plas2022.github.io - Programming Languages and Analysis for Security

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PLAS provides a forum for exploring and evaluating the use of programming language and program analysis techniques for promoting security in the complete range of software systems, from compilers to machine-learned models and smart contracts. The workshop encourages proposals of new, speculative ideas, evaluations of new or known techniques in practical settings, and discussions of emerging threats and problems. We also host position papers that are radical, forward-looking, and lead to lively and insightfu

The scope of PLAS includes, but is not limited to: Language-based techniques for detecting and eliminating side-channel vulnerabilities Programming language techniques and verification applied to security in other domains (e.g. adversarial learning and smart contracts) Software isolation techniques (e.g., SFI and sandboxing) and compiler-based hardening techniques (e.g, secure compilation). Compiler-based security mechanisms (e.g. security type systems) or runtime-based security mechanisms (e.g. inline refe

Bio: Elaine Shi is an Associate Professor at Carnegie Mellon University. Her research interests include cryptography, algorithms, and foundations of blockchains. Prior to CMU, she taught at the University of Maryland and Cornell University. She is a recipient of the Packard Fellowship, the Sloan Fellowship, the ONR YIP Award, the NSA best scientific cybersecurity paper award, and various other best paper awards.

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