Fast Secure and Anonymous Key Agreement Against Bad Randomness for Cloud Computing

Meng, Xinyu; Zhang, Lei; Kang, Burong

doi:10.1109/tcc.2020.3008795

Cited by 11 publications

(2 citation statements)

References 36 publications

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“…A cloud user can send a message securely after the vehicular cloud is formed 12 . To establish a secure channel in a cloud environment, researchers in a study 13 proposed a certificate‐less 0‐RTT (round trip time) anonymous authenticated key agreement protocol. Because of 0‐RTT, this technique exhibits high speed in establishing a secure connection.…”

Section: Related Workmentioning

confidence: 99%

Framework of data privacy preservation and location obfuscation in vehicular cloud networks

Al-Balasmeh

Singh

2021

Concurrency and Computation

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Summary The leakage of sensitive data of users and global positioning system location trajectories from different cloud computation sources have increased in daily lives. This critical problem can influence users' lives because attackers try to misuse the leaked information. In this study, we addressed the critical problem pertaining to the privacy of personal identification information (PII) and location information over vehicular cloud networks (VCNs). The problem was addressed by proposing a data and location privacy (DLP) framework that preserves data privacy in terms of the anonymity of PII and provides location privacy for users' trajectories through the obfuscation technique. The proposed DLP framework contains five stages: registration with VCN server, processing of PII/data privacy block, segregation of obfuscation data, authentication, and provision of cryptographic security. The result analysis shows that the proposed mechanism is able to generate obfuscated trajectories and successfully recomputes the original trajectories at the server side.

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Section: Related Workmentioning

confidence: 99%

Framework of data privacy preservation and location obfuscation in vehicular cloud networks

Al-Balasmeh

Singh

2021

Concurrency and Computation

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“…It is timesaving for the implementations of PKE systems to use the public system parameters. However, recent research results show that PKE schemes may suffer from parameter subversion attacks (PSA) which allow adversaries to fully control the public system parameters [20,23,[27][28][29][30][31] and hence compromise the security of the corresponding PKE schemes. For instance, the elliptic curve cryptosystem specified in NIST FIPS 186-4 standard has been analyzed to be insecure due to the malicious manipulation of the elliptic curves [23].…”

Section: Introductionmentioning

confidence: 99%

Selective-Opening Security for Public-Key Encryption in the Presence of Parameter Subversion

Kang

Huang

Zhang

2021

Security and Communication Networks

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In public-key encryption (PKE), ciphertexts received by a receiver may be possibly correlated and the security of a PKE relies on honestly generated system parameters. Security against selective opening attacks (SOA) for PKE guarantees that even when an attacker has broken into a subset of honestly generated ciphertexts and opened them (i.e., seeing plaintexts and random bits), the unopened ciphertexts remain secure. While security against parameter subversion attacks (PSA) for PKE requires that even when the public system parameters are maliciously generated, a PKE scheme should be secure. In this paper, we initiate the study of PKE secure against both SOA and PSA. To capture SOA and PSA simultaneously, we formulate a new security notion called indistinguishability under selective opening attacks and parameter subversion attacks (IND-SO-PSA). Further, we define the lossy trapdoor function and all-but-many lossy trapdoor function in the presence of PSA (LTF-PSA and ABM-LTF-PSA correspondingly) and propose an instantiation with the efficiently-embeddable group (EG). Applying these new primitives, we construct a PKE scheme that is proven to be IND-SO-PSA secure.

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Privacy-Preserving and Reliable Federated Learning

Zhang

Wang

et al. 2022

Algorithms and Architectures for Parallel Processing

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Fast Secure and Anonymous Key Agreement Against Bad Randomness for Cloud Computing

Cited by 11 publications

References 36 publications

Framework of data privacy preservation and location obfuscation in vehicular cloud networks

Framework of data privacy preservation and location obfuscation in vehicular cloud networks

Selective-Opening Security for Public-Key Encryption in the Presence of Parameter Subversion

Privacy-Preserving and Reliable Federated Learning

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