Персона: Макаров, Артём Олегович
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A Survey of Aggregate Signature Applications
2020, Makarov, A., Макаров, Артём Олегович
© 2020, Springer Nature Switzerland AG.We survey the applications of aggregate signatures. Signatures of this type allow to aggregate different signatures produced by different users for different messages into one small signature. Given n signatures of n distinct messages, it is possible to combine them into a single signature that can be used to convince any verifier that the n users signed these n original messages. Aggregate signatures are useful for reducing the storage and bandwidth requirements and can be applied in numerous applications. In this paper, we survey these applications including PKI, blockchain, sensor networks, secure routing, fast signatures, software authentication, secure logging, and outsourced databases. For each application, we describe the types of aggregate signatures that could be used, what are the advantages and effects of using aggregate signatures there.
About Asymmetric Execution of the Asymmetric ElGamal Cipher
2020, Varfolomeev, A. A., Makarov, A., Варфоломеев, Александр Алексеевич, Макаров, Артём Олегович
© 2020 IEEE.The paper continues the consideration of the concept of asymmetrically executable cryptosystems (ciphers), introduced by A. A. Varfolomeev at the SibCon 2016 and RusCrypto 2018 conferences, as applied to the ElGamal asymmetric cipher. These cryptosystems (ciphers) significantly increase the difficulty for an attacker to recover plain text with various regulatory restrictions on the size of cryptographic keys. A method for transforming a classical asymmetric cipher into an asymmetrically executable is proposed.
Extended Classification of Signature-only Signature Models
2021, Makarov, A., Varfolomeev, A. A., Макаров, Артём Олегович, Варфоломеев, Александр Алексеевич
© 2021 IEEE.In this paper, we extend the existing classification of signature models by Cao. To do so, we present a new signature classification framework and migrate the original classification to build an easily extendable faceted signature classification. We propose 20 new properties, 7 property families, and 1 signature classification type. With our classification, theoretically, up to 11 541 420 signature classes can be built, which should cover almost all existing signature schemes.