Tim Pappa (Walmart)

The evolution of vulnerability markets and disclosure norms has increasingly conditioned vulnerability and vulnerability patching disclosures to audiences. A limited collection of studies in the past two decades has attempted to empirically examine the frequency and the nature of attacks or threat activity related to the type of vulnerability disclosure, generally finding that the frequency of attacks appeared to decrease after disclosure. This presentation proposes extraordinary disclosures of software removal to disrupt collection baselines, suggesting that disclosure of unnamed but topical enterprise software such as enterprise deception software could create a singular, unique period of collection to compare to baseline cyber threat activity. This disruptive collection event could provide cyber threat intelligence teams and SOCs greater visibility into the periodicity and behaviors of known and unknown threat actors targeting them. The extraordinary disclosure of the removal of enterprise software could suggest there are present vulnerabilities on networks, which could prompt increased cyber threat actor attention and focused threat activity, because there is uncertainty about the removal of the software and the replacement of software, depending on the perceived function and capability of that software. This presentation is exploratory, recognizing that there is perhaps anecdotal but generally limited understanding of how cyber threat actors would respond if an organization disclosed the removal of enterprise software to audiences. This presentation proposes an integrated conceptual interpretation of the foundational theoretical frameworks that explain why and how people respond behaviorally to risk and reward and anticipated regret, applied in a context of influencing threat actors with extraordinary disclosures of removal of enterprise software.

View More Papers

DeepGo: Predictive Directed Greybox Fuzzing

Peihong Lin (National University of Defense Technology), Pengfei Wang (National University of Defense Technology), Xu Zhou (National University of Defense Technology), Wei Xie (National University of Defense Technology), Gen Zhang (National University of Defense Technology), Kai Lu (National University of Defense Technology)

Read More

FP-Fed: Privacy-Preserving Federated Detection of Browser Fingerprinting

Meenatchi Sundaram Muthu Selva Annamalai (University College London), Igor Bilogrevic (Google), Emiliano De Cristofaro (University of California, Riverside)

Read More

BliMe: Verifiably Secure Outsourced Computation with Hardware-Enforced Taint Tracking

Hossam ElAtali (University of Waterloo), Lachlan J. Gunn (Aalto University), Hans Liljestrand (University of Waterloo), N. Asokan (University of Waterloo, Aalto University)

Read More

Detecting Voice Cloning Attacks via Timbre Watermarking

Chang Liu (University of Science and Technology of China), Jie Zhang (Nanyang Technological University), Tianwei Zhang (Nanyang Technological University), Xi Yang (University of Science and Technology of China), Weiming Zhang (University of Science and Technology of China), NengHai Yu (University of Science and Technology of China)

Read More