由于数据记录通常比属性多,这样的要求不容易满足。 5 ATTACKS TO DECISION TREE 首先分析了SecureBoost面临的隐私风险(在推理阶段,攻击者重复提交查询以获得每个节点的属性。文章特别设计了联邦学习中的攻击,因为攻击者能够找到每个训练实例从根到叶遍历的路径。通过在推理阶段恢复节点属性,攻击者能够根据被攻击在树上的遍...
Federated learning (FL) has recently emerged as a promising solution under this new reality. Existing FL protocol design has been shown to exhibit vulnerabilities which can be exploited by adversaries both within and without the system to compromise data privacy. It is thus of paramount importance...
Federated learning (FL) has recently emerged as a promising solution under this new reality. Existing FL protocol design has been shown to exhibit vulnerabilities which can be exploited by adversaries both within and outside of the system to compromise data privacy. It is thus of paramount ...
Federated Learning (FL) offers innovative solutions for privacy-preserving collaborative machine learning (ML). Despite its promising potential, FL is vulnerable to various attacks due to its distributed nature, affecting the entire life cycle of FL services. These threats can harm the model's utilit...
作者应该是参考了《How To Backdoor Federated Learning》这篇文章(替换攻击的鼻祖了,很久远了,)最后的推导结论是 L~mt+1≈nη(X−Gt)+Gt Full Combination Backdoor Attack 1)Generate Full Combination Trigger. 这里面生成的trigger,包含的种类为M个,(理解为m个小trigger组合,其共有M种可能,减去全空和...
Federated learning allows secure collaboration across organizations, improving AI models without compromising sensitive data. Researchers are integrating AI with quantum computing to develop robust cryptographic solutions that resist decryption attempts. Moreover, Explainable AI (XAI) is making cybersecurity ...
P. Gupta, K. Yadav, B.B. Gupta, M. Alazab, T.R. Gadekallu, A novel data poisoning attack in federated learning based on inverted loss function. Comput. Secur.130, 103270 (2023) ArticleGoogle Scholar B. Zhao, Y. Lao, inProceedings of the AAAI Conference on Artificial Intelligence. Clpa...
Data Poisoning and Leakage Analysis in Federated Learning proper amount of randomized noise and the proper location to add such noise for effective mitigation of gradient leakage threats against training data privacy... W Wei,T Huang,Z Yahn,... - Springer, Cham 被引量: 0发表: 2025年 Mitigati...
Sawsan Abdul R, Hanine T, Chamseddine T, Azzam M (2020) Internet of things intrusion detection: centralized, on-device, or federated learning? IEEE Netw 34(6):310–317 Article Google Scholar Security N. Common malware persistence mechanisms. https://resources.infosecinstitute.com/common-malw...
Federated Parameter-Efficient Fine-Tuning (FedPEFT) is a technique that combines parameter-efficient fine-tuning (PEFT) with federated learning (FL) to improve the efficiency and privacy of training... Cyber Security News Hackers Cloning Websites, Exploiting RCE Flaws To Gain Access To Shopping Pla...