2021年12月,欧盟网络与信息安全局(ENISA)发布了题为《安全机器学习算法》(Securing Machine Learning Algorithms)的报告。 报告详细分析了当前机器学习算法的分类,针对机器学习系统的攻击和威胁,具体的威胁包括数据投毒、对抗攻击、数据窃取。报告给出了安全框架、标准等方面的具体和可操作性的安全控制
In conjunction with the realistic and diverse characteristics of the CIC-IoT2023 dataset, the study's empirical assessments provide invaluable knowledge for determining the most effective machine learning algorithms and fortification strategies to protect IoT infrastructures. Furthermore, this study ...
Caroline, B., B. Christian, B. Stephan, B. Luis, D. Giuseppe, E. Damiani, H. Sven, et al. 2021. Securing machine learning algorithms. Google Scholar Caruana, R., Y. Lou, J. Gehrke, P. Koch, M. Sturm, and N. Elhadad. 2015. Intelligible models for healthcare: Predicting pneumon...
Automated Monitoring and Evaluation DeepSeek's powerful data analytics optimize the AI Guardrail by enabling real-time monitoring of generated content. Leveraging machine learning algorithms, it continuously refines content filtering accuracy. Combined with natural language processing (NLP), it can also id...
There are various works about GRU in IoT security. The focal point of this research involves utilizing machine learning algorithms, with a particular emphasis on deep learning techniques, to fortify security within wireless sensor networks. This article addresses the hurdles wireless sensor networks enco...
Artificial Intelligence has come a long way since its inception in the 1950s. What began as a field focused on simple rule-based systems has blossomed into a complex landscape of machine learning algorithms, neural networks, and advanced statistical models. The past five years, in particular...
The paper also highlights several open research topics, such as the need for standardized encryption algorithms, the potential of machine learning algorithms to strengthen security and the accompanying challenges, the application of blockchain for resolving security issues in the IoT domain, and the ...
or the attacker may be able to bias the search to particular records they suspect might be present. For instance, they might be able to extract examples of Personal Identifiable Information (PII) used in training the LLM. To learn more, seeAlgorithms that Remember: Model Inversion Attacks and...
Anomaly Detection: Utilizing machine learning algorithms to learn normal behaviors within the network and flag deviations. This can be particularly effective in spotting sophisticated attacks that might bypass traditional detection methods. Incident Response Planning Having a well-defined incident res...
By removing unimportant features, RFE can reduce Dataset dimensionality which enhances the effectiveness of machine learning algorithms. Meanwhile, Data Augmentation can increase the size of the dataset by adding new instances with transformations, which can introduce noise, potentially dilute discriminant ...