Tim Pappa (Walmart)

Cyber threat actors generally create branding content to promote their reputation. While threat actor branding content could include carders masquerading as hacktivists, for example, the reputational branding of cyber threat actors is generally considered to be a singular, symbolic display of their threat and capabilities. This presentation suggests that Security Operations Centers (SOC) and cyber threat intelligence communities could proactively collect unique forensic and observational behavioral threat information on threat actors by manipulating their reputational content, anticipating threat actors will respond or react behaviorally when their reputations are questioned or ridiculed publicly. This presentation is exploratory, recognizing that most accounts of manipulating cyber threat actor reputational content are anecdotal. This presentation proposes an integrated conceptual interpretation of the foundational theoretical frameworks that explain why and how people respond behaviorally to content made for them, applied in a context of influencing threat actors with generative artificial intelligence content.

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Shaofei Li (Key Laboratory of High-Confidence Software Technologies (MOE), School of Computer Science, Peking University), Feng Dong (Huazhong University of Science and Technology), Xusheng Xiao (Arizona State University), Haoyu Wang (Huazhong University of Science and Technology), Fei Shao (Case Western Reserve University), Jiedong Chen (Sangfor Technologies Inc.), Yao Guo (Key Laboratory of High-Confidence Software Technologies…

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Efficient Normalized Reduction and Generation of Equivalent Multivariate Binary...

Arnau Gàmez-Montolio (City, University of London; Activision Research), Enric Florit (Universitat de Barcelona), Martin Brain (City, University of London), Jacob M. Howe (City, University of London)

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WIP: Hidden Hub Eavesdropping Attack in Matter-enabled Smart Home...

Song Liao, Jingwen Yan, Long Cheng (Clemson University)

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Securing Lidar Communication through Watermark-based Tampering Detection (Long)

Michele Marazzi, Stefano Longari, Michele Carminati, Stefano Zanero (Politecnico di Milano)

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