scholarly journals Intrusion Detection Based on Big Data Fuzzy Analytics

2021 ◽  
Author(s):  
Farah Jemili ◽  
Hajer Bouras
Keyword(s):  
Big Data ◽  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
High Performance ◽  
Detection System ◽  
Training Dataset ◽  
False Alarms ◽  
Massive Datasets ◽  
Detection Rates

In today’s world, Intrusion Detection System (IDS) is one of the significant tools used to the improvement of network security, by detecting attacks or abnormal data accesses. Most of existing IDS have many disadvantages such as high false alarm rates and low detection rates. For the IDS, dealing with distributed and massive data constitutes a challenge. Besides, dealing with imprecise data is another challenge. This paper proposes an Intrusion Detection System based on big data fuzzy analytics; Fuzzy C-Means (FCM) method is used to cluster and classify the pre-processed training dataset. The CTU-13 and the UNSW-NB15 are used as distributed and massive datasets to prove the feasibility of the method. The proposed system shows high performance in terms of accuracy, precision, detection rates, and false alarms.

scholarly journals A Universal High-Performance Correlation Analysis Detection Model and Algorithm for Network Intrusion Detection System

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Hongliang Zhu ◽  
Wenhan Liu ◽  
Maohua Sun ◽  
Yang Xin
Keyword(s):  
Intrusion Detection ◽  
Correlation Analysis ◽  
Intrusion Detection System ◽  
High Performance ◽  
Detection System ◽  
Transition Diagram ◽  
Detection Rates ◽  
Detection Techniques ◽  
Detection Model ◽  
Network Intrusion

In big data era, the single detection techniques have already not met the demand of complex network attacks and advanced persistent threats, but there is no uniform standard to make different correlation analysis detection be performed efficiently and accurately. In this paper, we put forward a universal correlation analysis detection model and algorithm by introducing state transition diagram. Based on analyzing and comparing the current correlation detection modes, we formalize the correlation patterns and propose a framework according to data packet timing and behavior qualities and then design a new universal algorithm to implement the method. Finally, experiment, which sets up a lightweight intrusion detection system using KDD1999 dataset, shows that the correlation detection model and algorithm can improve the performance and guarantee high detection rates.

Association Rule-Mining-Based Intrusion Detection System With Entropy-Based Feature Selection

2020 ◽  
pp. 1-24
Author(s):  
Devaraju Sellappan ◽  
Ramakrishnan Srinivasan
Keyword(s):  
Intrusion Detection ◽  
Association Rule ◽  
Intrusion Detection System ◽  
Association Rule Mining ◽  
Detection System ◽  
False Positive Rate ◽  
Rule Mining ◽  
Detection Rates ◽  
Mining Algorithm ◽  
Positive Rate

Intrusion detection system (IDSs) are important to industries and organizations to solve the problems of networks, and various classifiers are used to classify the activity as malicious or normal. Today, the security has become a decisive part of any industrial and organizational information system. This chapter demonstrates an association rule-mining algorithm for detecting various network intrusions. The KDD dataset is used for experimentation. There are three input features classified as basic features, content features, and traffic features. There are several attacks are present in the dataset which are classified into Denial of Service (DoS), Probe, Remote to Local (R2L), and User to Root (U2R). The proposed method gives significant improvement in the detection rates compared with other methods. Association rule mining algorithm is proposed to evaluate the KDD dataset and dynamic data to improve the efficiency, reduce the false positive rate (FPR) and provides less time for processing.

Campus Network Security Program Based on Snort Network Security Intrusion Detection System

2012 ◽  
Vol 433-440 ◽  
pp. 3235-3240
Author(s):  
Ling Jia
Keyword(s):  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Collocation Methods ◽  
Campus Network ◽  
Security Risks ◽  
Network Layer ◽  
Defense Strategies

This paper studies the security problems of campus network and summarizes the current on the current security risks and threats that campus network faces, focusing on analysis of attack-defense strategies on DOS network layer, proposing the security program of campus network which uses firewall as well as network security intrusion detection system snort. This paper analyzes the functional advantages of the program and presents in details the setup deployment and collocation methods of network security intrusion detection system based on snort in the campus network, and its application results are also summarized.

ANALISIS NETWORK SECURITY SNORT METODE INTRUSION DETECTION SYSTEM UNTUK OPTIMASI KEAMANAN JARINGAN KOMPUTER

Jursima ◽  
2018 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Parningotan Panggabean
Keyword(s):  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Denial Of Service

<p><em>Perkembangan teknologi informasi, khususnya jaringan komputer memungkinkan terjadinya pertukaran informasi yang mudah, cepat dan semakin kompleks. Keamanan jaringan komputer harus diperhatikan guna menjaga validitas dan integritas data serta informasi yang berada dalam jaringan tersebut. Masalah yang dihadapi adalah adanya Log Bug yang didapatkan pada komputer server Dinas Lingkungan Hidup Kota Batam yang diindikasikan adanya serangan Denial of Service (DoS) pada komputer tersebut. Berdasarkan masalah diatas maka penulis mencoba membuat sebuah penelitian yang berjudul “Analisis Network Security Snort menggunakan metode  Intrusion Detection System (IDS) untuk Optimasi  Keamanan Jaringan Komputer” dan diharapkan dapat mendeteksi serangan Denial of Service (DoS). Intrusion Detection System (IDS)  adalah sebuah tool, metode, sumber daya yang memberikan bantuan untuk melakukan identifikasi, memberikan laporan terhadap aktivitas jaringan komputer. Aplikasi yang digunakan untuk mendeteksi serangan menggunakan Snort. Snort dapat mendeteksi serangan DoS. Serangan DoS dilakukan dengan menggunakan aplikasi Loic.</em></p>

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