Akul Goyal (Provenance Security, Inc.), Adam Bates (Provenance Security, Inc.)

Provenance-based security applications are showing tremendous promise in the academic literature, but successfully transition these technologies to practice will require community stakeholders to demonstrate the business potential of provenance analysis. Customer Discovery is a structured process through which early-stage start-ups can validate the commercial potential of an idea through direct interaction with potential customers. As a provenance-based security start-up, we conducted hundreds of customer discovery interviews, and believe that many of our findings would be of interest to the broader academic community. In this position paper, we summarize our findings and consider how they could inform future research on provenance analysis.

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Automating Function-Level TARA for Automotive Full-Lifecycle Security

Yuqiao Yang (UESTC), Yongzhao Zhang (UESTC), Wenhao Liu (GoGoByte Technology), Jun Li (GoGoByte Technology), Pengtao Shi (GoGoByte Technology), DingYu Zhong (UESTC), Jie Yang (UESTC), Ting Chen (UESTC), Sheng Cao (UESTC), Yuntao Ren (UESTC), Yongyue Wu (UESTC), Xiaosong Zhang (UESTC)

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ProtocolGuard: Detecting Protocol Non-compliance Bugs via LLM-guided Static Analysis...

Xiangpu Song (School of Cyber Science and Technology, Shandong University), Longjia Pei (School of Cyber Science and Technology, Shandong University), Jianliang Wu (Simon Fraser University), Yingpei Zeng (Hangzhou Dianzi University), Gaoshuo He (School of Cyber Science and Technology, Shandong University), Chaoshun Zuo (Independent Researcher), Xiaofeng Liu (School of Cyber Science and Technology, Shandong University), Qingchuan…

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Beyond Raw Bytes: Towards Large Malware Language Models

Luke Kurlandski (Rochester Institute of Technology, Rochester New York USA), Harel Berger (Ariel University, Israel), Yin Pan (Rochester Institute of Technology, Rochester New York USA), Matthew Wright (Rochester Institute of Technology, Rochester New York USA)

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