A baseline study of potentially malicious activity across five network telescopes
- Authors: Irwin, Barry V W
- Date: 2013
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/429714 , vital:72634 , https://ieeexplore.ieee.org/abstract/document/6568378
- Description: +This paper explores the Internet Background Radiation (IBR) observed across five distinct network telescopes over a 15 month period. These network telescopes consisting of a /24 netblock each and are deployed in IP space administered by TENET, the tertiary education network in South Africa covering three numerically distant /8 network blocks. The differences and similarities in the observed network traffic are explored. Two anecdotal case studies are presented relating to the MS08-067 and MS12-020 vulnerabilities in the Microsoft Windows platforms. The first of these is related to the Conficker worm outbreak in 2008, and traffic targeting 445/tcp remains one of the top constituents of IBR as observed on the telescopes. The case of MS12-020 is of interest, as a long period of scanning activity targeting 3389/tcp, used by the Microsoft RDP service, was observed, with a significant drop on activity relating to the release of the security advisory and patch. Other areas of interest are highlighted, particularly where correlation in scanning activity was observed across the sensors. The paper concludes with some discussion on the application of network telescopes as part of a cyber-defence solution.
- Full Text:
- Authors: Irwin, Barry V W
- Date: 2013
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/429714 , vital:72634 , https://ieeexplore.ieee.org/abstract/document/6568378
- Description: +This paper explores the Internet Background Radiation (IBR) observed across five distinct network telescopes over a 15 month period. These network telescopes consisting of a /24 netblock each and are deployed in IP space administered by TENET, the tertiary education network in South Africa covering three numerically distant /8 network blocks. The differences and similarities in the observed network traffic are explored. Two anecdotal case studies are presented relating to the MS08-067 and MS12-020 vulnerabilities in the Microsoft Windows platforms. The first of these is related to the Conficker worm outbreak in 2008, and traffic targeting 445/tcp remains one of the top constituents of IBR as observed on the telescopes. The case of MS12-020 is of interest, as a long period of scanning activity targeting 3389/tcp, used by the Microsoft RDP service, was observed, with a significant drop on activity relating to the release of the security advisory and patch. Other areas of interest are highlighted, particularly where correlation in scanning activity was observed across the sensors. The paper concludes with some discussion on the application of network telescopes as part of a cyber-defence solution.
- Full Text:
Developing a virtualised testbed environment in preparation for testing of network based attacks
- Van Heerden, Renier, Pieterse, Heloise, Burke, Ivan, Irwin, Barry V W
- Authors: Van Heerden, Renier , Pieterse, Heloise , Burke, Ivan , Irwin, Barry V W
- Date: 2013
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/429648 , vital:72629 , 10.1109/ICASTech.2013.6707509
- Description: Computer network attacks are difficult to simulate due to the damage they may cause to live networks and the complexity required simulating a useful network. We constructed a virtualised network within a vSphereESXi environment which is able to simulate: thirty workstations, ten servers, three distinct network segments and the accompanying network traffic. The VSphere environment provided added benefits, such as the ability to pause, restart and snapshot virtual computers. These abilities enabled the authors to reset the simulation environment before each test and mitigated against the damage that an attack potentially inflicts on the test network. Without simulated network traffic, the virtualised network was too sterile. This resulted in any network event being a simple task to detect, making network traffic simulation a requirement for an event detection test bed. Five main kinds of traffic were simulated: Web browsing, File transfer, e-mail, version control and Intranet File traffic. The simulated traffic volumes were pseudo randomised to represent differing temporal patterns. By building a virtualised network with simulated traffic we were able to test IDS' and other network attack detection sensors in a much more realistic environment before moving it to a live network. The goal of this paper is to present a virtualised testbedenvironmentin which network attacks can safely be tested.
- Full Text:
- Authors: Van Heerden, Renier , Pieterse, Heloise , Burke, Ivan , Irwin, Barry V W
- Date: 2013
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/429648 , vital:72629 , 10.1109/ICASTech.2013.6707509
- Description: Computer network attacks are difficult to simulate due to the damage they may cause to live networks and the complexity required simulating a useful network. We constructed a virtualised network within a vSphereESXi environment which is able to simulate: thirty workstations, ten servers, three distinct network segments and the accompanying network traffic. The VSphere environment provided added benefits, such as the ability to pause, restart and snapshot virtual computers. These abilities enabled the authors to reset the simulation environment before each test and mitigated against the damage that an attack potentially inflicts on the test network. Without simulated network traffic, the virtualised network was too sterile. This resulted in any network event being a simple task to detect, making network traffic simulation a requirement for an event detection test bed. Five main kinds of traffic were simulated: Web browsing, File transfer, e-mail, version control and Intranet File traffic. The simulated traffic volumes were pseudo randomised to represent differing temporal patterns. By building a virtualised network with simulated traffic we were able to test IDS' and other network attack detection sensors in a much more realistic environment before moving it to a live network. The goal of this paper is to present a virtualised testbedenvironmentin which network attacks can safely be tested.
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An Analysis and Implementation of Methods for High Speed Lexical Classification of Malicious URLs
- Egan, Shaun P, Irwin, Barry V W
- Authors: Egan, Shaun P , Irwin, Barry V W
- Date: 2012
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/429757 , vital:72637 , https://digifors.cs.up.ac.za/issa/2012/Proceedings/Research/58_ResearchInProgress.pdf
- Description: Several authors have put forward methods of using Artificial Neural Networks (ANN) to classify URLs as malicious or benign by using lexical features of those URLs. These methods have been compared to other methods of classification, such as blacklisting and spam filtering, and have been found to be as accurate. Early attempts proved to be as highly accurate. Fully featured classifications use lexical features as well as lookups to classify URLs and include (but are not limited to) blacklists, spam filters and reputation services. These classifiers are based on the Online Perceptron Model, using a single neuron as a linear combiner and used lexical features that rely on the presence (or lack thereof) of words belonging to a bag-of-words. Several obfuscation resistant features are also used to increase the positive classification rate of these perceptrons. Examples of these include URL length, number of directory traversals and length of arguments passed to the file within the URL. In this paper we describe how we implement the online perceptron model and methods that we used to try to increase the accuracy of this model through the use of hidden layers and training cost validation. We discuss our results in relation to those of other papers, as well as other analysis performed on the training data and the neural networks themselves to best understand why they are so effective. Also described will be the proposed model for developing these Neural Networks, how to implement them in the real world through the use of browser extensions, proxy plugins and spam filters for mail servers, and our current implementation. Finally, work that is still in progress will be described. This work includes other methods of increasing accuracy through the use of modern training techniques and testing in a real world environment.
- Full Text:
- Authors: Egan, Shaun P , Irwin, Barry V W
- Date: 2012
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/429757 , vital:72637 , https://digifors.cs.up.ac.za/issa/2012/Proceedings/Research/58_ResearchInProgress.pdf
- Description: Several authors have put forward methods of using Artificial Neural Networks (ANN) to classify URLs as malicious or benign by using lexical features of those URLs. These methods have been compared to other methods of classification, such as blacklisting and spam filtering, and have been found to be as accurate. Early attempts proved to be as highly accurate. Fully featured classifications use lexical features as well as lookups to classify URLs and include (but are not limited to) blacklists, spam filters and reputation services. These classifiers are based on the Online Perceptron Model, using a single neuron as a linear combiner and used lexical features that rely on the presence (or lack thereof) of words belonging to a bag-of-words. Several obfuscation resistant features are also used to increase the positive classification rate of these perceptrons. Examples of these include URL length, number of directory traversals and length of arguments passed to the file within the URL. In this paper we describe how we implement the online perceptron model and methods that we used to try to increase the accuracy of this model through the use of hidden layers and training cost validation. We discuss our results in relation to those of other papers, as well as other analysis performed on the training data and the neural networks themselves to best understand why they are so effective. Also described will be the proposed model for developing these Neural Networks, how to implement them in the real world through the use of browser extensions, proxy plugins and spam filters for mail servers, and our current implementation. Finally, work that is still in progress will be described. This work includes other methods of increasing accuracy through the use of modern training techniques and testing in a real world environment.
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Building a Graphical Fuzzing Framework
- Zeisberger, Sascha, Irwin, Barry V W
- Authors: Zeisberger, Sascha , Irwin, Barry V W
- Date: 2012
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/429772 , vital:72638 , https://digifors.cs.up.ac.za/issa/2012/Proceedings/Research/59_ResearchInProgress.pdf
- Description: Fuzz testing is a robustness testing technique that sends malformed data to an application’s input. This is to test an application’s behaviour when presented with input beyond its specification. The main difference between traditional testing techniques and fuzz testing is that in most traditional techniques an application is tested according to a specification and rated on how well the application conforms to that specification. Fuzz testing tests beyond the scope of a specification by intelligently generating values that may be interpreted by an application in an unintended manner. The use of fuzz testing has been more prevalent in academic and security communities despite showing success in production environments. To measure the effectiveness of fuzz testing, an experiment was conducted where several publicly available applications were fuzzed. In some instances, fuzz testing was able to force an application into an invalid state and it was concluded that fuzz testing is a relevant testing technique that could assist in developing more robust applications. This success prompted a further investigation into fuzz testing in order to compile a list of requirements that makes an effective fuzzer. The aforementioned investigation assisted in the design of a fuzz testing framework, the goal of which is to make the process more accessible to users outside of an academic and security environment. Design methodologies and justifications of said framework are discussed, focusing on the graphical user interface components as this aspect of the framework is used to increase the usability of the framework.
- Full Text:
- Authors: Zeisberger, Sascha , Irwin, Barry V W
- Date: 2012
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/429772 , vital:72638 , https://digifors.cs.up.ac.za/issa/2012/Proceedings/Research/59_ResearchInProgress.pdf
- Description: Fuzz testing is a robustness testing technique that sends malformed data to an application’s input. This is to test an application’s behaviour when presented with input beyond its specification. The main difference between traditional testing techniques and fuzz testing is that in most traditional techniques an application is tested according to a specification and rated on how well the application conforms to that specification. Fuzz testing tests beyond the scope of a specification by intelligently generating values that may be interpreted by an application in an unintended manner. The use of fuzz testing has been more prevalent in academic and security communities despite showing success in production environments. To measure the effectiveness of fuzz testing, an experiment was conducted where several publicly available applications were fuzzed. In some instances, fuzz testing was able to force an application into an invalid state and it was concluded that fuzz testing is a relevant testing technique that could assist in developing more robust applications. This success prompted a further investigation into fuzz testing in order to compile a list of requirements that makes an effective fuzzer. The aforementioned investigation assisted in the design of a fuzz testing framework, the goal of which is to make the process more accessible to users outside of an academic and security environment. Design methodologies and justifications of said framework are discussed, focusing on the graphical user interface components as this aspect of the framework is used to increase the usability of the framework.
- Full Text:
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