Progress of Machine Learning in the Field of Intrusion Detection Systems
International Journal on Cryptography and Information Security(2021)
摘要
With the growth in the use of the Internet and local area networks, malicious attacks and intrusions into computer systems are increasing. Implementing intrusion detection systems have become extremely important to help maintain good network security. Support vector machines (SVMs), a classic pattern recognition tool, have been widely used in intrusion detection. They can handle very large data with high efficiency, are easy to use, and exhibit good prediction behavior. This paper presents a new SVM model enriched with a Gaussian kernel function based on the features of the training data for intrusion detection. The new model is tested with the CICIDS2017 dataset. The test proves better results in terms of detection efficiency and false alarm rate, which can give better coverage and make detection more efficient.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要