Titlebook: Information Security Applications; 20th International C Ilsun You Conference proceedings 2020 Springer Nature Switzerland AG 2020 formal me

ABYSS

安定

官僚統(tǒng)治

A Secure and Self-tallying E-voting System Based on Blockchainers for ballot security and these random numbers will be cancelled out when multiplying all ballots to allow counting the ballots. Secondly, we adopt non-interactive zero knowledge proof to make sure these ballots are valid. Our scheme is proved to be secure.

帳單

Zero-Knowledge Proof System for Fully Anonymous Attribute Based Group Signatures from Lattices with per proposes a new zero-knowledge protocol to support provers to convince verifiers, that attributes used for creating the signature are valid and have naive tokens. Moreover, this paper offers a new Attribute-Based Group Signature (ABGS) scheme, that uses the proposed protocol and achieves full anonymity.

tattle

Strengthened PAKE Protocols Secure Against Malicious Private Key Generatorersonating the server. Then, we propose two strengthened PAKE (. and .) protocols that prevents such malicious PKG’s passive/active attacks. Also, we discuss security of the . and . protocols, and compare relevant protocols in terms of efficiency and security.

易受刺激

可互換

0302-9743 ckchain; Cryptography; Security with AI and Machine Learning; IoT Security; Hardware Security; and Selected Security Issues..978-3-030-39302-1978-3-030-39303-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

背景

uncertain

Reversible Data Hiding in Homomorphic Encrypted Images Without Preprocessingg before data embedding. Compared with the state-of-the-art methods, higher embedding capacity can be obtained with the proposed method while the original or processed image can be correctly generated.

里程碑

Model Selection for Data Analysis in Encrypted Domain: Application to?Simple Linear Regressionng 4-fold cross validation, 4 different estimates of our model’s errors are calculated. And then we use bias and variance extracted from these errors to find the best model. We perform an experiment on a dataset extracted from Kaggle and show that our approach can homomorphically regress a given encrypted data without decrypting it.