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

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 104 [1] => 70 ) ) ) [post__not_in] => Array ( [0] => 17633 ) )

5G-Spector: An O-RAN Compliant Layer-3 Cellular Attack Detection Service

Haohuang Wen (The Ohio State University), Phillip Porras (SRI International), Vinod Yegneswaran (SRI International), Ashish Gehani (SRI International), Zhiqiang Lin (The Ohio State University)

Read More

Random Spoofing Attack against Scan Matching Algorithm SLAM (Long)

Masashi Fukunaga (MitsubishiElectric), Takeshi Sugawara (The University of Electro-Communications)

Read More

IdleLeak: Exploiting Idle State Side Effects for Information Leakage

Fabian Rauscher (Graz University of Technology), Andreas Kogler (Graz University of Technology), Jonas Juffinger (Graz University of Technology), Daniel Gruss (Graz University of Technology)

Read More

Don't Interrupt Me – A Large-Scale Study of On-Device...

Marian Harbach (Google), Igor Bilogrevic (Google), Enrico Bacis (Google), Serena Chen (Google), Ravjit Uppal (Google), Andy Paicu (Google), Elias Klim (Google), Meggyn Watkins (Google), Balazs Engedy (Google)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)