scholarly journals Optimization of Rules for Intrusion Detection System (Org-Ids)

2019 ◽  
Vol 8 (3) ◽  
pp. 1356-1361
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Optimization Technique ◽  
Good Time ◽  
Rule Generation ◽  
Individual System ◽  
High Level ◽  
Memory Complexity ◽  
Entire Network

Computer Networks are prone to be attacked by a number of network attacks. To protect an individual system or the entire network from the malicious behaviour, a high level security system is needed. Intrusion detection system (IDS) is a system which give such protection to the network from the intrusions like misuse, unauthorised access etc. Even though many forms of new attacks come into practice, providing the security for the system from the known attack is also a challenging task. The solution is a Signature based IDS which is a potential tool to identify the known attack, sending alert and protect the networks. So a novel signature based IDS(ORG-IDS) with four phases such as Feature Selection, Classification, Optimized Rule generation and Pattern matching is proposed. For any efficient signature based IDS, it should have the signature rules in less number but it should be effective in identifying attacks with good time and memory complexity. In this paper, a new algorithm is proposed for Rule generation phase of proposed IDS to configure the rules by implementing Ant Colony Optimization Technique with Association Rule Mining . The parameters like number of rules, running time and memory utilization are measured and proved that this proposed algorithm outperforms the other existing algorithms.

scholarly journals Effective Intrusion Detection System to Secure Data in Cloud Using Machine Learning

Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2306
Author(s):  
Ammar Aldallal ◽  
Faisal Alisa
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Fitness Function ◽  
Support Vector ◽  
Network Intrusion ◽  
Proposed Model ◽  
High Level

When adopting cloud computing, cybersecurity needs to be applied to detect and protect against malicious intruders to improve the organization’s capability against cyberattacks. Having network intrusion detection with zero false alarm is a challenge. This is due to the asymmetry between informative features and irrelevant and redundant features of the dataset. In this work, a novel machine learning based hybrid intrusion detection system is proposed. It combined support vector machine (SVM) and genetic algorithm (GA) methodologies with an innovative fitness function developed to evaluate system accuracy. This system was examined using the CICIDS2017 dataset, which contains normal and most up-to-date common attacks. Both algorithms, GA and SVM, were executed in parallel to achieve two optimal objectives simultaneously: obtaining the best subset of features with maximum accuracy. In this scenario, an SVM was employed using different values of hyperparameters of the kernel function, gamma, and degree. The results were benchmarked with KDD CUP 99 and NSL-KDD. The results showed that the proposed model remarkably outperformed these benchmarks by up to 5.74%. This system will be effective in cloud computing, as it is expected to provide a high level of symmetry between information security and detection of attacks and malicious intrusion.

scholarly journals Securing the Network by the Intruder using Predictive Accession

2020 ◽  
Vol 8 (6) ◽  
pp. 1822-1825
Keyword(s):  
Genetic Algorithm ◽  
Intrusion Detection ◽  
Private Information ◽  
Intrusion Detection System ◽  
Genetic Parameters ◽  
Detection System ◽  
Modified Genetic Algorithm ◽  
Main Target ◽  
High Level ◽  
Intrusion Detection And Prevention

Today, it is very crucial to deliver a immense level security to protect highly delicate and private information. Intrusion Detection System is an essential technology in Network Security. So my aim is to use IDS system and meliorate the performance of the IDS. The main target of Intrusion detection and prevention systems (IDPS) is to determine the feasible incidents, logging clue about them and in report attempts. Intruder is the person who tries to interrupt the network. So, it is essential to present a high level security to defend extremely susceptible and confidential information. Key aim of this thesis is to secure the network from the intruders identifying them also predicting them for the next transactions within the network. For that modified genetic algorithm is used to rank the parents and produce better individuals for the prediction of the intruders and provide better security to the network. Also improve the performance of genetic parameters.

scholarly journals A Novel Optimization Algorithm Based on Stinging Behavior of Bee

2018 ◽  
Vol 7 (4) ◽  
pp. 153
Author(s):  
S. Jayalakshmi ◽  
R. Aswini
Keyword(s):  
Intrusion Detection ◽  
Honey Bee ◽  
Optimization Algorithm ◽  
Intrusion Detection System ◽  
Detection System ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Biological Behavior ◽  
New Host ◽  
Stinging Behavior

<span lang="EN-US">Optimization algorithms are search methods to find an optimal solution to a problem with a set of constraints. Bio-Inspired Algorithms (BIAs) are based on biological behavior to solve a real world problem. BIA with optimization technique is to improve the overall performance of BIA. The aim of this paper is to introduce a novel optimization algorithm which is inspired by natural stinging behavior of honey bee to find the optimal solution. This algorithm performs both monitor and sting if any occurrence of predators. By applying a novel optimization algorithm based on stinging behavior of bee, used to solve the intrusion detection problems. In this paper, a new host intrusion detection system based on novel optimization algorithm has been proposed and implemented. The performance of the proposed Anomaly-based Host Intrusion Detection System (A-HIDS) using a novel optimization algorithm based on stinging behavior of bee has been tested. In this paper, after an explanation of the natural stinging behavior of honey bee, a novel optimization algorithm and A-HIDS are described and implemented. The results show that the novel optimization algorithm offers some advantage according to the nature of the problem.</span>

scholarly journals Issues and Challenges for Preventing Cyber - Attacks

2020 ◽  
pp. 212-215
Author(s):  
Arvind Kishanrao Rathod ◽  
Bhushan Shivaji Kulkarni
Keyword(s):  
Intrusion Detection ◽  
Cyber Security ◽  
Intrusion Detection System ◽  
Preventive Measures ◽  
Detection System ◽  
Social Engineering ◽  
Cyber Attacks ◽  
Security Policies ◽  
Data Corruption ◽  
Individual System

The main objective of cyber security is to prevent various types of attacks on individual user system or organizations system or network by implementing some preventive measures such as by enforcing security policies, providing security awareness among the peoples by organizing frequent trainings or workshop to avoid social engineering attacks. Also implementing some tools such as intrusion detection system, firewall, antiviruses in individual system on organizations network and avoid from data corruption or alteration attacks by attackers via internet or some other means.

Distributed Intrusion Detection Systems

2007 ◽  
pp. 231-238
Author(s):  
Rosalind Deena Kumari ◽  
G. Radhamani
Keyword(s):  
Intrusion Detection ◽  
System Architecture ◽  
Intrusion Detection System ◽  
Detection System ◽  
Research Work ◽  
Intrusion Detection Systems ◽  
Future Research ◽  
Detection Systems ◽  
Distributed Intrusion Detection ◽  
Entire Network

The recent tremendous increase in the malicious usage of the network has made it necessary that an IDS should encapsulate the entire network rather than at a system. This was the inspiration for the birth of a distributed intrusion detection system (DIDS). Different configurations of DIDSs have been actively used and are also rapidly evolving due to the changes in the types of threats. This chapter will give the readers an overview of DIDS and the system architecture. It also highlights on the various agents that are involved in DIDS and the benefits of the system. Finally, directions for future research work are discussed.

scholarly journals NETWORK INTRUSION DETECTION AND PREVENTION ATTACKS

2012 ◽  
Vol 2 (3) ◽  
pp. 21-23
Author(s):  
Harpreet Kaur
Keyword(s):  
Intrusion Detection ◽  
Distributed System ◽  
Intrusion Detection System ◽  
Detection System ◽  
Network Intrusion Detection ◽  
Business Sector ◽  
Network Systems ◽  
Network Intrusion ◽  
Entire Network ◽  
Intrusion Detection And Prevention

Intrusion detection is an important technology in business sector as well as an active area of research. It is an important tool for information security. A Network Intrusion Detection System is used to monitor networks for attacks or intrusions and report these intrusions to the administrator in order to take evasive action. Today computers are part of networked; distributed systems that may span multiple buildings sometimes located thousands of miles apart. The network of such a system is a pathway for communication between the computers in the distributed system. The network is also a pathway for intrusion. This system is designed to detect and combat some common attacks on network systems. It follows the signature based IDs methodology for ascertaining attacks. A signature based IDS will monitor packets on the network and compare them against a database of signatures or attributes from known malicious threats. In this system the attack log displays the list of attacks to the administrator for evasive action. This system works as an alert device in the event of attacks directed towards an entire network.

scholarly journals Malware Detection and Prevention System Based on Multi-Stage Rules

2013 ◽  
Vol 7 (2) ◽  
pp. 29-43 ◽  
Author(s):  
Ammar Alazab ◽  
Michael Hobbs ◽  
Jemal Abawajy ◽  
Ansam Khraisat
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Malware Detection ◽  
Rule Generation ◽  
Malicious Attack ◽  
Multi Stage ◽  
Prevention System ◽  
Rule Sets ◽  
Anomaly Intrusion Detection

The continuously rising Internet attacks pose severe challenges to develop an effective Intrusion Detection System (IDS) to detect known and unknown malicious attack. In order to address the problem of detecting known, unknown attacks and identify an attack grouped, the authors provide a new multi stage rules for detecting anomalies in multi-stage rules. The authors used the RIPPER for rule generation, which is capable to create rule sets more quickly and can determine the attack types with smaller numbers of rules. These rules would be efficient to apply for Signature Intrusion Detection System (SIDS) and Anomaly Intrusion Detection System (AIDS).

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