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Privacy and security enhancement in smart cities using advanced cryptographic techniques. [PDF]
More KD, Pramod D.
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Lightweight semantic compression visual cryptography for secure medical image transmission in IoT systems. [PDF]
Blesswin AJ +5 more
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QRBT: Quantum Driven Reinforcement Learning for Scalable Blockchain Transaction Processing. [PDF]
Lella KK, Mallu SRK.
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Blockchain and federated Q-learning-based secure, fault tolerant, and energy efficient framework for ad hoc networks. [PDF]
Tandon R, Gupta PK, Cheng X.
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Correction: Cellular automata based key distribution for lightweight hybrid image encryption with elliptic curve cryptography. [PDF]
Yogi B, Khan AK, Roy S.
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Adaptive Multi-Model Hierarchical Federated Learning for Robust IoT Intrusion Detection. [PDF]
Latif S, Djenouri D.
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Quantum-resilient cross-trust evaluation for zero trust 5G security. [PDF]
Jeysuriya K, Renjith PN, Sudhakaran G.
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SIAM Journal on Computing, 1991
The property of nonmalleability for the encryption function \(E\) is a stronger extension of the classic notion of semantic security that was introduced by Goldwasser and Micali. This property is defined as follows. For all polynomial-time computable relations \(R\) seeing \(\alpha\in E(x)\) does not help one to find \(\beta\in E(y)\), \(\beta\neq ...
Danny Dolev, Cynthia Dwork, Moni Naor
openaire +2 more sources
The property of nonmalleability for the encryption function \(E\) is a stronger extension of the classic notion of semantic security that was introduced by Goldwasser and Micali. This property is defined as follows. For all polynomial-time computable relations \(R\) seeing \(\alpha\in E(x)\) does not help one to find \(\beta\in E(y)\), \(\beta\neq ...
Danny Dolev, Cynthia Dwork, Moni Naor
openaire +2 more sources

