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.

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Separation is Good: A Faster Order-Fairness Byzantine Consensus

Ke Mu (Southern University of Science and Technology, China), Bo Yin (Changsha University of Science and Technology, China), Alia Asheralieva (Loughborough University, UK), Xuetao Wei (Southern University of Science and Technology, China & Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, SUSTech, China)

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Flow Correlation Attacks on Tor Onion Service Sessions with...

Daniela Lopes (INESC-ID / IST, Universidade de Lisboa), Jin-Dong Dong (Carnegie Mellon University), Pedro Medeiros (INESC-ID / IST, Universidade de Lisboa), Daniel Castro (INESC-ID / IST, Universidade de Lisboa), Diogo Barradas (University of Waterloo), Bernardo Portela (INESC TEC / Universidade do Porto), João Vinagre (INESC TEC / Universidade do Porto), Bernardo Ferreira (LASIGE, Faculdade de…

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