Yue Xiao (IBM Research), Dhilung Kirat (IBM Research), Douglas Lee Schales (IBM Research), Jiyong Jang (IBM Research), Luyi Xing (Indiana University Bloomington), Xiaojing Liao (Indiana University)

Abstract—A Software Bill of Materials (SBOM) is a detailed inventory that lists the dependencies that make up a software product. Accurate, complete, and up-to-date SBOMs are essential for vulnerability management, reducing license compliance risks, and maintaining high software integrity. The US National Institute of Standards and Technology (NTIA) has established minimum requirements for SBOMs to comply with, especially the correctness and completeness of listed dependencies in SBOMs. However, these requirements remain unexamined in practice. This paper presents the first systematic study on the landscape of SBOMs, including their prevalence, release trends, and characteristics in the Java ecosystem. We developed an end-to-end tool to evaluate the completeness and accuracy of dependencies in SBOMs. Our tool analyzed 25,882 SBOMs and associated JAR files, identifying that 7,907 SBOMs failed to disclose direct dependencies, highlighting the prevalence and severity of SBOM noncompliance issues. Furthermore, 4.97% of these omitted dependencies were vulnerable, leaving software susceptible to potential exploits. Through detailed measurement studies and analysis of root causes, this research uncovers significant security implications of non-compliant SBOMs, especially concerning vulnerability management. These findings, crucial for enhancing SBOM compliance assurance, are being responsibly reported to relevant stakeholders.

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Revisiting EM-based Estimation for Locally Differentially Private Protocols

Yutong Ye (Institute of software, Chinese Academy of Sciences & Zhongguancun Laboratory, Beijing, PR.China.), Tianhao Wang (University of Virginia), Min Zhang (Institute of Software, Chinese Academy of Sciences), Dengguo Feng (Institute of Software, Chinese Academy of Sciences)

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VoiceRadar: Voice Deepfake Detection using Micro-Frequency and Compositional Analysis

Kavita Kumari (Technical University of Darmstadt), Maryam Abbasihafshejani (University of Texas at San Antonio), Alessandro Pegoraro (Technical University of Darmstadt), Phillip Rieger (Technical University of Darmstadt), Kamyar Arshi (Technical University of Darmstadt), Murtuza Jadliwala (University of Texas at San Antonio), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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TZ-DATASHIELD: Automated Data Protection for Embedded Systems via Data-Flow-Based...

Zelun Kong (University of Texas at Dallas), Minkyung Park (University of Texas at Dallas), Le Guan (University of Georgia), Ning Zhang (Washington University in St. Louis), Chung Hwan Kim (University of Texas at Dallas)

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