TY - GEN
T1 - Predicting hacker adoption on darkweb forums using sequential rule mining
AU - Marin, Ericsson
AU - Almukaynizi, Mohammed
AU - Nunes, Eric
AU - Shakarian, Jana
AU - Shakarian, Paulo
N1 - Funding Information:
ACKNOWLEDGMENT Some authors were supported by the Office of Naval Research (ONR) contract N00014-15-1-2742, the Office of Naval Research (ONR) Neptune program, the ASU Global Security Initiative (GSI) and the National Council for Scientific and Technological Development (CNPq-Brazil).
PY - 2019/3/20
Y1 - 2019/3/20
N2 - In recent years, there is a notable rise for proactive, intelligence-driven cyber defense mechanisms. Following this demand, we study here how to leverage the spread of adoption behavior among individuals to predict their posts on hacking forums of the darkweb, driven by the influential activities of their peers. We formulate our problem as a sequential rule mining task, where the goal is to discover user posting rules through sequences of user posts, to later use those rules to make predictions in a near future. We run our experiments using multiple post time granularities and time-windows for obtaining rules, observing precision results up to 0.78 and precision gains up to 837%, when compared to the prior probabilities of hackers posts. Our approach is an additional step in the fight against cyber-attacks.
AB - In recent years, there is a notable rise for proactive, intelligence-driven cyber defense mechanisms. Following this demand, we study here how to leverage the spread of adoption behavior among individuals to predict their posts on hacking forums of the darkweb, driven by the influential activities of their peers. We formulate our problem as a sequential rule mining task, where the goal is to discover user posting rules through sequences of user posts, to later use those rules to make predictions in a near future. We run our experiments using multiple post time granularities and time-windows for obtaining rules, observing precision results up to 0.78 and precision gains up to 837%, when compared to the prior probabilities of hackers posts. Our approach is an additional step in the fight against cyber-attacks.
KW - Darkweb
KW - Hacking forums
KW - Rule-learning
KW - Social influence
KW - User adoption
UR - http://www.scopus.com/inward/record.url?scp=85063898360&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063898360&partnerID=8YFLogxK
U2 - 10.1109/BDCloud.2018.00174
DO - 10.1109/BDCloud.2018.00174
M3 - Conference contribution
AN - SCOPUS:85063898360
T3 - Proceedings - 16th IEEE International Symposium on Parallel and Distributed Processing with Applications, 17th IEEE International Conference on Ubiquitous Computing and Communications, 8th IEEE International Conference on Big Data and Cloud Computing, 11th IEEE International Conference on Social Computing and Networking and 8th IEEE International Conference on Sustainable Computing and Communications, ISPA/IUCC/BDCloud/SocialCom/SustainCom 2018
SP - 1183
EP - 1190
BT - Proceedings - 16th IEEE International Symposium on Parallel and Distributed Processing with Applications, 17th IEEE International Conference on Ubiquitous Computing and Communications, 8th IEEE International Conference on Big Data and Cloud Computing, 11th IEEE International Conference on Social Computing and Networking and 8th IEEE International Conference on Sustainable Computing and Communications, ISPA/IUCC/BDCloud/SocialCom/SustainCom 2018
A2 - Chen, Jinjun
A2 - Yang, Laurence T.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE International Symposium on Parallel and Distributed Processing with Applications, 17th IEEE International Conference on Ubiquitous Computing and Communications, 8th IEEE International Conference on Big Data and Cloud Computing, 11th IEEE International Conference on Social Computing and Networking and 8th IEEE International Conference on Sustainable Computing and Communications, ISPA/IUCC/BDCloud/SocialCom/SustainCom 2018
Y2 - 11 December 2018 through 13 December 2018
ER -