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Titlebook: Security and Privacy in Communication Networks; 15th EAI Internation Songqing Chen,Kim-Kwang Raymond Choo,Aziz Mohaisen Conference proceedi

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21#
發(fā)表于 2025-3-25 06:56:33 | 只看該作者
Trojan Attack on Deep Generative Models in Autonomous Driving
22#
發(fā)表于 2025-3-25 08:11:31 | 只看該作者
23#
發(fā)表于 2025-3-25 12:31:13 | 只看該作者
Secure Consistency Verification for Untrusted Cloud Storage by Public Blockchainsontract race conditions). We analyze and harden the security of ContractChecker protocols under these proposed new attacks..We implement a functional prototype of the ContractChecker on Ethereum/Solidity. By experiments on private and public Ethereum testnets, we extensively evaluate the cost of the
24#
發(fā)表于 2025-3-25 17:16:22 | 只看該作者
An Enhanced Verifiable Inter-domain Routing Protocol Based on Blockchainconsensus algorithm used in the blockchain. We theoretically prove the correctness of BRVM, and implement a prototype based on Quagga and Fabric. Our experiments show that BRVM can solve this kind of promise-violating problem caused by multiple collusion nodes, and about 21% faster than SPIDeR [.] i
25#
發(fā)表于 2025-3-25 20:34:06 | 只看該作者
Edge-Assisted CNN Inference over Encrypted Data for Internet of Thingsrivacy of IoT data to be offloaded. In our scheme, the most time-consuming convolutional and fully-connected layers are offloaded to edge computing devices and the IoT device only performs efficient encryption and decryption on the fly. As a result, our scheme enables IoT devices to securely offload
26#
發(fā)表于 2025-3-26 02:13:10 | 只看該作者
27#
發(fā)表于 2025-3-26 07:19:26 | 只看該作者
28#
發(fā)表于 2025-3-26 10:22:32 | 只看該作者
DeepCG: Classifying Metamorphic Malware Through Deep Learning of Call Graphsmethod, dubbed ., which enables automatic feature learning of metamorphic malware via deep learning. Specifically, we encapsulate the information of each call graph into an image that is then fed into deep convolutional neural networks for classifying the malware family. Particularly, due to its bui
29#
發(fā)表于 2025-3-26 15:33:03 | 只看該作者
ChaffyScript: Vulnerability-Agnostic Defense of JavaScript Exploits via Memory Perturbatione and 12.96% for FireFox. The maximal memory overhead JS heap usage, observed using the Octane benchmark, was 8.2%. To demonstrate the deployment flexibility of ., we have integrated it into a web proxy.
30#
發(fā)表于 2025-3-26 19:05:12 | 只看該作者
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