Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
In Artificial Immune Systems (AIS), negative selection algorithms are used widely. This paper presents the author's research in improving the negative selection algorithm to increase the performance of AIS applications for detecting computer virus. Our algorithm’s time complexity is equal to and its space complexity is less than those mentioned in [7]. | Nguyễn Văn Trường và cs Tạp chí KHOA HỌC & CÔNG NGHỆ 72(10): 53 - 58 IMPROVING NEGATIVE SELECTION ALGORITHM IN ARTIFICIAL IMMUNE SYSTEMS FOR COMPUTER VIRUS DETECTION Nguyen Van Truong1, Pham Dinh Lam2* 1 College of Education –TNU; 2 Board of Information Technology – TNU ABSTRACT In Artificial Immune Systems (AIS), negative selection algorithms are used widely. This paper presents the author's research in improving the negative selection algorithm to increase the performance of AIS applications for detecting computer virus. Our algorithm’s time complexity is equal to and its space complexity is less than those mentioned in [7]. Furthermore, these complexities are irrelevant to the size of detector set used. This new valuable characteristic makes it especially suitable for AISs having ability to detect viruses 100% accurately even with very large data space. Keywords: Artificial immune system, Negative selection algorithm, Intrusion detection system, self, detector INTRODUCTION The idea comes from biology has led to the appearance of some new research areas such as: artificial neural networks, genetic algorithms, etc. AIS is an approach to artificial intelligence system to solve problems based on the principles, functions and operational model of biological immune system. Like the biological immune system, AIS has a number of important characteristics such as resistance to noise, unsupervised learning, memory, distribution, and selforganization. AIS is evaluated as a new and effective soft computing method. AIS can be applied in many fields such as machine learning, robotics, learning control, optimization, etc. It is well known through the applications in the field of computer security and information security; especially in building up the Intrusion Detection Systems (IDS), that can protect computer systems against intruders and the destruction of computer viruses or other malicious software system. General model of IDS are shown in Figure 1 .
