University Structure

Laboratory of Cryptographic Methods of Information Security

The Laboratory of Cryptographic Methods of Information Security addresses present-day challenges in cryptography, coding theory, steganography, and security of AI-based systems.

The laboratory actively explores the following fields: 

  • coding methods in cryptography, including post-quantum cryptography; 

  • steganography and digital watermarks. Data protection and insert detection;

  • systems and methods for multi-factor authentication;

  • data security and user privacy in distributed storage systems;

  • blockchain technologies;

  • AI systems security.

Researchers at the laboratory develop novel post-quantum security methods, test cryptographic solutions, design systems for steganographic integration of various data, and build new security protocols for advanced processing, storage, and transfer systems.



  • development and testing of practical solutions to ensure cybersecurity in banking (2021);

  • study of promising types of algebraic noise-immune codes and the development of algorithms for their fast decoding for on-board equipment of long-term spacecrafts (2020);

  • design and study of post-quantum cryptography systems based on correction codes (2019);

  • bug protection in flash memory (2016);

In progress:

  • Technologies for protecting information and functional safety of AI-based systems (2022-present);

  • AI methods for cyberphysical systems (2020-present).


Over the past two years, the laboratory’s team produced the following significant results:

  • a model of a data storage system for decentralized networks based on blockchain technologies;

  • an optimization method for Peterson's algorithm for decoding binary Goppa codes in cryptosystems based on coding theory; 

  • a patented modification of the McEliece cryptosystem for post-quantum cryptography based on generalized codes;

  • methods for reducing the key size in post-quantum cryptosystems based on error correction codes;

  • validated methods for detecting attacker groups in systems ensuring cybersecurity of next-gen networks, and much more.

Educational programs

  • Bachelor’s program: Information Security (in Russian);

  • Master’s program: Information Security (in Russian and English).


  • Russian Railways;

  • Rostelecom;

  • Sberbank;

  • Gazprom Neft;

  • StarLine;

  • ARSIB;

  • St. Petersburg’s Committee on Informatization and Communications;

  • St. Petersburg Federal Research Center of the Russian Academy of Sciences.


  • Ometov, A., Bezzateev, S., Mäkitalo, N., Andreev, S., Mikkonen, T., & Koucheryavy, Y. (2018). Multi-Factor Authentication: A Survey. Cryptography, 2(1), 1;

  • Bezzateev, S., & Shekhunova, N. A. (2019). Totally decomposed cumulative Goppa codes with improved estimations. Designs, Codes and Cryptography, 87(2–3), 569-587;

  • Bezzateev, S. V., & Voloshina, N. V. (2017). Masking Compression based on Weighted Image Structure Model. Informatsionno-upravliaiushchie Sistemy, 6(91), 88-95;

  • Ometov, A., Bardinova, Y., Afanasyeva, A., Masek, P., Zhidanov, K., Vanurin, S., Sayfullin, M., Shubina, V., Komarov, M., & Bezzateev, S. (2020). An Overview on Blockchain for Smartphones: State-of-the-Art, Consensus, Implementation, Challenges and Future Trends. IEEE Access, 8, 103994–104015;

  • Bezzateev, S., & Shekhunova, N. A. (2018). Lower Bounds on the Covering Radius of the Non-Binary and Binary Irreducible Goppa Codes. IEEE Transactions on Information Theory, 64(11), 7171-7177;

  • Davydov, V. V., & Bezzateev, S. (2020). Accident Detection in Internet of Vehicles using Blockchain Technology.

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