Title :
A social agent dynamic honeynet for attack modeling
Author :
Caglayan, A. ; Alavedra, J. ; Toothaker, M. ; Cassani, L.
Author_Institution :
Milcord, Waltham, MA, USA
Abstract :
In our paper we present initial findings related to an effort to develop an agent based dynamic honeynet that simulates user interactions with social networks for the purposes of developing attack models. Our solution allows security professionals to create networks simulating user activity for companies and government entities through the provision of a set of parameters. Our research pointed to the importance of instantiating a social dimension to our virtual agents, providing the agent with the ability to interact with a variety of social networks. For this purpose, we developed influence models to learn patterns from actual users´ activity on social networks to improve the effectiveness of the social agents. We discuss our responses to the technical challenges and analytically investigate the initial results of our honeynet´s ability to attract adversary activity.
Keywords :
learning (artificial intelligence); multi-agent systems; security of data; social networking (online); user interfaces; attack modeling; government entity; social agent dynamic honeynet; social dimension; user activity; user interaction; virtual agent; Arrays; Bayesian methods; Companies; Software agents; Twitter; attack modeling; cyber intelligence; intelligent agents; social networks;
Conference_Titel :
Homeland Security (HST), 2012 IEEE Conference on Technologies for
Conference_Location :
Waltham, MA
Print_ISBN :
978-1-4673-2708-4
DOI :
10.1109/THS.2012.6459863