2016年内部威胁研究研讨会 Workshop on Research for Insider Threat

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Welcome to the webpages of the 2016 Workshop on Research for Insider Threats, which is held on May 26, 2016, as part of the 37th IEEE Symposium on Security and Privacy.
The threat of malicious insiders to organizational security has historically been one of the most difficult challenges to address. Insiders often attack using authorized access and with behavior very difficult to distinguish from normal activities. Today, insider attacks are further enabled by immense data storage capabilities, advanced searching algorithms, and the difficulty of comprehensive monitoring of networked systems. Because the actions that occur during insider attacks look much like normal user activities, this exacerbates the technical challenges of proposed solutions to reduce the high incidence of false positives. Furthermore, several recent high-profile attacks have been enabled by non-malicious, or unintentional, insiders fooled by exploits from external attackers.
The insider threat problem continues to receive attention from government agencies. Executive Order 13587 requires all US Government agencies handling classified information to implement insider threat programs to protect sensitive information, leading to a greatly increased interest among US Government agencies in advances in detection of insider threats. Additionally, upcoming changes to the NISP Operating Manual (NISPOM, DoD 5220.22-M) will require insider threat programs for potentially tens of thousands of defense contractors. In recent years, DARPA sponsored two programs (CINDER and ADAMS) aimed at Insider Threat challenges, and there is currently a planned insider threat program sponsored by IARPA, called Scientific advances to Continuous Insider Threat Evaluation (SCITE), that focuses on new research aimed at identifying malicious insiders using active indicators. Technical solutions are emerging, but there are still significant challenges, for example, in the areas of reliable data on insider attacks, understanding the fundamentals of insider threats, and security and privacy aspects of surveillance data caused by advanced insider threat detection programs.

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Topics of interest include but are not limited to:

insider threat indicator development
data collection, aggregation, and correlation for threat indicators
data collection of baseline user data and behaviors
analytic approaches that address key challenges such as reducing false positives
novel techniques/new technologies for prevention, detection, and response to insider attacks
predictive analytics for identifying potential indicators of insider threat
linguistic approaches to identifying potential behavior of concern
insider attacker behavioral models and analysis
adversarial and game theoretic models of insider threats and attacks
evaluation, experimentation and risk assessment of insider threat detection approaches
mobile devices and insider threats
social networking and insider threats
identifying unknown insider attack patterns
sociotechnical approaches to protecting against insider threat attacks
biometric approaches for identifying potential insider threat behavior.
application of solutions from other domains to address insider threats
unintentional insider threats
research directions addressing privacy and security