scholarly journals A Review of the Advances in Cyber Security Benchmark Datasets for Evaluating Data-Driven Based Intrusion Detection Systems

2015 ◽  
Vol 62 ◽  
pp. 221-227 ◽  
Author(s):  
Adamu I. Abubakar ◽  
Haruna Chiroma ◽  
Sanah Abdullahi Muaz ◽  
Libabatu Baballe Ila
Keyword(s):  
Intrusion Detection ◽  
Cyber Security ◽  
Intrusion Detection Systems ◽  
Data Driven ◽  
Detection Systems ◽  
Benchmark Datasets

A Compressive Compilation of Cyber Security for Internet of Energy (IoE)

2022 ◽  
pp. 883-910
Author(s):  
Gustavo Arroyo-Figueroa ◽  
Isai Rojas-Gonzalez ◽  
José Alberto Hernández-Aguilar
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Cyber Security ◽  
Research Work ◽  
Intrusion Detection Systems ◽  
Electrical Network ◽  
Future Research ◽  
Electrical Grid ◽  
Detection Systems ◽  
Security Challenges

Internet of energy (IoE) is the natural evolution of Smart Grid incorporating the paradigm of internet of things (IoT). This complicated environment has a lot of threats and vulnerabilities, so the security challenges are very complex and specialized. This chapter contains a compilation of the main threats, vulnerabilities, and attacks that can occur in the IoE environment and the critical structure of the electrical grid. The objective is to show the best cybersecurity practices that can support maintaining a safe, reliable, and available electrical network complying with the requirements of availability, integrity, and confidentially of the information. The study includes review of countermeasures, standards, and specialized intrusion detection systems, as mechanisms to solve security problems in IoE. Better understanding of security challenges and solutions in the IoE can be the light on future research work for IoE security.

A Compressive Compilation of Cyber Security for Internet of Energy (IoE)

2020 ◽  
pp. 267-294
Author(s):  
Gustavo Arroyo-Figueroa ◽  
Isai Rojas-Gonzalez ◽  
José Alberto Hernández-Aguilar
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Cyber Security ◽  
Research Work ◽  
Intrusion Detection Systems ◽  
Electrical Network ◽  
Future Research ◽  
Electrical Grid ◽  
Detection Systems ◽  
Security Challenges

Internet of energy (IoE) is the natural evolution of Smart Grid incorporating the paradigm of internet of things (IoT). This complicated environment has a lot of threats and vulnerabilities, so the security challenges are very complex and specialized. This chapter contains a compilation of the main threats, vulnerabilities, and attacks that can occur in the IoE environment and the critical structure of the electrical grid. The objective is to show the best cybersecurity practices that can support maintaining a safe, reliable, and available electrical network complying with the requirements of availability, integrity, and confidentially of the information. The study includes review of countermeasures, standards, and specialized intrusion detection systems, as mechanisms to solve security problems in IoE. Better understanding of security challenges and solutions in the IoE can be the light on future research work for IoE security.

Designing Light Weight Intrusion Detection Systems

2012 ◽  
pp. 304-317
Author(s):  
Václav Snášel ◽  
Jan Platoš ◽  
Pavel Krömer ◽  
Ajith Abraham
Keyword(s):  
Intrusion Detection ◽  
Computational Intelligence ◽  
Matrix Factorization ◽  
Cyber Security ◽  
Detection System ◽  
Factorization Method ◽  
Performance Comparison ◽  
Intrusion Detection Systems ◽  
Light Weight ◽  
Detection Systems

Recently cyber security has emerged as an established discipline for computer systems and infrastructures with a focus on protection of valuable information stored on those systems from adversaries who want to obtain, corrupt, damage, destroy or prohibit access to it. An Intrusion Detection System (IDS) is a program that analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. This chapter presents some of the challenges in designing efficient ad light weight intrusion detection systems, which could provide high accuracy, low false alarm rate and reduced number of features. Finally, the authors present the Non-negative matrix factorization method for detecting real attacks and the performance comparison with other computational intelligence techniques.

Designing Light Weight Intrusion Detection Systems

2009 ◽  
pp. 216-229 ◽  
Author(s):  
Václav Snášel ◽  
Jan Platoš ◽  
Pavel Krömer ◽  
Ajith Abraham
Keyword(s):  
Intrusion Detection ◽  
Computational Intelligence ◽  
Matrix Factorization ◽  
Cyber Security ◽  
Detection System ◽  
Factorization Method ◽  
Performance Comparison ◽  
Intrusion Detection Systems ◽  
Light Weight ◽  
Detection Systems

Recently cyber security has emerged as an established discipline for computer systems and infrastructures with a focus on protection of valuable information stored on those systems from adversaries who want to obtain, corrupt, damage, destroy or prohibit access to it. An Intrusion Detection System (IDS) is a program that analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. This chapter presents some of the challenges in designing efficient ad light weight intrusion detection systems, which could provide high accuracy, low false alarm rate and reduced number of features. Finally, the authors present the Non-negative matrix factorization method for detecting real attacks and the performance comparison with other computational intelligence techniques.

Cyber Security And The Evolution Of Intrusion Detection Systems

2005 ◽  
Vol 1 (1) ◽  
pp. 74-82 ◽  
Author(s):  
Ajith Abraham ◽  
◽  
Crina Grosan ◽  
Yuehui Chen ◽  
◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Cyber Security ◽  
Intrusion Detection Systems ◽  
Detection Systems

scholarly journals TON_IoT Telemetry Dataset: A New Generation Dataset of IoT and IIoT for Data-Driven Intrusion Detection Systems

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 165130-165150 ◽  
Author(s):  
Abdullah Alsaedi ◽  
Nour Moustafa ◽  
Zahir Tari ◽  
Abdun Mahmood ◽  
Adnan Anwar
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection Systems ◽  
Data Driven ◽  
Detection Systems ◽  
New Generation

scholarly journals Machine Learning Approach for Intrusion Detection Systems as a Cyber Security Strategy for Small and Medium Enterprises

2022 ◽  
Vol 19 ◽  
pp. 474-480
Author(s):  
Nevila Baci ◽  
Kreshnik Vukatana ◽  
Marius Baci
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Cyber Security ◽  
Small And Medium Enterprises ◽  
Classification Model ◽  
Supervised Machine Learning ◽  
Intrusion Detection Systems ◽  
Detection Systems ◽  
Original Dataset ◽  
Medium Enterprises

Small and medium enterprises (SMEs) are businesses that account for a large percentage of the economy in many countries, but they lack cyber security. The present study examines different supervised machine learning methods with a focus on intrusion detection systems (IDSs) that will help in improving SMEs’ security. The algorithms that are tested through a real dataset, are Naïve Bayes, Sequential minimal optimization (SMO), C4.5 decision tree, and Random Forest. The experiments are run using the Waikato Environment for Knowledge Analyses (WEKA) 3.8.4 tools and the metrics used to evaluate the results were: accuracy, false-positive rate (FPR), and total time to train and build a classification model. The results obtained from the original dataset with 130 features show a high value of accuracy, but the computation time to build the classification model was notably high for the cases of C4.5 (1 hr. and 20 mins) and SMO algorithm (4 hrs. and 20 mins). the Information Gain (IG) method was used and the result was impressive. The time needed to train the model was reduced in the order of a few minutes and the accuracy was high (above 95%). In the end, challenges that SMEs can have for choosing an IDS such as lack of scalability and autonomic self-adaptation, can be solved by using a correct methodology with machine learning techniques.

scholarly journals A Survey on Multi-Agent Based Collaborative Intrusion Detection Systems

2021 ◽  
Vol 11 (2) ◽  
pp. 111-142
Author(s):  
Nassima Bougueroua ◽  
Smaine Mazouzi ◽  
Mohamed Belaoued ◽  
Noureddine Seddari ◽  
Abdelouahid Derhab ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Cyber Security ◽  
Intrusion Detection Systems ◽  
Multi Agent Systems ◽  
Research Issues ◽  
Detection Systems ◽  
Multi Agent ◽  
Collaborative Intrusion Detection ◽  
Complex Phenomena ◽  
General Architecture

Abstract Multi-Agent Systems (MAS) have been widely used in many areas like modeling and simulation of complex phenomena, and distributed problem solving. Likewise, MAS have been used in cyber-security, to build more efficient Intrusion Detection Systems (IDS), namely Collaborative Intrusion Detection Systems (CIDS). This work presents a taxonomy for classifying the methods used to design intrusion detection systems, and how such methods were used alongside with MAS in order to build IDS that are deployed in distributed environments, resulting in the emergence of CIDS. The proposed taxonomy, consists of three parts: 1) general architecture of CIDS, 2) the used agent technology, and 3) decision techniques, in which used technologies are presented. The proposed taxonomy reviews and classifies the most relevant works in this topic and highlights open research issues in view of recent and emerging threats. Thus, this work provides a good insight regarding past, current, and future solutions for CIDS, and helps both researchers and professionals design more effective solutions.

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