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Titlebook: Information and Communications Security; 23rd International C Debin Gao,Qi Li,Xiaofeng Liao Conference proceedings 2021 Springer Nature Swi

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Source Identification from In-Vehicle CAN-FD Signaling: What Can We Expect?icle CAN-FD network from bus signaling and the contributions are four-fold..We hope our results could be used as a step forward and a guidance on securing the commercialization and batch production of in-vehicle CAN-FD network in the near future.
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TranFuzz: An Ensemble Black-Box Attack Framework Based on Domain Adaptation and Fuzzinghat the proposed method can achieve an attack success rate of more than 68% in a real-world CVS attack. Moreover, TranFuzz can also reinforce both the robustness (up to 3.3%) and precision (up to 5%) of the original neural network performance by taking advantage of the adversarial re-training.
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Rectifying Administrated ERC20 Tokensver these contracts. Moreover, the owners of these tokens carry lesser social and legal responsibilities compared to the traditional centralized actors that those tokens intend to disrupt. This entails two major problems: a) the owners of the tokens have the ability to quickly steal all the funds an
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: Model Agnostic Defense against Targeted Poisoning Attacks in Federated Learningures. The aggregation of interpreted values for important features against a baseline input detects the presence of an adversary. The proposed solution scales in terms of attackers and is also robust against adversarial noise in either homogeneous or heterogeneous distribution. The most appealing ab
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GAN-Based Adversarial Patch for Malware C2 Traffic to Bypass DL Detectorused by GAN training. Results show that the adversarial patch generated by GAN can prevent malware C2 traffic from being detected with 51.4% success rate. The higher time efficiency and smaller malware impact make our method more suitable for real attacks.
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Analyzing the Security of OTP 2FA in the Face of Malicious Terminalswhich mostly use two variants of .and observed that almost all of them are vulnerable to this attack. Here, the threat model is practical as the attack components can be installed in the user’s terminal without any root/administrator privilege. Moreover, the attack modules require a small number of
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