Immune System Based Intrusion Detection System (IS-IDS): A Proposed Model (original) (raw)
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Research in the field of computer and network science demands for tools and methodology to test their security effectively. Intrusion Detection System is used to perform the same with a fact that an intruder’s behavior will be noticeably different from that of a legitimate user and would exploit security vulnerabilities. IDS have thousands of alerts per day; some are mistakenly triggered by begin events. This make it extremely difficult to correctly identify alerts related to attack. The use of artificial immune systems in intrusion detection is an appealing concept for two reasons .Firstly the human immune system provides the human body with a high level of protection from invading pathogens in a robust, self organized and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. This research paper proposes a neural network approach to building a network-based IDS, which is inspired by a artificial immune system to find the unseen or unknown attack
Intrusion Detection System using Artificial Immune Systems: A Case Study
International journal of advanced research in computer science and software engineering, 2018
Networks are working at their apical efficiency and are increasing in size by every second; emergence of various threats becomes hindrance in the growth and privacy of the users. The network is vulnerable to security breaches, due to malicious nodes. Intrusion detection systems aim at removing this vulnerability. In this paper, intrusion detection mechanisms for large-scale dynamic networks are investigated. Artificial immune system is a concept that works to protect a network the way immune systems of vertebrates work in nature. This paper also illustrates this artificial immune system, the integration of bio-inspired algorithms, and its functionality with the computer networks.
A Survey of Artificial Immune System based Network Intrusion Detection System
— Increased property and additionally the employment of cyberspace have exposed the subversion before of the organizations, there for there is a need to use of intrusion detection system to protect information system and communication network from malicious attacks and unauthorized access. Associate intrusion detection system (IDS) is also a security system that monitors portable computer systems and network traffic, analyze that traffic to identify getable security breaches and elevate alerts. Associate IDS triggers thousands of alerts per day that's powerful for human users to research them and take acceptable actions. It's very important to chop back the warning alerts, intelligently integrate and correlate them therefore on gift a high level browse of the detected security issue to the administrator.
An intrusion detection system using ideas from the immune system
… . CEC2004. Congress on, 2004
This paper proposes an intrusion detection framework and presents a prototype for an intrusion detection system based on it. This framework takes architectural inspiration from the human immune system and brings desirable features to intrusion detection systems, such as automated intrusion recovery, attack signature extraction, and potential to improve behavior-based detection. These features are enabled through intrusion evidence detection. The prototype, called ADENOIDS, is designed to deal with application attacks, extracting signature for remote buffer overflow attacks. The framework and ADENOIDS are described and experimental results are presented.
Immune-Inspired Algorithm For Network Intrusion Detection
2007
The central challenge with computer security is determining the difference between normal and potentially harmful activity. A promising solution is emerging in the form of Artificial Immune Systems (AIS). These include the theories regarding how the immune system responds to pathogenic material. This paper takes relatively new theory: the Danger theory and Dendritic cells, and explores the relevance of those to the application domain of security and evaluating on the Kdd’99 data.
A Review on Hybrid Intrusion Detection System using Artificial Immune System Approaches
International Journal of Computer Applications, 2013
With the growing advances in the technology the uses of computer systems and the internet is also growing at a rapid rate, and with the increase in their usage vulnerabilities and threats are also increasing tremendously. A large number of approaches have been proposed till now for improving the security of a host system and a network. One of the proposed approach is an Intrusion Detection System (IDS). An IDS works for a system is referred as Host IDS and the one that works for a network is referred as Network IDS. But their functionality is specific to particular host and a network, one does not work as an alternative to another. Thus, an IDS is needed that overcomes the drawbacks of both the systems and combines their advantages to form a Hybrid Intrusion Detection System. An Hybrid IDS captures both host and network data and thereby apply an analysis approach. In order to make these systems robust and effective biologically inspired Artificial Immune System (AIS) approaches can be used that makes the system flexible enough to work in every scenario. This paper provides a review of various IDS and application of various AIS approaches to them.
ARTIFICIAL IMMUNE SYSTEM BASED INTRUSION DETECTION SYSTEMS-A COMPREHENSIVE REVIEW
Intrusion Detection System (IDS) helps us to identify the abnormalities and attacks that can affect the confidentiality, integrity, and availability of the system or network. IDS has a close connection with the processes and mechanisms of Human Immune Systems(HIS) which helps to identify pathogens that can cause harmful diseases in human beings. So it is obvious that mechanisms inspired by HIS can be used in IDS also whose primary function is to detect malicious packets. Artificial immune systems(AIS) thus comes into effect mimicking the processes used by HIS to detect and avoid harmful pathogens. This paper gives a modest insight into intrusion detection techniques that are based on AIS.The works discussed here mainly concentrates on distributed agent based systems. The commonly used algorithms in AIS based IDS is collated and the limitations of existing work as well as future directions in this aspects are discussed.
Towards an Artificial Immune System for Network Intrusion Detection
2002
This paper describes the research towards the use of an artificial immune system (AIS) for network intrusion detection. Specifically, we focus on one significant component of a complete AIS, static clonal selection with a negative selection operator, describing this system in detail. Three different data sets from the UCI repository for machine learning are used in the experiments. Two important factors, the detector sample size and the antigen sample size, are investigated in order to generate an appropriate mixture of general and specific detectors for learning non-self antigen patterns. The results of series of experiments suggest how to choose appropriate detector and antigen sample sizes. These ideal sizes allow the AIS to achieve a good non-self antigen detection rate with a very low rate of self antigen detection. We conclude that the embedded negative selection operator plays an important role in the AIS by helping it to maintain a low false positive detection rate.