Rock Stevens (University of Maryland), Faris Bugra Kokulu (Arizona State University), Adam Doupé (Arizona State University), Michelle L. Mazurek (University of Maryland)

Organizations that provide essential services such as electricity, healthcare, and secure financial transactions are required to use digital-security compliance programs to establish a baseline of minimum security. Unfortunately, these compliance programs are known to suffer from a multitude of issues (both in how they are written and in how organizations implement them), resulting in organizations implementing their own security measures to fill actual or perceived compliance gaps. In this study, we survey 40 security professionals from six U.S. essential-service sectors to gain insight into how organizations complement compliance to fix perceived security gaps, which measures worked particularly well, and how their organizations prioritize and evaluate the measures they adopt. We find that organizations complement compliance programs often, with 37 of 40 participants confirming that their organizations have gone beyond what they perceive as mandated compliance measures to mitigate otherwise unaddressed risks. While participants were generally positive about these perceived complementary measures, they also reported challenges related to poor management, information saturation, and difficulty keeping complementary measures up-to-date and relevant. Based on these results, we recommend that compliance standards directly integrate guidance for carefully managing and auditing any perceived complementary measures that an organization chooses to implement and that organizations carefully plan end-to-end deployment and operation before implementing these measures.

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Context-Sensitive and Directional Concurrency Fuzzing for Data-Race Detection

Zu-Ming Jiang (Tsinghua University), Jia-Ju Bai (Tsinghua University), Kangjie Lu (University of Minnesota), Shi-Min Hu (Tsinghua University)

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EMS: History-Driven Mutation for Coverage-based Fuzzing

Chenyang Lyu (Zhejiang University), Shouling Ji (Zhejiang University), Xuhong Zhang (Zhejiang University & Zhejiang University NGICS Platform), Hong Liang (Zhejiang University), Binbin Zhao (Georgia Institute of Technology), Kangjie Lu (University of Minnesota), Raheem Beyah (Georgia Institute of Technology)

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Interpretable Federated Transformer Log Learning for Cloud Threat Forensics

Gonzalo De La Torre Parra (University of the Incarnate Word, TX, USA), Luis Selvera (Secure AI and Autonomy Lab, The University of Texas at San Antonio, TX, USA), Joseph Khoury (The Cyber Center For Security and Analytics, University of Texas at San Antonio, TX, USA), Hector Irizarry (Raytheon, USA), Elias Bou-Harb (The Cyber Center For…

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