Intrusion Detection Using Secured and Efficient Data Mining
نویسندگان
چکیده
An Intrusion detection system (IDS) is a device or a software application that monitors a network or systems for malicious activity or policy violations. Intrusion Detection Systems supports to discover, determine, and identify unauthorized use, duplication, alteration, and destruction of information systems. So, to make intrusion detection system more efficient, the techniques that are more advantageous are used here. The NSL dataset is proposed to train the intrusion detection system. The NSL dataset is used to avoid duplication of entries of intruders in the dataset. The output received by using NSL dataset and previously proposed KDD cup dataset will be compared. Also, the real-time intrusion detection can be done.
منابع مشابه
Multi-Level and Secured Agent-Based Intrusion Detection System
Since Intrusion Detection System IDS has become necessary security tool for detecting attacks on computer network and resources, it is essential to improve previous designs. Recently many mobile agent-based IDSs have been designed, but there are still some drawbacks. Some of these drawbacks are lowdetection efficiency,high false alarm rate and agent security. A multi-level and secured IDS archi...
متن کاملIntrusion Detection based on a Novel Hybrid Learning Approach
Information security and Intrusion Detection System (IDS) plays a critical role in the Internet. IDS is an essential tool for detecting different kinds of attacks in a network and maintaining data integrity, confidentiality and system availability against possible threats. In this paper, a hybrid approach towards achieving high performance is proposed. In fact, the important goal of this paper ...
متن کاملA Fuzzy Neural Network and Multiple Kernel Fuzzy C-means Algorithm for Secured Intrusion Detection System
An Intrusion Detection System (IDS) is a security layer used to detect constant intrusive behavior in information systems. Many intrusion detection systems have been proposed based on the various data mining approaches such as decision tree, clustering, etc. Although the intrusion detection system is efficient way to find the attacks in the system, existing ones have some disadvantages which af...
متن کاملAnomaly Base Network Intrusion Detection by Using Random Decision Tree and Random Projection: A Fast Network Intrusion Detection Technique
Network Intrusion Detection Systems (NIDSs) have become an important component in network security infrastructure. Currently, many NIDSs are rule-based systems whose performances highly depend on their rule sets. Unfortunately, due to the huge volume of network traffic, coding the rules by security experts becomes difficult and time-consuming. Since data mining techniques can build network intr...
متن کاملIntrusion Detection System Using Data Mining
This paper analysis and criticizes the way of using, functioning the intrusion detection system in data mining. Understanding the techniques. A survey on Data Mining based Intrusion Detection Systems phase, intrusion detection system is studied. are analysed using any network administrator. 1Data Mining and Optimization Research Group (DMO), Centre for Artificial Intrusion Detection System (IDS...
متن کامل