CrySP carries out research in a wide variety of topics. Some examples are:

  • Security and privacy in machine learning. Analyzing and preventing the leakage of private information from machine learning models, enabling provenance verification of machine learning models, analyzing model theft and security-relevant failure modes of machine learning models (N. Asokan, Florian Kerschbaum).
  • Secure systems. Designing, analyzing, building (and occasionally breaking) secure and privacy-preserving systems. A key consideration is building systems that are simultaneously secure, easy to use and inexpensive to deploy. (N. Asokan)
  • (Distributed) cryptographic protocols. Designing interactive protocols to enable secure communication, such as key agreement protocols, key distribution schemes, secret sharing schemes, identification schemes, broadcast encryption and oblivious transfer (D. Stinson).
  • Efficient cryptographic algorithms and their implementation. Designing and analyzing cryptographic primitives such as block and stream ciphers, public-key encryption schemes, signature schemes, message authentication codes, key establishment protocols, and pairing-based cryptography (D. Stinson).
  • Cryptographic hash functions. Analyzing the security of iterated design techniques and the random oracle model and constructing families of universal hash functions (D. Stinson).
  • Privacy-preserving communications networks. Creating privacy-preserving communications networks with better security, privacy, efficiency, and scalability properties than existing ones. (I. Goldberg)
  • Off-the-Record Messaging. Improving the user interface, robustness, and group communication abilities of Off-the-Record Messaging, or OTR. (I. Goldberg)
  • Censorship Resistance. Designing, developing, and deploying censorship resistance technologies, examining the motivations of the censor and the resister, and analyzing the game-theoretic aspects of their interactions. (I. Goldberg)
  • Private Information Retrieval. Creating Private Information Retrieval (PIR) protocols that are computationally and communicationally efficient, while also providing for Byzantine robustness. (I. Goldberg)
  • Efficient Zero-Knowledge Proofs. Developing batch techniques for Zero-Knowledge Proofs (ZKPs) that make a larger variety of complex ZKPs more efficient; developing a software library that can be easily used by programmers without expertise in ZKPs to prove and verify simple, complex, and batched statements. (I. Goldberg)
  • Security and privacy for smartphone users. Developing security and privacy technologies that allow smartphone users to use mobile apps in a secure and privacy-protecting way. (U. Hengartner).
  • Location privacy. Developing privacy-preserving technologies for users of location-based services. (U. Hengartner).
  • Genomic Privacy. Developing privacy-preserving technologies to protect the storage and processing of genomic data. (U. Hengartner).
  • Privacy for (mobile) social networking. Designing privacy-preserving technologies for users of (mobile) online social networking sites. (U. Hengartner).
  • Cryptographic and online voting. Designing and analyzing voting protocols with high usability and voter-verifiable correctness (U. Hengartner).
  • Response and recovery strategies. Evaluating and designing effective incident response strategies to ensure business continuity (I. McKillop).
  • Security assessment and audit. Applying system vulnerability and risk assessment techniques with a particular focus on the financial services and health sectors. (I. McKillop).
  • Computation over encrypted data and programs. Developing theoretical and practical foundations for secure computation over encrypted data and programs (functional encryption, homomorphic encryption, multi-party computation, multilinear maps and program obfuscation) (S. Gorbunov).
  • Cryptocurrencies. Developing and building new cryptocurrencies (S. Gorbunov).