes has become a challenge, more specifically a Big Data challenge. With the advent of technologies and architectures designed to handle Big Data volumes, researchers have investigated their application to the processing of NetFlow data. This work builds on prior work wherein a scoring methodology was proposed for identifying anomalies in NetFlow by proposing and implementing a system that allows for automatic, real-time scoring through the adoption of Big Data stream processing architectures. The first part of the research looks at the means of event detection using the scoring approach and implementing as a number of individual, standalone components, each responsible for detecting and scoring a single type of flow trait. The second part is the implementation of these scoring components in a framework, named Themis1, capable of handling high volumes of data with low latency processing times. This was tackled using tools, technologies and architectural elements from the world of Big Data stream processing. The performance of the framework on the stream processing architecture was shown to demonstrate good flow throughput at low processing latencies on a single low end host. The successful demonstration of the framework on a single host opens the way to leverage the scaling capabilities afforded by the architectures and technologies used. This gives weight to the possibility of using this framework for real time threat detection using NetFlow data from larger networked environments.
- Full Text:
- Date Issued: 2019
A multi-threading software countermeasure to mitigate side channel analysis in the time domain
- Authors: Frieslaar, Ibraheem
- Date: 2019
- Subjects: Computer security , Data encryption (Computer science) , Noise generators (Electronics)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/71152 , vital:29790
- Description: This research is the first of its kind to investigate the utilisation of a multi-threading software-based countermeasure to mitigate Side Channel Analysis (SCA) attacks, with a particular focus on the AES-128 cryptographic algorithm. This investigation is novel, as there has not been a software-based countermeasure relying on multi-threading to our knowledge. The research has been tested on the Atmel microcontrollers, as well as a more fully featured system in the form of the popular Raspberry Pi that utilises the ARM7 processor. The main contributions of this research is the introduction of a multi-threading software based countermeasure used to mitigate SCA attacks on both an embedded device and a Raspberry Pi. These threads are comprised of various mathematical operations which are utilised to generate electromagnetic (EM) noise resulting in the obfuscation of the execution of the AES-128 algorithm. A novel EM noise generator known as the FRIES noise generator is implemented to obfuscate data captured in the EM field. FRIES comprises of hiding the execution of AES-128 algorithm within the EM noise generated by the 512 Secure Hash Algorithm (SHA) from the libcrypto++ and OpenSSL libraries. In order to evaluate the proposed countermeasure, a novel attack methodology was developed where the entire secret AES-128 encryption key was recovered from a Raspberry Pi, which has not been achieved before. The FRIES noise generator was pitted against this new attack vector and other known noise generators. The results exhibited that the FRIES noise generator withstood this attack whilst other existing techniques still leaked out secret information. The visual location of the AES-128 encryption algorithm in the EM spectrum and key recovery was prevented. These results demonstrated that the proposed multi-threading software based countermeasure was able to be resistant to existing and new forms of attacks, thus verifying that a multi-threading software based countermeasure can serve to mitigate SCA attacks.
- Full Text:
- Date Issued: 2019
- Authors: Frieslaar, Ibraheem
- Date: 2019
- Subjects: Computer security , Data encryption (Computer science) , Noise generators (Electronics)
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/71152 , vital:29790
- Description: This research is the first of its kind to investigate the utilisation of a multi-threading software-based countermeasure to mitigate Side Channel Analysis (SCA) attacks, with a particular focus on the AES-128 cryptographic algorithm. This investigation is novel, as there has not been a software-based countermeasure relying on multi-threading to our knowledge. The research has been tested on the Atmel microcontrollers, as well as a more fully featured system in the form of the popular Raspberry Pi that utilises the ARM7 processor. The main contributions of this research is the introduction of a multi-threading software based countermeasure used to mitigate SCA attacks on both an embedded device and a Raspberry Pi. These threads are comprised of various mathematical operations which are utilised to generate electromagnetic (EM) noise resulting in the obfuscation of the execution of the AES-128 algorithm. A novel EM noise generator known as the FRIES noise generator is implemented to obfuscate data captured in the EM field. FRIES comprises of hiding the execution of AES-128 algorithm within the EM noise generated by the 512 Secure Hash Algorithm (SHA) from the libcrypto++ and OpenSSL libraries. In order to evaluate the proposed countermeasure, a novel attack methodology was developed where the entire secret AES-128 encryption key was recovered from a Raspberry Pi, which has not been achieved before. The FRIES noise generator was pitted against this new attack vector and other known noise generators. The results exhibited that the FRIES noise generator withstood this attack whilst other existing techniques still leaked out secret information. The visual location of the AES-128 encryption algorithm in the EM spectrum and key recovery was prevented. These results demonstrated that the proposed multi-threading software based countermeasure was able to be resistant to existing and new forms of attacks, thus verifying that a multi-threading software based countermeasure can serve to mitigate SCA attacks.
- Full Text:
- Date Issued: 2019
A study of malicious software on the macOS operating system
- Authors: Regensberg, Mark Alan
- Date: 2019
- Subjects: Malware (Computer software) , Computer security , Computer viruses , Mac OS
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/92302 , vital:30701
- Description: Much of the published malware research begins with a common refrain: the cost, quantum and complexity of threats are increasing, and research and practice should prioritise efforts to automate and reduce times to detect and prevent malware, while improving the consistency of categories and taxonomies applied to modern malware. Existing work related to malware targeting Apple's macOS platform has not been spared this approach, although limited research has been conducted on the true nature of threats faced by users of the operating system. While macOS focused research available consistently notes an increase in macOS users, devices and ultimately in threats, an opportunity exists to understand the real nature of threats faced by macOS users and suggest potential avenues for future work. This research provides a view of the current state of macOS malware by analysing and exploring a dataset of malware detections on macOS endpoints captured over a period of eleven months by an anti-malware software vendor. The dataset is augmented with malware information provided by the widely used Virus. Total service, as well as the application of prior automated malware categorisation work, AVClass to categorise and SSDeep to cluster and report on observed data. With Windows and Android platforms frequently in the spotlight as targets for highly disruptive malware like botnets, ransomware and cryptominers, research and intuition seem to suggest the threat of malware on this increasingly popular platform should be growing and evolving accordingly. Findings suggests that the direction and nature of growth and evolution may not be entirely as clear as industry reports suggest. Adware and Potentially Unwanted Applications (PUAs) make up the vast majority of the detected threats, with remote access trojans (RATs), ransomware and cryptocurrency miners comprising a relatively small proportion of the detected malware. This provides a number of avenues for potential future work to compare and contrast with research on other platforms, as well as identification of key factors that may influence its growth in the future.
- Full Text:
- Date Issued: 2019
- Authors: Regensberg, Mark Alan
- Date: 2019
- Subjects: Malware (Computer software) , Computer security , Computer viruses , Mac OS
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/92302 , vital:30701
- Description: Much of the published malware research begins with a common refrain: the cost, quantum and complexity of threats are increasing, and research and practice should prioritise efforts to automate and reduce times to detect and prevent malware, while improving the consistency of categories and taxonomies applied to modern malware. Existing work related to malware targeting Apple's macOS platform has not been spared this approach, although limited research has been conducted on the true nature of threats faced by users of the operating system. While macOS focused research available consistently notes an increase in macOS users, devices and ultimately in threats, an opportunity exists to understand the real nature of threats faced by macOS users and suggest potential avenues for future work. This research provides a view of the current state of macOS malware by analysing and exploring a dataset of malware detections on macOS endpoints captured over a period of eleven months by an anti-malware software vendor. The dataset is augmented with malware information provided by the widely used Virus. Total service, as well as the application of prior automated malware categorisation work, AVClass to categorise and SSDeep to cluster and report on observed data. With Windows and Android platforms frequently in the spotlight as targets for highly disruptive malware like botnets, ransomware and cryptominers, research and intuition seem to suggest the threat of malware on this increasingly popular platform should be growing and evolving accordingly. Findings suggests that the direction and nature of growth and evolution may not be entirely as clear as industry reports suggest. Adware and Potentially Unwanted Applications (PUAs) make up the vast majority of the detected threats, with remote access trojans (RATs), ransomware and cryptocurrency miners comprising a relatively small proportion of the detected malware. This provides a number of avenues for potential future work to compare and contrast with research on other platforms, as well as identification of key factors that may influence its growth in the future.
- Full Text:
- Date Issued: 2019
An analysis of the use of DNS for malicious payload distribution
- Authors: Dube, Ishmael
- Date: 2019
- Subjects: Internet domain names , Computer networks -- Security measures , Computer security , Computer network protocols , Data protection
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/97531 , vital:31447
- Description: The Domain Name System (DNS) protocol is a fundamental part of Internet activities that can be abused by cybercriminals to conduct malicious activities. Previous research has shown that cybercriminals use different methods, including the DNS protocol, to distribute malicious content, remain hidden and avoid detection from various technologies that are put in place to detect anomalies. This allows botnets and certain malware families to establish covert communication channels that can be used to send or receive data and also distribute malicious payloads using the DNS queries and responses. Cybercriminals use the DNS to breach highly protected networks, distribute malicious content, and exfiltrate sensitive information without being detected by security controls put in place by embedding certain strings in DNS packets. This research undertaking broadens this research field and fills in the existing research gap by extending the analysis of DNS being used as a payload distribution channel to detection of domains that are used to distribute different malicious payloads. This research undertaking analysed the use of the DNS in detecting domains and channels that are used for distributing malicious payloads. Passive DNS data which replicate DNS queries on name servers to detect anomalies in DNS queries was evaluated and analysed in order to detect malicious payloads. The research characterises the malicious payload distribution channels by analysing passive DNS traffic and modelling the DNS query and response patterns. The research found that it is possible to detect malicious payload distribution channels through the analysis of DNS TXT resource records.
- Full Text:
- Date Issued: 2019
- Authors: Dube, Ishmael
- Date: 2019
- Subjects: Internet domain names , Computer networks -- Security measures , Computer security , Computer network protocols , Data protection
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/97531 , vital:31447
- Description: The Domain Name System (DNS) protocol is a fundamental part of Internet activities that can be abused by cybercriminals to conduct malicious activities. Previous research has shown that cybercriminals use different methods, including the DNS protocol, to distribute malicious content, remain hidden and avoid detection from various technologies that are put in place to detect anomalies. This allows botnets and certain malware families to establish covert communication channels that can be used to send or receive data and also distribute malicious payloads using the DNS queries and responses. Cybercriminals use the DNS to breach highly protected networks, distribute malicious content, and exfiltrate sensitive information without being detected by security controls put in place by embedding certain strings in DNS packets. This research undertaking broadens this research field and fills in the existing research gap by extending the analysis of DNS being used as a payload distribution channel to detection of domains that are used to distribute different malicious payloads. This research undertaking analysed the use of the DNS in detecting domains and channels that are used for distributing malicious payloads. Passive DNS data which replicate DNS queries on name servers to detect anomalies in DNS queries was evaluated and analysed in order to detect malicious payloads. The research characterises the malicious payload distribution channels by analysing passive DNS traffic and modelling the DNS query and response patterns. The research found that it is possible to detect malicious payload distribution channels through the analysis of DNS TXT resource records.
- Full Text:
- Date Issued: 2019
An investigation of the security of passwords derived from African languages
- Authors: Sishi, Sibusiso Teboho
- Date: 2019
- Subjects: Computers -- Access control -- Passwords , Computer users -- Attitudes , Internet -- Access control , Internet -- Security measures , Internet -- Management , Data protection
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/163273 , vital:41024
- Description: Password authentication has become ubiquitous in the cyber age. To-date, there have been several studies on country based passwords by authors who studied, amongst others, English, Finnish, Italian and Chinese based passwords. However, there has been a lack of focused study on the type of passwords that are being created in Africa and whether there are benefits in creating passwords in an African language. For this research, password databases containing LAN Manager (LM) and NT LAN Manager (NTLM) hashes extracted from South African organisations in a variety of sectors in the economy, were obtained to gain an understanding of user behaviour in creating passwords. Analysis of the passwords obtained from these hashes (using several cracking methods) showed that many organisational passwords are based on the English language. This is understandable considering that the business language in South Africa is English even though South Africa has 11 official languages. African language based passwords were derived from known English weak passwords and some of the passwords were appended with numbers and special characters. The African based passwords created using eight Southern African languages were then uploaded to the Internet to test the security around using passwords based on African languages. Since most of the passwords were able to be cracked by third party researchers, we conclude that any password that is derived from known weak English words marked no improvement in the security of a password written in an African language, especially the more widely spoken languages, namely, isiZulu, isiXhosa and Setswana.
- Full Text:
- Date Issued: 2019
- Authors: Sishi, Sibusiso Teboho
- Date: 2019
- Subjects: Computers -- Access control -- Passwords , Computer users -- Attitudes , Internet -- Access control , Internet -- Security measures , Internet -- Management , Data protection
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/163273 , vital:41024
- Description: Password authentication has become ubiquitous in the cyber age. To-date, there have been several studies on country based passwords by authors who studied, amongst others, English, Finnish, Italian and Chinese based passwords. However, there has been a lack of focused study on the type of passwords that are being created in Africa and whether there are benefits in creating passwords in an African language. For this research, password databases containing LAN Manager (LM) and NT LAN Manager (NTLM) hashes extracted from South African organisations in a variety of sectors in the economy, were obtained to gain an understanding of user behaviour in creating passwords. Analysis of the passwords obtained from these hashes (using several cracking methods) showed that many organisational passwords are based on the English language. This is understandable considering that the business language in South Africa is English even though South Africa has 11 official languages. African language based passwords were derived from known English weak passwords and some of the passwords were appended with numbers and special characters. The African based passwords created using eight Southern African languages were then uploaded to the Internet to test the security around using passwords based on African languages. Since most of the passwords were able to be cracked by third party researchers, we conclude that any password that is derived from known weak English words marked no improvement in the security of a password written in an African language, especially the more widely spoken languages, namely, isiZulu, isiXhosa and Setswana.
- Full Text:
- Date Issued: 2019
Bolvedere: a scalable network flow threat analysis system
- Authors: Herbert, Alan
- Date: 2019
- Subjects: Bolvedere (Computer network analysis system) , Computer networks -- Scalability , Computer networks -- Measurement , Computer networks -- Security measures , Telecommunication -- Traffic -- Measurement
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/71557 , vital:29873
- Description: Since the advent of the Internet, and its public availability in the late 90’s, there have been significant advancements to network technologies and thus a significant increase of the bandwidth available to network users, both human and automated. Although this growth is of great value to network users, it has led to an increase in malicious network-based activities and it is theorized that, as more services become available on the Internet, the volume of such activities will continue to grow. Because of this, there is a need to monitor, comprehend, discern, understand and (where needed) respond to events on networks worldwide. Although this line of thought is simple in its reasoning, undertaking such a task is no small feat. Full packet analysis is a method of network surveillance that seeks out specific characteristics within network traffic that may tell of malicious activity or anomalies in regular network usage. It is carried out within firewalls and implemented through packet classification. In the context of the networks that make up the Internet, this form of packet analysis has become infeasible, as the volume of traffic introduced onto these networks every day is so large that there are simply not enough processing resources to perform such a task on every packet in real time. One could combat this problem by performing post-incident forensics; archiving packets and processing them later. However, as one cannot process all incoming packets, the archive will eventually run out of space. Full packet analysis is also hindered by the fact that some existing, commonly-used solutions are designed around a single host and single thread of execution, an outdated approach that is far slower than necessary on current computing technology. This research explores the conceptual design and implementation of a scalable network traffic analysis system named Bolvedere. Analysis performed by Bolvedere simply asks whether the existence of a connection, coupled with its associated metadata, is enough to conclude something meaningful about that connection. This idea draws away from the traditional processing of every single byte in every single packet monitored on a network link (Deep Packet Inspection) through the concept of working with connection flows. Bolvedere performs its work by leveraging the NetFlow version 9 and IPFIX protocols, but is not limited to these. It is implemented using a modular approach that allows for either complete execution of the system on a single host or the horizontal scaling out of subsystems on multiple hosts. The use of multiple hosts is achieved through the implementation of Zero Message Queue (ZMQ). This allows for Bolvedre to horizontally scale out, which results in an increase in processing resources and thus an increase in analysis throughput. This is due to ease of interprocess communications provided by ZMQ. Many underlying mechanisms in Bolvedere have been automated. This is intended to make the system more userfriendly, as the user need only tell Bolvedere what information they wish to analyse, and the system will then rebuild itself in order to achieve this required task. Bolvedere has also been hardware-accelerated through the use of Field-Programmable Gate Array (FPGA) technologies, which more than doubled the total throughput of the system.
- Full Text:
- Date Issued: 2019
- Authors: Herbert, Alan
- Date: 2019
- Subjects: Bolvedere (Computer network analysis system) , Computer networks -- Scalability , Computer networks -- Measurement , Computer networks -- Security measures , Telecommunication -- Traffic -- Measurement
- Language: English
- Type: text , Thesis , Doctoral , PhD
- Identifier: http://hdl.handle.net/10962/71557 , vital:29873
- Description: Since the advent of the Internet, and its public availability in the late 90’s, there have been significant advancements to network technologies and thus a significant increase of the bandwidth available to network users, both human and automated. Although this growth is of great value to network users, it has led to an increase in malicious network-based activities and it is theorized that, as more services become available on the Internet, the volume of such activities will continue to grow. Because of this, there is a need to monitor, comprehend, discern, understand and (where needed) respond to events on networks worldwide. Although this line of thought is simple in its reasoning, undertaking such a task is no small feat. Full packet analysis is a method of network surveillance that seeks out specific characteristics within network traffic that may tell of malicious activity or anomalies in regular network usage. It is carried out within firewalls and implemented through packet classification. In the context of the networks that make up the Internet, this form of packet analysis has become infeasible, as the volume of traffic introduced onto these networks every day is so large that there are simply not enough processing resources to perform such a task on every packet in real time. One could combat this problem by performing post-incident forensics; archiving packets and processing them later. However, as one cannot process all incoming packets, the archive will eventually run out of space. Full packet analysis is also hindered by the fact that some existing, commonly-used solutions are designed around a single host and single thread of execution, an outdated approach that is far slower than necessary on current computing technology. This research explores the conceptual design and implementation of a scalable network traffic analysis system named Bolvedere. Analysis performed by Bolvedere simply asks whether the existence of a connection, coupled with its associated metadata, is enough to conclude something meaningful about that connection. This idea draws away from the traditional processing of every single byte in every single packet monitored on a network link (Deep Packet Inspection) through the concept of working with connection flows. Bolvedere performs its work by leveraging the NetFlow version 9 and IPFIX protocols, but is not limited to these. It is implemented using a modular approach that allows for either complete execution of the system on a single host or the horizontal scaling out of subsystems on multiple hosts. The use of multiple hosts is achieved through the implementation of Zero Message Queue (ZMQ). This allows for Bolvedre to horizontally scale out, which results in an increase in processing resources and thus an increase in analysis throughput. This is due to ease of interprocess communications provided by ZMQ. Many underlying mechanisms in Bolvedere have been automated. This is intended to make the system more userfriendly, as the user need only tell Bolvedere what information they wish to analyse, and the system will then rebuild itself in order to achieve this required task. Bolvedere has also been hardware-accelerated through the use of Field-Programmable Gate Array (FPGA) technologies, which more than doubled the total throughput of the system.
- Full Text:
- Date Issued: 2019
Categorising Network Telescope data using big data enrichment techniques
- Authors: Davis, Michael Reginald
- Date: 2019
- Subjects: Denial of service attacks , Big data , Computer networks -- Security measures
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/92941 , vital:30766
- Description: Network Telescopes, Internet backbone sampling, IDS and other forms of network-sourced Threat Intelligence provide researchers with insight into the methods and intent of remote entities by capturing network traffic and analysing the resulting data. This analysis and determination of intent is made difficult by the large amounts of potentially malicious traffic, coupled with limited amount of knowledge that can be attributed to the source of the incoming data, as the source is known only by its IP address. Due to the lack of commonly available tooling, many researchers start this analysis from the beginning and so repeat and re-iterate previous research as the bulk of their work. As a result new insight into methods and approaches of analysis is gained at a high cost. Our research approaches this problem by using additional knowledge about the source IP address such as open ports, reverse and forward DNS, BGP routing tables and more, to enhance the researcher's ability to understand the traffic source. The research is a BigData experiment, where large (hundreds of GB) datasets are merged with a two month section of Network Telescope data using a set of Python scripts. The result are written to a Google BigQuery database table. Analysis of the network data is greatly simplified, with questions about the nature of the source, such as its device class (home routing device or server), potential vulnerabilities (open telnet ports or databases) and location becoming relatively easy to answer. Using this approach, researchers can focus on the questions that need answering and efficiently address them. This research could be taken further by using additional data sources such as Geo-location, WHOIS lookups, Threat Intelligence feeds and many others. Other potential areas of research include real-time categorisation of incoming packets, in order to better inform alerting and reporting systems' configuration. In conclusion, categorising Network Telescope data in this way provides insight into the intent of the (apparent) originator and as such is a valuable tool for those seeking to understand the purpose and intent of arriving packets. In particular, the ability to remove packets categorised as non-malicious (e.g. those in the Research category) from the data eliminates a known source of `noise' from the data. This allows the researcher to focus their efforts in a more productive manner.
- Full Text:
- Date Issued: 2019
- Authors: Davis, Michael Reginald
- Date: 2019
- Subjects: Denial of service attacks , Big data , Computer networks -- Security measures
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/92941 , vital:30766
- Description: Network Telescopes, Internet backbone sampling, IDS and other forms of network-sourced Threat Intelligence provide researchers with insight into the methods and intent of remote entities by capturing network traffic and analysing the resulting data. This analysis and determination of intent is made difficult by the large amounts of potentially malicious traffic, coupled with limited amount of knowledge that can be attributed to the source of the incoming data, as the source is known only by its IP address. Due to the lack of commonly available tooling, many researchers start this analysis from the beginning and so repeat and re-iterate previous research as the bulk of their work. As a result new insight into methods and approaches of analysis is gained at a high cost. Our research approaches this problem by using additional knowledge about the source IP address such as open ports, reverse and forward DNS, BGP routing tables and more, to enhance the researcher's ability to understand the traffic source. The research is a BigData experiment, where large (hundreds of GB) datasets are merged with a two month section of Network Telescope data using a set of Python scripts. The result are written to a Google BigQuery database table. Analysis of the network data is greatly simplified, with questions about the nature of the source, such as its device class (home routing device or server), potential vulnerabilities (open telnet ports or databases) and location becoming relatively easy to answer. Using this approach, researchers can focus on the questions that need answering and efficiently address them. This research could be taken further by using additional data sources such as Geo-location, WHOIS lookups, Threat Intelligence feeds and many others. Other potential areas of research include real-time categorisation of incoming packets, in order to better inform alerting and reporting systems' configuration. In conclusion, categorising Network Telescope data in this way provides insight into the intent of the (apparent) originator and as such is a valuable tool for those seeking to understand the purpose and intent of arriving packets. In particular, the ability to remove packets categorised as non-malicious (e.g. those in the Research category) from the data eliminates a known source of `noise' from the data. This allows the researcher to focus their efforts in a more productive manner.
- Full Text:
- Date Issued: 2019
Modernisation and extension of InetVis: a network security data visualisation tool
- Authors: Johnson, Yestin
- Date: 2019
- Subjects: Data visualization , InetVis (Application software)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/69223 , vital:29447
- Description: This research undertook an investigation in digital archaeology, modernisation, and revitalisation of the InetVis software application, developed at Rhodes University in 2007. InetVis allows users to visualise network traffic in an interactive 3D scatter plot. This software is based on the idea of the Spinning Cube of Potential Doom, introduced by Stephen Lau. The original InetVis research project aimed to extend this concept and implementation, specifically for use in analysing network telescope traffic. The InetVis source code was examined and ported to run on modern operating systems. The porting process involved updating the UI framework, Qt, from version 3 to 5, as well as adding support for 64-bit compilation. This research extended its usefulness with the implementation of new, high-value, features and improvements. The most notable new features include the addition of a general settings framework, improved screenshot generation, automated visualisation modes, new keyboard shortcuts, and support for building and running InetVis on macOS. Additional features and improvements were identified for future work. These consist of support for a plug-in architecture and an extended heads-up display. A user survey was then conducted, determining that respondents found InetVis to be easy to use and useful. The user survey also allowed the identification of new and proposed features that the respondents found to be most useful. At this point, no other tool offers the simplicity and user-friendliness of InetVis when it comes to the analysis of network packet captures, especially those from network telescopes.
- Full Text:
- Date Issued: 2019
- Authors: Johnson, Yestin
- Date: 2019
- Subjects: Data visualization , InetVis (Application software)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/69223 , vital:29447
- Description: This research undertook an investigation in digital archaeology, modernisation, and revitalisation of the InetVis software application, developed at Rhodes University in 2007. InetVis allows users to visualise network traffic in an interactive 3D scatter plot. This software is based on the idea of the Spinning Cube of Potential Doom, introduced by Stephen Lau. The original InetVis research project aimed to extend this concept and implementation, specifically for use in analysing network telescope traffic. The InetVis source code was examined and ported to run on modern operating systems. The porting process involved updating the UI framework, Qt, from version 3 to 5, as well as adding support for 64-bit compilation. This research extended its usefulness with the implementation of new, high-value, features and improvements. The most notable new features include the addition of a general settings framework, improved screenshot generation, automated visualisation modes, new keyboard shortcuts, and support for building and running InetVis on macOS. Additional features and improvements were identified for future work. These consist of support for a plug-in architecture and an extended heads-up display. A user survey was then conducted, determining that respondents found InetVis to be easy to use and useful. The user survey also allowed the identification of new and proposed features that the respondents found to be most useful. At this point, no other tool offers the simplicity and user-friendliness of InetVis when it comes to the analysis of network packet captures, especially those from network telescopes.
- Full Text:
- Date Issued: 2019
Targeted attack detection by means of free and open source solutions
- Authors: Bernardo, Louis F
- Date: 2019
- Subjects: Computer networks -- Security measures , Information technology -- Security measures , Computer security -- Management , Data protection
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/92269 , vital:30703
- Description: Compliance requirements are part of everyday business requirements for various areas, such as retail and medical services. As part of compliance it may be required to have infrastructure in place to monitor the activities in the environment to ensure that the relevant data and environment is sufficiently protected. At the core of such monitoring solutions one would find some type of data repository, or database, to store and ultimately correlate the captured events. Such solutions are commonly called Security Information and Event Management, or SIEM for short. Larger companies have been known to use commercial solutions such as IBM's Qradar, Logrythm, or Splunk. However, these come at significant cost and arent suitable for smaller businesses with limited budgets. These solutions require manual configuration of event correlation for detection of activities that place the environment in danger. This usually requires vendor implementation assistance that also would come at a cost. Alternatively, there are open source solutions that provide the required functionality. This research will demonstrate building an open source solution, with minimal to no cost for hardware or software, while still maintaining the capability of detecting targeted attacks. The solution presented in this research includes Wazuh, which is a combination of OSSEC and the ELK stack, integrated with an Network Intrusion Detection System (NIDS). The success of the integration, is determined by measuring postive attack detection based on each different configuration options. To perform the testing, a deliberately vulnerable platform named Metasploitable will be used as a victim host. The victim host vulnerabilities were created specifically to serve as target for Metasploit. The attacks were generated by utilising Metasploit Framework on a prebuilt Kali Linux host.
- Full Text:
- Date Issued: 2019
- Authors: Bernardo, Louis F
- Date: 2019
- Subjects: Computer networks -- Security measures , Information technology -- Security measures , Computer security -- Management , Data protection
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/92269 , vital:30703
- Description: Compliance requirements are part of everyday business requirements for various areas, such as retail and medical services. As part of compliance it may be required to have infrastructure in place to monitor the activities in the environment to ensure that the relevant data and environment is sufficiently protected. At the core of such monitoring solutions one would find some type of data repository, or database, to store and ultimately correlate the captured events. Such solutions are commonly called Security Information and Event Management, or SIEM for short. Larger companies have been known to use commercial solutions such as IBM's Qradar, Logrythm, or Splunk. However, these come at significant cost and arent suitable for smaller businesses with limited budgets. These solutions require manual configuration of event correlation for detection of activities that place the environment in danger. This usually requires vendor implementation assistance that also would come at a cost. Alternatively, there are open source solutions that provide the required functionality. This research will demonstrate building an open source solution, with minimal to no cost for hardware or software, while still maintaining the capability of detecting targeted attacks. The solution presented in this research includes Wazuh, which is a combination of OSSEC and the ELK stack, integrated with an Network Intrusion Detection System (NIDS). The success of the integration, is determined by measuring postive attack detection based on each different configuration options. To perform the testing, a deliberately vulnerable platform named Metasploitable will be used as a victim host. The victim host vulnerabilities were created specifically to serve as target for Metasploit. The attacks were generated by utilising Metasploit Framework on a prebuilt Kali Linux host.
- Full Text:
- Date Issued: 2019
Towards understanding and mitigating attacks leveraging zero-day exploits
- Authors: Smit, Liam
- Date: 2019
- Subjects: Computer crimes -- Prevention , Data protection , Hacking , Computer security , Computer networks -- Security measures , Computers -- Access control , Malware (Computer software)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/115718 , vital:34218
- Description: Zero-day vulnerabilities are unknown and therefore not addressed with the result that they can be exploited by attackers to gain unauthorised system access. In order to understand and mitigate against attacks leveraging zero-days or unknown techniques, it is necessary to study the vulnerabilities, exploits and attacks that make use of them. In recent years there have been a number of leaks publishing such attacks using various methods to exploit vulnerabilities. This research seeks to understand what types of vulnerabilities exist, why and how these are exploited, and how to defend against such attacks by either mitigating the vulnerabilities or the method / process of exploiting them. By moving beyond merely remedying the vulnerabilities to defences that are able to prevent or detect the actions taken by attackers, the security of the information system will be better positioned to deal with future unknown threats. An interesting finding is how attackers exploit moving beyond the observable bounds to circumvent security defences, for example, compromising syslog servers, or going down to lower system rings to gain access. However, defenders can counter this by employing defences that are external to the system preventing attackers from disabling them or removing collected evidence after gaining system access. Attackers are able to defeat air-gaps via the leakage of electromagnetic radiation as well as misdirect attribution by planting false artefacts for forensic analysis and attacking from third party information systems. They analyse the methods of other attackers to learn new techniques. An example of this is the Umbrage project whereby malware is analysed to decide whether it should be implemented as a proof of concept. Another important finding is that attackers respect defence mechanisms such as: remote syslog (e.g. firewall), core dump files, database auditing, and Tripwire (e.g. SlyHeretic). These defences all have the potential to result in the attacker being discovered. Attackers must either negate the defence mechanism or find unprotected targets. Defenders can use technologies such as encryption to defend against interception and man-in-the-middle attacks. They can also employ honeytokens and honeypots to alarm misdirect, slow down and learn from attackers. By employing various tactics defenders are able to increase their chance of detecting and time to react to attacks, even those exploiting hitherto unknown vulnerabilities. To summarize the information presented in this thesis and to show the practical importance thereof, an examination is presented of the NSA's network intrusion of the SWIFT organisation. It shows that the firewalls were exploited with remote code execution zerodays. This attack has a striking parallel in the approach used in the recent VPNFilter malware. If nothing else, the leaks provide information to other actors on how to attack and what to avoid. However, by studying state actors, we can gain insight into what other actors with fewer resources can do in the future.
- Full Text:
- Date Issued: 2019
- Authors: Smit, Liam
- Date: 2019
- Subjects: Computer crimes -- Prevention , Data protection , Hacking , Computer security , Computer networks -- Security measures , Computers -- Access control , Malware (Computer software)
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/115718 , vital:34218
- Description: Zero-day vulnerabilities are unknown and therefore not addressed with the result that they can be exploited by attackers to gain unauthorised system access. In order to understand and mitigate against attacks leveraging zero-days or unknown techniques, it is necessary to study the vulnerabilities, exploits and attacks that make use of them. In recent years there have been a number of leaks publishing such attacks using various methods to exploit vulnerabilities. This research seeks to understand what types of vulnerabilities exist, why and how these are exploited, and how to defend against such attacks by either mitigating the vulnerabilities or the method / process of exploiting them. By moving beyond merely remedying the vulnerabilities to defences that are able to prevent or detect the actions taken by attackers, the security of the information system will be better positioned to deal with future unknown threats. An interesting finding is how attackers exploit moving beyond the observable bounds to circumvent security defences, for example, compromising syslog servers, or going down to lower system rings to gain access. However, defenders can counter this by employing defences that are external to the system preventing attackers from disabling them or removing collected evidence after gaining system access. Attackers are able to defeat air-gaps via the leakage of electromagnetic radiation as well as misdirect attribution by planting false artefacts for forensic analysis and attacking from third party information systems. They analyse the methods of other attackers to learn new techniques. An example of this is the Umbrage project whereby malware is analysed to decide whether it should be implemented as a proof of concept. Another important finding is that attackers respect defence mechanisms such as: remote syslog (e.g. firewall), core dump files, database auditing, and Tripwire (e.g. SlyHeretic). These defences all have the potential to result in the attacker being discovered. Attackers must either negate the defence mechanism or find unprotected targets. Defenders can use technologies such as encryption to defend against interception and man-in-the-middle attacks. They can also employ honeytokens and honeypots to alarm misdirect, slow down and learn from attackers. By employing various tactics defenders are able to increase their chance of detecting and time to react to attacks, even those exploiting hitherto unknown vulnerabilities. To summarize the information presented in this thesis and to show the practical importance thereof, an examination is presented of the NSA's network intrusion of the SWIFT organisation. It shows that the firewalls were exploited with remote code execution zerodays. This attack has a striking parallel in the approach used in the recent VPNFilter malware. If nothing else, the leaks provide information to other actors on how to attack and what to avoid. However, by studying state actors, we can gain insight into what other actors with fewer resources can do in the future.
- Full Text:
- Date Issued: 2019
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