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An Innovative Network Scanning Framework


Harjinder Lallie

Suitable for

Computer Science, Part B
Mathematics and Computer Science, Part C
Computer Science and Philosophy, Part C
Computer Science, Part C


Networks often contain multiple vulnerabilities and weaknesses which can be exploited by attackers. Security analysts often find it necessary to perform n Network scanning, probing and vulnerability testing aids the process of discovering and correcting network vulnerabilities. There exist a number of challenges in terms of gathering network data in this manner: -          Scalability. Scanning/probing techniques do not scale well to large networks (Lippmann et al., 2006, Bopche and Mehtre, 2014). -          Semantic problems. A number of approaches – such as that by Roschke et al. (2009) and Cheng et al. (2011) attempted to combine and correlate the results returned from multiple vulnerability databases. However, the databases return the results in different formats - some in textual format, others in XML format. This means that the results have to be unified into a common meaningful format -          Data Consolidation. Other than Rosschke et al’s (2009) study into combining network scanning methods, there have been very few studies which critically evaluate methods of combining the use and results of multiple scanning tools -          Performance. Scanning and then combining the results from multiple scanners takes a lot of time (Cheng et al., 2011). Quite often the network configuration changes during the scan – which means that the results are quite often inaccurate. This thesis addresses one or more of the challenges presented above.

Prerequisites: This project involves practical work which may involve setting up a virtual network and applying a range of scanning, probing and vulnerability testing mechanisms on the network.