Sirvan Almasi (Imperial College London), William J. Knottenbelt (Imperial College London)

Password composition policies (PCPs) are critical security rules that govern how users create passwords for online authentication. Despite passwords remaining the primary authentication method online, there is significant disagreement among experts, regulatory bodies, and researchers about what constitutes effective password policies. This lack of consensus has led to high variance in PCP implementations across websites, leaving both developers and users uncertain. Current approaches lack a theoretical foundation for evaluating and comparing different password composition policies. We show that a structure-based policy, such as the three-random words recommended by UK’s National Cyber Security Centre (NCSC), can improve password security. We demonstrate this using an empirical evaluation of labelled password datasets and a new theoretical framework. Using these methods we demonstrate the feasibility and security of multi-word password policy and extend the NCSC’s recommendation to five words to account for nonuniform word selection. These findings provide an evidence-based framework for password policy development and suggest that current web authentication systems should adjust their minimum word requirements upward while maintaining usability.

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Hyeongjun Choi, Young Eun Kwon, Ji Won Yoon (Korea University)

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Yichen Gong (Tsinghua University), Delong Ran (Tsinghua University), Xinlei He (Hong Kong University of Science and Technology (Guangzhou)), Tianshuo Cong (Tsinghua University), Anyu Wang (Tsinghua University), Xiaoyun Wang (Tsinghua University)

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Repurposing Neural Networks for Efficient Cryptographic Computation

Xin Jin (The Ohio State University), Shiqing Ma (University of Massachusetts Amherst), Zhiqiang Lin (The Ohio State University)

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