Johnathan Wilkes, John Anny (Palo Alto Networks)

By embracing automation, organizations can transcend manual limitations to reduce mean time to response and address exposures consistently across their cybersecurity infrastructure. In the dynamic realm of cybersecurity, swiftly addressing externally discovered exposures is paramount, as each represents a ticking time bomb. A paradigm shift towards automation to enhance speed, efficiency, and uniformity in the remediation process is needed to answer the question, "You found the exposure, now what?". Traditional manual approaches are not only time-consuming but also prone to human error, underscoring the need for a comprehensive, automated solution. Acknowledging the diversity of exposures and the array of security tools, we will propose how to remediate common external exposures, such as open ports and dangling domains. The transformative nature of this shift is crucial, particularly in the context of multiple cloud platforms with distinct data enrichment and remediation capabilities.

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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)

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Large Language Model guided Protocol Fuzzing

Ruijie Meng (National University of Singapore, Singapore), Martin Mirchev (National University of Singapore), Marcel Böhme (MPI-SP, Germany and Monash University, Australia), Abhik Roychoudhury (National University of Singapore)

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Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks...

Zitao Chen (University of British Columbia), Karthik Pattabiraman (University of British Columbia)

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On the Vulnerability of Traffic Light Recognition Systems to...

Sri Hrushikesh Varma Bhupathiraju (University of Florida), Takami Sato (University of California, Irvine), Michael Clifford (Toyota Info Labs), Takeshi Sugawara (The University of Electro-Communications), Qi Alfred Chen (University of California, Irvine), Sara Rampazzi (University of Florida)

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