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Trustworthy systems design using semantic risk modelling

Trustworthy systems design using semantic risk modelling
Trustworthy systems design using semantic risk modelling
In this paper, we set out to explore some of the many ways in which Social Network Analysis (SNA) can be applied to the field of security. In particular, we investigate what information someone (e.g., an attacker) could infer if they were able to gather data on a person’s friend-groups or device communications (e.g., email interactions) and whether this could be used to predict the “hierarchical importance” of the individual. This research could be applied to various social networks to help with criminal investigations by identifying the users with high influence within the criminal gangs on DarkWeb Forums, in order to help identify the ring-leaders of the gangs. For this study we conducted an initial investigation on the Enron email dataset, and investigated the effectiveness of existing SNA metrics in establishing hierarchy from the social network created from the email communications metadata. We then tested the metrics on a fresh dataset to assess the practicality of our results to a new network.
Chakravarthy, Ajay
4647aa93-2664-4dd7-977b-2a8331f3810c
Chen, Xiaoyu
1b25bdd4-7dba-46be-8799-266b0c0f6785
Nasser, Bassem
d601c873-8295-44e3-a4e1-d363a26ee086
Surridge, Michael
3bd360fa-1962-4992-bb16-12fc4dd7d9a9
Chakravarthy, Ajay
4647aa93-2664-4dd7-977b-2a8331f3810c
Chen, Xiaoyu
1b25bdd4-7dba-46be-8799-266b0c0f6785
Nasser, Bassem
d601c873-8295-44e3-a4e1-d363a26ee086
Surridge, Michael
3bd360fa-1962-4992-bb16-12fc4dd7d9a9

Chakravarthy, Ajay, Chen, Xiaoyu, Nasser, Bassem and Surridge, Michael (2015) Trustworthy systems design using semantic risk modelling. 1st International Conference on Cyber Security for Sustainable Society, United Kingdom. 26 - 27 Feb 2015.

Record type: Conference or Workshop Item (Paper)

Abstract

In this paper, we set out to explore some of the many ways in which Social Network Analysis (SNA) can be applied to the field of security. In particular, we investigate what information someone (e.g., an attacker) could infer if they were able to gather data on a person’s friend-groups or device communications (e.g., email interactions) and whether this could be used to predict the “hierarchical importance” of the individual. This research could be applied to various social networks to help with criminal investigations by identifying the users with high influence within the criminal gangs on DarkWeb Forums, in order to help identify the ring-leaders of the gangs. For this study we conducted an initial investigation on the Enron email dataset, and investigated the effectiveness of existing SNA metrics in establishing hierarchy from the social network created from the email communications metadata. We then tested the metrics on a fresh dataset to assess the practicality of our results to a new network.

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Published date: 27 February 2015
Venue - Dates: 1st International Conference on Cyber Security for Sustainable Society, United Kingdom, 2015-02-26 - 2015-02-27
Organisations: IT Innovation

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Local EPrints ID: 383465
URI: https://eprints.soton.ac.uk/id/eprint/383465
PURE UUID: e1a79bda-9d8b-48c7-91ac-c874a0182e52

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Date deposited: 16 Mar 2016 12:08
Last modified: 17 Jul 2017 20:13

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