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Titlebook: Innovative Security Solutions for Information Technology and Communications; 8th International Co Ion Bica,David Naccache,Emil Simion Confe

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樓主: SPIR
41#
發(fā)表于 2025-3-28 17:22:56 | 只看該作者
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發(fā)表于 2025-3-28 21:03:48 | 只看該作者
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發(fā)表于 2025-3-29 01:32:20 | 只看該作者
Evaluation of Lightweight Block Ciphers for Embedded Systemsower devices which usually communicate through wireless connections. To avoid security and reliability problems, efficient cryptographic algorithms must be used for authentication, key exchange and message encryption. Due to the wide range of such algorithms and their characteristics, some ciphers a
44#
發(fā)表于 2025-3-29 07:02:15 | 只看該作者
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發(fā)表于 2025-3-29 08:00:44 | 只看該作者
A Novel Fast and Secure Chaos-Based Algorithm for Image Encryptione algorithm for image encryption scheme based on chaotic generators is proposed. In the proposed method, permutation-diffusion design is used to create computationally secure encryption primitives and the integer sequences obtained by the sorting of chaotic Logistic map generator by descending order
46#
發(fā)表于 2025-3-29 12:20:14 | 只看該作者
Efficient Montgomery Multiplication on GPUste fields. Contemporary processors are not designed to support such operations in a productive manner, since most of them natively work on 8 to 64 bit word sizes. Thus, an expensive cryptographic accelerator is frequently required to offload the computational burden. In this paper, we focus on a hig
47#
發(fā)表于 2025-3-29 17:32:07 | 只看該作者
48#
發(fā)表于 2025-3-29 20:22:45 | 只看該作者
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發(fā)表于 2025-3-30 03:11:00 | 只看該作者
A Cooperative Black Hole Node Detection and Mitigation Approach for MANETstion, researchers are working specifically on the security issues in MANETs, and many secure routing protocols/measures within the networks have been proposed. Our proposed work presents a more efficient approach for detecting the cooperative black hole attack in a MANET, which is particularly vulne
50#
發(fā)表于 2025-3-30 07:19:47 | 只看該作者
Up-High to Down-Low: Applying Machine Learning to an Exploit Databasepe classifications is public exploit databases. Unfortunately, these databases contain only meta-data (high level or abstract data) of these exploits. Considering that classification depends on the raw measurements found in the field, these databases have been overlooked. In this study, we offer two
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