Cherlynn Cha (ExpressVPN)

Alerts serve as the backbone of most SOCs, but alerts alone cannot detect modern, advanced threats without being so noisy that they quickly induce analyst fatigue. Threat hunting has arisen as a complement to alerting, but most SOCs do not operationalize threat hunting with the same rigor as alerting. In this session, we will discuss how SOC teams can overcome this through a model we call Continuous Threat Hunting: using analytic-driven methods to cover more data, but with a standardized approach designed to produce repeatability, effectiveness, and confidence in result.

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Make your IoT environments robust against adversarial machine learning...

Hamed Haddadpajouh (University of Guelph), Ali Dehghantanha (University of Guelph)

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AdvCAPTCHA: Creating Usable and Secure Audio CAPTCHA with Adversarial...

Hao-Ping (Hank) Lee (Carnegie Mellon University), Wei-Lun Kao (National Taiwan University), Hung-Jui Wang (National Taiwan University), Ruei-Che Chang (University of Michigan), Yi-Hao Peng (Carnegie Mellon University), Fu-Yin Cherng (National Chung Cheng University), Shang-Tse Chen (National Taiwan University)

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AutoWatch: Learning Driver Behavior with Graphs for Auto Theft...

Paul Agbaje, Abraham Mookhoek, Afia Anjum, Arkajyoti Mitra (University of Texas at Arlington), Mert D. Pesé (Clemson University), Habeeb Olufowobi (University of Texas at Arlington)

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LMSanitator: Defending Prompt-Tuning Against Task-Agnostic Backdoors

Chengkun Wei (Zhejiang University), Wenlong Meng (Zhejiang University), Zhikun Zhang (CISPA Helmholtz Center for Information Security and Stanford University), Min Chen (CISPA Helmholtz Center for Information Security), Minghu Zhao (Zhejiang University), Wenjing Fang (Ant Group), Lei Wang (Ant Group), Zihui Zhang (Zhejiang University), Wenzhi Chen (Zhejiang University)

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