Inetvis: a graphical aid for the detection and visualisation of network scans
- Irwin, Barry V W, van Riel, Jean-Pierre
- Authors: Irwin, Barry V W , van Riel, Jean-Pierre
- Date: 2007
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/430381 , vital:72687 , https://www.cs.ru.ac.za/research/g02V2468/publications/Irwin-VizSEC2007_draft.pdf
- Description: This paper presents an investigative analysis of network scans and scan detection algorithms. Visualisation is employed to review network telescope traffic and identify incidents of scan activity. Some of the identified phenomena appear to be novel forms of host discovery. The scan detection algorithms of Snort and Bro are critiqued by comparing the visualised scans with alert output. Where human assessment disa-grees with the alert output, explanations are sought after by analysing the detection algorithms. The algorithms of the Snort and Bro intrusion detection systems are based on counting unique connection attempts to destination addresses and ports. For Snort, notable false positive and false negative cases result due to a grossly oversimplified method of counting unique destination addresses and ports.
- Full Text:
- Date Issued: 2007
- Authors: Irwin, Barry V W , van Riel, Jean-Pierre
- Date: 2007
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/430381 , vital:72687 , https://www.cs.ru.ac.za/research/g02V2468/publications/Irwin-VizSEC2007_draft.pdf
- Description: This paper presents an investigative analysis of network scans and scan detection algorithms. Visualisation is employed to review network telescope traffic and identify incidents of scan activity. Some of the identified phenomena appear to be novel forms of host discovery. The scan detection algorithms of Snort and Bro are critiqued by comparing the visualised scans with alert output. Where human assessment disa-grees with the alert output, explanations are sought after by analysing the detection algorithms. The algorithms of the Snort and Bro intrusion detection systems are based on counting unique connection attempts to destination addresses and ports. For Snort, notable false positive and false negative cases result due to a grossly oversimplified method of counting unique destination addresses and ports.
- Full Text:
- Date Issued: 2007
Identifying and Investigating Intrusive Scanning Patterns by Visualizing Network Telescope Traffic in a 3-D Scatter-plot
- van Riel, Jean-Pierre, Irwin, Barry V W
- Authors: van Riel, Jean-Pierre , Irwin, Barry V W
- Date: 2006
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/428719 , vital:72531 , https://citeseerx.ist.psu.edu/document?repid=rep1type=pdfanddoi=aeb0738f0e53a8c9f407fee7e55c852643f2644c
- Description: Detecting and investigating intrusive Internet activity is an ever-present challenge for network administrators and security researchers. Network monitoring can generate large, unmanageable amounts of log data, which further complicates distinguishing between illegitimate and legiti-mate traffic. Considering the above issue, this article has two aims. First, it describes an investigative methodology for network monitoring and traffic review; and second, it discusses results from applying this meth-od. The method entails a combination of network telescope traffic cap-ture and visualisation. Observing traffic from the perspective of a dedi-cated sensor network reduces the volume of data and alleviates the concern of confusing malicious traffic with legitimate traffic. Compliment-ing this, visual analysis facilitates the rapid review and correlation of events, thereby utilizing human intelligence in the identification of scan-ning patterns. To demonstrate the proposed method, several months of network telescope traffic is captured and analysed with a tailor made 3D scatter-plot visualisation. As the results show, the visualisation saliently conveys anomalous patterns, and further analysis reveals that these patterns are indicative of covert network probing activity. By incorporat-ing visual analysis with traditional approaches, such as textual log re-view and the use of an intrusion detection system, this research contrib-utes improved insight into network scanning incidents.
- Full Text:
- Date Issued: 2006
- Authors: van Riel, Jean-Pierre , Irwin, Barry V W
- Date: 2006
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/428719 , vital:72531 , https://citeseerx.ist.psu.edu/document?repid=rep1type=pdfanddoi=aeb0738f0e53a8c9f407fee7e55c852643f2644c
- Description: Detecting and investigating intrusive Internet activity is an ever-present challenge for network administrators and security researchers. Network monitoring can generate large, unmanageable amounts of log data, which further complicates distinguishing between illegitimate and legiti-mate traffic. Considering the above issue, this article has two aims. First, it describes an investigative methodology for network monitoring and traffic review; and second, it discusses results from applying this meth-od. The method entails a combination of network telescope traffic cap-ture and visualisation. Observing traffic from the perspective of a dedi-cated sensor network reduces the volume of data and alleviates the concern of confusing malicious traffic with legitimate traffic. Compliment-ing this, visual analysis facilitates the rapid review and correlation of events, thereby utilizing human intelligence in the identification of scan-ning patterns. To demonstrate the proposed method, several months of network telescope traffic is captured and analysed with a tailor made 3D scatter-plot visualisation. As the results show, the visualisation saliently conveys anomalous patterns, and further analysis reveals that these patterns are indicative of covert network probing activity. By incorporat-ing visual analysis with traditional approaches, such as textual log re-view and the use of an intrusion detection system, this research contrib-utes improved insight into network scanning incidents.
- Full Text:
- Date Issued: 2006
Inetvis, a visual tool for network telescope traffic analysis
- van Riel, Jean-Pierre, Irwin, Barry V W
- Authors: van Riel, Jean-Pierre , Irwin, Barry V W
- Date: 2006
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/430176 , vital:72671 , https://doi.org/10.1145/1108590.1108604
- Description: This article illustrates the merits of visual analysis as it presents prelimi-nary findings using InetVis - an animated 3-D scatter plot visualization of network events. The concepts and features of InetVis are evaluated with reference to related work in the field. Tested against a network scanning tool, anticipated visual signs of port scanning and network mapping serve as a proof of concept. This research also unveils sub-stantial amounts of suspicious activity present in Internet traffic during August 2005, as captured by a class C network telescope. InetVis is found to have promising scalability whilst offering salient depictions of intrusive network activity.
- Full Text:
- Date Issued: 2006
- Authors: van Riel, Jean-Pierre , Irwin, Barry V W
- Date: 2006
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/430176 , vital:72671 , https://doi.org/10.1145/1108590.1108604
- Description: This article illustrates the merits of visual analysis as it presents prelimi-nary findings using InetVis - an animated 3-D scatter plot visualization of network events. The concepts and features of InetVis are evaluated with reference to related work in the field. Tested against a network scanning tool, anticipated visual signs of port scanning and network mapping serve as a proof of concept. This research also unveils sub-stantial amounts of suspicious activity present in Internet traffic during August 2005, as captured by a class C network telescope. InetVis is found to have promising scalability whilst offering salient depictions of intrusive network activity.
- Full Text:
- Date Issued: 2006
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