An investigation into the current state of web based cryptominers and cryptojacking
- Authors: Len, Robert
- Date: 2021-04
- Subjects: Cryptocurrencies , Malware (Computer software) , Computer networks -- Security measures , Computer networks -- Monitoring , Cryptomining , Coinhive , Cryptojacking
- Language: English
- Type: thesis , text , Masters , MSc
- Identifier: http://hdl.handle.net/10962/178248 , vital:42924
- Description: The aim of this research was to conduct a review of the current state and extent of surreptitious crypto mining software and its prevalence as a means for income generation. Income is generated through the use of a viewer's browser to execute custom JavaScript code to mine cryptocurrencies such as Monero and Bitcoin. The research aimed to measure the prevalence of illicit mining scripts being utilised for “in-browser" cryptojacking while further analysing the ecosystems that support the cryptomining environment. The extent of the research covers aspects such as the content (or type) of the sites hosting malicious “in-browser" cryptomining software as well as the occurrences of currencies utilised in the cryptographic mining and the analysis of cryptographic mining code samples. This research aims to compare the results of previous work with the current state of affairs since the closure of Coinhive in March 2018. Coinhive were at the time the market leader in such web based mining services. Beyond the analysis of the prevalence of cryptomining on the web today, research into the methodologies and techniques used to detect and counteract cryptomining are also conducted. This includes the most recent developments in malicious JavaScript de-obfuscation as well as cryptomining signature creation and detection. Methodologies for heuristic JavaScript behaviour identification and subsequent identification of potential malicious out-liars are also included within the research of the countermeasure analysis. The research revealed that although no longer functional, Coinhive remained as the most prevalent script being used for “in-browser" cryptomining services. While remaining the most prevalent, there was however a significant decline in overall occurrences compared to when coinhive.com was operational. Analysis of the ecosystem hosting \in-browser" mining websites was found to be distributed both geographically as well as in terms of domain categorisations. , Thesis (MSc) -- Faculty of Science, Computer Science, 2021
- Full Text:
- Authors: Len, Robert
- Date: 2021-04
- Subjects: Cryptocurrencies , Malware (Computer software) , Computer networks -- Security measures , Computer networks -- Monitoring , Cryptomining , Coinhive , Cryptojacking
- Language: English
- Type: thesis , text , Masters , MSc
- Identifier: http://hdl.handle.net/10962/178248 , vital:42924
- Description: The aim of this research was to conduct a review of the current state and extent of surreptitious crypto mining software and its prevalence as a means for income generation. Income is generated through the use of a viewer's browser to execute custom JavaScript code to mine cryptocurrencies such as Monero and Bitcoin. The research aimed to measure the prevalence of illicit mining scripts being utilised for “in-browser" cryptojacking while further analysing the ecosystems that support the cryptomining environment. The extent of the research covers aspects such as the content (or type) of the sites hosting malicious “in-browser" cryptomining software as well as the occurrences of currencies utilised in the cryptographic mining and the analysis of cryptographic mining code samples. This research aims to compare the results of previous work with the current state of affairs since the closure of Coinhive in March 2018. Coinhive were at the time the market leader in such web based mining services. Beyond the analysis of the prevalence of cryptomining on the web today, research into the methodologies and techniques used to detect and counteract cryptomining are also conducted. This includes the most recent developments in malicious JavaScript de-obfuscation as well as cryptomining signature creation and detection. Methodologies for heuristic JavaScript behaviour identification and subsequent identification of potential malicious out-liars are also included within the research of the countermeasure analysis. The research revealed that although no longer functional, Coinhive remained as the most prevalent script being used for “in-browser" cryptomining services. While remaining the most prevalent, there was however a significant decline in overall occurrences compared to when coinhive.com was operational. Analysis of the ecosystem hosting \in-browser" mining websites was found to be distributed both geographically as well as in terms of domain categorisations. , Thesis (MSc) -- Faculty of Science, Computer Science, 2021
- Full Text:
An exploration of the overlap between open source threat intelligence and active internet background radiation
- Authors: Pearson, Deon Turner
- Date: 2020
- Subjects: Computer networks -- Security measures , Computer networks -- Monitoring , Malware (Computer software) , TCP/IP (Computer network protocol) , Open source intelligence
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/103802 , vital:32299
- Description: Organisations and individuals are facing increasing persistent threats on the Internet from worms, port scanners, and malicious software (malware). These threats are constantly evolving as attack techniques are discovered. To aid in the detection and prevention of such threats, and to stay ahead of the adversaries conducting the attacks, security specialists are utilising Threat Intelligence (TI) data in their defense strategies. TI data can be obtained from a variety of different sources such as private routers, firewall logs, public archives, and public or private network telescopes. However, at the rate and ease at which TI is produced and published, specifically Open Source Threat Intelligence (OSINT), the quality is dropping, resulting in fragmented, context-less and variable data. This research utilised two sets of TI data, a collection of OSINT and active Internet Background Radiation (IBR). The data was collected over a period of 12 months, from 37 publicly available OSINT datasets and five IBR datasets. Through the identification and analysis of common data between the OSINT and IBR datasets, this research was able to gain insight into how effective OSINT is at detecting and potentially reducing ongoing malicious Internet traffic. As part of this research, a minimal framework for the collection, processing/analysis, and distribution of OSINT was developed and tested. The research focused on exploring areas in common between the two datasets, with the intention of creating an enriched, contextualised, and reduced set of malicious source IP addresses that could be published for consumers to use in their own environment. The findings of this research pointed towards a persistent group of IP addresses observed on both datasets, over the period under research. Using these persistent IP addresses, the research was able to identify specific services being targeted. Amongst these persistent IP addresses were significant packets from Mirai like IoT Malware on port 23/tcp and 2323/tcp as well as general scanning activity on port 445/TCP.
- Full Text:
- Authors: Pearson, Deon Turner
- Date: 2020
- Subjects: Computer networks -- Security measures , Computer networks -- Monitoring , Malware (Computer software) , TCP/IP (Computer network protocol) , Open source intelligence
- Language: English
- Type: text , Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10962/103802 , vital:32299
- Description: Organisations and individuals are facing increasing persistent threats on the Internet from worms, port scanners, and malicious software (malware). These threats are constantly evolving as attack techniques are discovered. To aid in the detection and prevention of such threats, and to stay ahead of the adversaries conducting the attacks, security specialists are utilising Threat Intelligence (TI) data in their defense strategies. TI data can be obtained from a variety of different sources such as private routers, firewall logs, public archives, and public or private network telescopes. However, at the rate and ease at which TI is produced and published, specifically Open Source Threat Intelligence (OSINT), the quality is dropping, resulting in fragmented, context-less and variable data. This research utilised two sets of TI data, a collection of OSINT and active Internet Background Radiation (IBR). The data was collected over a period of 12 months, from 37 publicly available OSINT datasets and five IBR datasets. Through the identification and analysis of common data between the OSINT and IBR datasets, this research was able to gain insight into how effective OSINT is at detecting and potentially reducing ongoing malicious Internet traffic. As part of this research, a minimal framework for the collection, processing/analysis, and distribution of OSINT was developed and tested. The research focused on exploring areas in common between the two datasets, with the intention of creating an enriched, contextualised, and reduced set of malicious source IP addresses that could be published for consumers to use in their own environment. The findings of this research pointed towards a persistent group of IP addresses observed on both datasets, over the period under research. Using these persistent IP addresses, the research was able to identify specific services being targeted. Amongst these persistent IP addresses were significant packets from Mirai like IoT Malware on port 23/tcp and 2323/tcp as well as general scanning activity on port 445/TCP.
- Full Text:
- «
- ‹
- 1
- ›
- »