Персона: Запечников, Сергей Владимирович
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Институт интеллектуальных кибернетических систем
Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.
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- ПубликацияОткрытый доступSystematization of knowledge: privacy methods and zero knowledge proofs in corporate blockchains(2023) Konkin, A.; Zapechnikov, S.; Запечников, Сергей ВладимировичNowadays enterprises implement blockchain technology in various industries, including finance, logistics, and other sectors. While the core idea behind blockchain is to decentralize storage, enterprises need to address privacy issues of replicated data. One of the methods to solve privacy in the blockchain is to adjust zero-knowledge-proof protocols. We comprehensively review blockchain privacy techniques employing zero-knowledge proofs and other cryptographic techniques and discuss the World and Russian standardization processes in blockchain privacy techniques.
- ПубликацияОткрытый доступPrivacy-Preserving Machine Learning as a Tool for Secure Personalized Information Services(2020) Zapechnikov, S.; Запечников, Сергей Владимирович© 2020 The Authors. Published by Elsevier B.V.The article deals with the problems of cryptographic protection of data processing algorithms and techniques. They are novel techniques allowing to process private information without disclosing it to persons engaged in processing. One of the main applications of such security tools is the creation of personalized information services, which opens up new opportunities for business and reduces the risks of unauthorized access to personal data. We review important building blocks for cryptographic protection of data processing, such as zero-knowledge proofs, secure multi-party computations, and homomorphic encryption. Often, personalized information services are based on data mining and machine learning, so privacy-preserved machine learning is a very important building block for them. We analyze the concept of differential privacy which serves as the basis for privacy-preserving machine learning and some other cryptographic schemes. At the end of the paper, we forecast the perspectives of encrypted data processing.
- ПубликацияОткрытый доступAnalysis of Secure Protocols and Authentication Methods for Messaging(2020) Sukhodolskiy, I.; Zapechnikov, S.; Запечников, Сергей Владимирович© 2020 The Authors. Published by Elsevier B.V.Messengers became popular means of communication among people for both personal and corporate purposes. However, there are many cases of data leakage, as well as the facts of hacking and wiretapping messages by third parties. This paper explores the security of popular messaging protocols both among individual users and user groups.
- ПубликацияОткрытый доступOn the key composition for post-quantum group messaging and file exchange(2021) Bobrysheva, J.; Zapechnikov, S.; Запечников, Сергей Владимирович© 2020 Elsevier B.V.. All rights reserved.Advances in the development of quantum technologies force to create new methods of secure information transfer over insecure networks and channels. In this article, we analyze some important properties of secure group messaging resilient to quantum computer attacks: message authentication and asynchronous key update. We consider options for ensuring message authentication and detect the difference between the requirements for this property in group communications and point-to-point channels. We define the structure of key information and preshared key packages for the new protocol based on the classic X3DH protocol.
- ПубликацияОткрытый доступHistorical notes on Russian cryptography(2023) Epishkina, A.; Zapechnikov, S.; Belozubova, A.; Епишкина, Анна Васильевна; Белозубова, Анна Игоревна; Запечников, Сергей ВладимировичThe article is devoted to the main milestones in the development of encryption techniques and mathematical methods of cryptography in Russia from the period of ancient Russia up to the nowadays. We break down the history of Russian cryptography into several periods and highlight the periods of cryptography development, analyze the most notable achievements and summarize the main results and applications of each period. The review of scientific research and standardization of cryptography in modern Russia is given. The progress of related areas is briefly analyzed: steganography and protection against falsification of documents.
- ПубликацияОткрытый доступContemporary trends in privacy-preserving data pattern recognition(2021) Zapechnikov, S.; Запечников, Сергей Владимирович© 2020 Elsevier B.V.. All rights reserved.The article is devoted to the recent scientific problem of privacy-preserving data pattern recognition. The purposes of the work are to systematize the security models for such tasks, to identify algorithmic tools that can be used to ensure the privacy of the data processing, and application of models and to analyze the privacy-preserving data pattern recognition systems. The article presents the main concepts and some definitions related to privacy-preserving machine learning, gives a systematization of related problems, and notes modern and promising areas of development of machine learning. Special cryptographic methods and protocols are correlated to the solved problems. A brief description of the known privacy-preserving data pattern recognition systems is given. Unsolved problems in the field of privacy-preserving data pattern recognition are considered.
- ПубликацияОткрытый доступPrivacy methods and zero-knowledge poof for corporate blockchain(2021) Konkin, A.; Zapechnikov, S.; Запечников, Сергей Владимирович© 2020 Elsevier B.V.. All rights reserved.Nowadays distributed ledger technology or blockchain is widely used in the corporate sector for various industries. Although implementation issues (coding practice, lack of capabilities, etc.) are not among the major barriers for the technology adaption, there are still some informational security challenges to adjust and scale blockchain networks for corporate usage. One of them is to provide functionality for private transactions stored in a blockchain. Some methods including mix networks, ring signatures, and off-chain protocols were applied to meet the privacy requirements. However, these methods have some limitations associated with the key blockchain characteristics such as decentralized storing system and immutability verification of private data. This article examines zero-knowledge proof (ZKP) methods for corporate blockchain networks. The article provides the review of existing methods for private transactions, discovers the implementation of ZKP methods, also performance and scalability issues are discussed.