scholarly journals Efficient Working of Signature Based Intrusion Detection Technique in Computer Networks

2019 ◽  
pp. 60-64 ◽  
Author(s):  
Abid Hussain ◽  
Praveen Kumar Sharma
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Computer Network ◽  
Detection System ◽  
Network Intrusion ◽  
Computer Network Security ◽  
Dramatic Rise ◽  
Security Infrastructure ◽  
The Subject ◽  
Concept Of Information

The subject of Computer Network Intrusion Detection System (IDS) is a very interesting research topic actively pursued by many investigators. The goal of intrusion detection is to monitor network assets and to detect anomalous behaviour and misuse. This concept has been around for the past several years but only recently, it has seen a dramatic rise in interest of researchers and system developers for incorporation into the overall information security infrastructure. In today's world, the concept of information has been moved to the digital size from conventional size. Protection of the data stored in the digital archive and is easily accessibility at any time have become a quite important phenomenon. In this concept, intrusion detection and prevention systems as security tools are widely used today [1]. In this paper, a signature based intrusion detection system approach has been proposed for computer network security. This paper is based on the efficient working of the Signature based intrusion detection method and protects the computer network against the intrusion or the unspecified packets.

scholarly journals Machine Learning Techniques for Network Intrusion Detection System (NIDS): A Survey

2021 ◽  
Vol 9 (12) ◽  
pp. 1477-1483
Keyword(s):  
Machine Learning ◽  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Computer Network ◽  
Detection System ◽  
Vital Role ◽  
Cyber Attacks ◽  
Machine Learning Techniques ◽  
Network Intrusion

In computer network, security of the network is a major issue and intrusion is the most common threats to security. Cyber attacks detection is becoming more enlightened challenge in detecting these threats accurately. In network security, intrusion detection system (IDS) has played a vital role to detect intrusion. In recent years, numerous methods have been proposed for intrusion detection to detect these security threats. This survey paper study examines recent work in the topic of network security, machine learning based techniques as well as a discussion of the many datasets that are commonly used to evaluate IDS. It also explains how researchers employ Machine Learning Based Techniques to detect intrusions

scholarly journals Genetic algorithm for intrusion detection system in computer network

2020 ◽  
Vol 19 (3) ◽  
pp. 1670
Author(s):  
Hamizan Suhaimi ◽  
Saiful Izwan Suliman ◽  
Afdallyna Fathiyah Harun ◽  
Roslina Mohamad ◽  
Yuslinda Wati Mohamad Yusof ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Computer Network ◽  
Local Area Network ◽  
Detection System ◽  
Local Area ◽  
Small Scale ◽  
Area Network ◽  
Network Intrusion

<span>Internet connection nowadays has become one of the essential requirements to execute our daily activities effectively. Among the major applications of wide Internet connections is local area network (LAN) which connects all internet-enabled devices in a small-scale area such as office building, computer lab etc. This connection will allow legit user to access the resources of the network anywhere as long as authorization is acquired. However, this might be seen as opportunities for some people to illegally access the network. Hence, the occurrence of network hacking and privacy breach. Therefore, it is very vital for a computer network administrator to install a very protective and effective method to detect any network intrusion and, secondly to protect the network from illegal access that can compromise the security of the resources in the network. These resources include sensitive and confidential information that could jeopardise someone’s life or sovereignty of a country if manipulated by wrong hands.  In Network Intrusion Detection System (NIDS) framework, apart from detecting unauthorized access, it is equally important to recognize the type of intrusions in order for the necessary precautions and preventive measures to take place. This paper presents the application of Genetic Algorithm (GA) and its steps in performing intrusion detection process. Standard benchmark dataset known as KDD’99 cup was utilized with forty-one distinctive features representing the identity of network connections. Results presented demonstrate the effectiveness of the proposed method and warrant good research focus as it promises exciting discovery in solving similar-patent of problems.   </span>

scholarly journals Network intrusion detection system using immune-genetic algorithm (IGA)

2020 ◽  
Vol 17 (2) ◽  
pp. 1059
Author(s):  
Hamizan Suhaimi ◽  
Saiful Izwan Suliman ◽  
Ismail Musirin ◽  
Afdallyna Harun ◽  
Roslina Mohamad ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Computer Network ◽  
Detection System ◽  
Personal Information ◽  
Genetic Operators ◽  
Network Systems ◽  
Immune Genetic Algorithm ◽  
Network Intrusion

Network security is an important aspect in maintaining computer network systems and personal information from being illegally accessed by third parties. The major problem that frequently occurs in computer network systems is the failure in detecting possible network-attacks. Apart from that, the process of recognizing the type of attack that occurs is very crucial as it will determine the elimination process that should take place to counter the intrusion. This paper proposes the application of standard Genetic Algorithm (GA) that combines with immune algorithm process to enhance the computer system’s capability in recognizing possible intrusion occurrence in a computer system. Simulation was conducted numerous times to test the effectiveness of the proposed intrusion detection system by manipulating the parameter values for genetic operators utilized in GA. The effectiveness of the proposed method is shown in the gathered results and the analysis conducted further supports and proves that Immune Genetic Algorithm (IGA) has the capability to predict the occurrence of intrusion in computer network.

scholarly journals Network intrusion detection system by using genetic algorithm

2019 ◽  
Vol 16 (3) ◽  
pp. 1593
Author(s):  
Hamizan Suhaimi ◽  
Saiful Izwan Suliman ◽  
Ismail Musirin ◽  
Afdallyna Fathiyah Harun ◽  
Roslina Mohamad
Keyword(s):  
Genetic Algorithm ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Computer Network ◽  
Detection System ◽  
Classification Rule ◽  
Network Intrusion Detection ◽  
Detection Systems ◽  
The Past ◽  
Network Intrusion

Developing a better intrusion detection systems (IDS) has attracted many researchers in the area of computer network for the past decades. In this paper, Genetic Algorithm (GA) is proposed as a tool that capable to identify harmful type of connections in a computer network. Different features of connection data such as duration and types of connection in network were analyzed to generate a set of classification rule. For this project, standard benchmark dataset known as KDD Cup 99 was investigated and utilized to study the effectiveness of the proposed method on this problem domain. The rules comprise of eight variables that were simulated during the training process to detect any malicious connection that can lead to a network intrusion. With good performance in detecting bad connections, this method can be applied in intrusion detection system to identify attack thus improving the security features of a computer network.

scholarly journals Anomaly based Intrusion Detection System using Machine Learning

2021 ◽  
Vol 9 (9) ◽  
pp. 255-260
Author(s):  
Akshat Runwal
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Intrusion Detection ◽  
Anomaly Detection ◽  
Intrusion Detection System ◽  
Computer Network ◽  
Detection System ◽  
High Detection Rate ◽  
Network Intrusion ◽  
Average Accuracy

Abstract: Attacks on the computer infrastructures are becoming an increasingly serious issue. The problem is ubiquitous and we need a reliable system to prevent it. An anomaly detection-based network intrusion detection system is vital to any security framework within a computer network. The existing Intrusion detection system have a high detection rate but they also have mendacious alert rates. With the use of Machine Learning, we can implement an efficient and reliable model for Intrusion detection and stop some of the hazardous attacks in the network. This paper focuses on detailed study on NSL- KDD dataset after extracting some of the relevant records and then several experiments have been performed and evaluated to assess various machine learning classifiers based on dataset. The implemented experiments demonstrated that the Random forest classifier has achieved the highest average accuracy and has outperformed the other models in various evaluations. Keywords: Intrusion Detection System, Anomaly Detection, Machine Learning, Random Forest, Network Security

Design and Research on Intrusion Detection System in the Computer Network Security

2013 ◽  
Vol 416-417 ◽  
pp. 1418-1422
Author(s):  
Yu Tao Sun
Keyword(s):  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Computer Network ◽  
Detection System ◽  
Security Threat ◽  
Network Intrusion ◽  
Detection Technology ◽  
The Status ◽  
Process System

This paper first discusses the information security and network security, security threat, hacker intrusion process, system and network security vulnerabilities, and then introduces the status of intrusion detection system. By the comparison of two kinds of intrusion detection systems, the article puts forward the detection system based on the combination of the soil and the intrusion of network intrusion detection technology. Combined with the actual project development, this article focuses on the key technology design idea and the realization of the intrusion detection system in network security.

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