Visible to the public Threat Intelligence Sharing Community: A Countermeasure Against Advanced Persistent Threat

TitleThreat Intelligence Sharing Community: A Countermeasure Against Advanced Persistent Threat
Publication TypeConference Paper
Year of Publication2019
AuthorsChandel, Sonali, Yan, Mengdi, Chen, Shaojun, Jiang, Huan, Ni, Tian-Yi
Conference Name2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)
Keywordsadvanced attacking skills, advanced persistent threat, analyzing malicious behavior, APT, APT attack, business data processing, Computer crime, Conferences, cyber attack, cyber-attacks, data sharing, Human Behavior, information processing, intelligence information, low-quality shared intelligence, Metrics, persistent attacking skills, pubcrawl, resilience, Resiliency, Scalability, Sharing Community, threat intelligence, threat intelligence sharing community
AbstractAdvanced Persistent Threat (APT) having focused target along with advanced and persistent attacking skills under great concealment is a new trend followed for cyber-attacks. Threat intelligence helps in detecting and preventing APT by collecting a host of data and analyzing malicious behavior through efficient data sharing and guaranteeing the safety and quality of information exchange. For better protection, controlled access to intelligence information and a grading standard to revise the criteria in diagnosis for a security breach is needed. This paper analyses a threat intelligence sharing community model and proposes an improvement to increase the efficiency of sharing by rethinking the size and composition of a sharing community. Based on various external environment variables, it filters the low-quality shared intelligence by grading the trust level of a community member and the quality of a piece of intelligence. We hope that this research can fill in some security gaps to help organizations make a better decision in handling the ever-increasing and continually changing cyber-attacks.
DOI10.1109/MIPR.2019.00070
Citation Keychandel_threat_2019