Data Collection for Intrusion Detection System Based on Stratified Random Sampling

2007 ◽  
Author(s):  
Kuo Zhao ◽  
Meng Zhang ◽  
Kexin Yang ◽  
Liang Hu
Keyword(s):  
Data Collection ◽  
Intrusion Detection ◽  
Random Sampling ◽  
Intrusion Detection System ◽  
Detection System ◽  
Stratified Random Sampling

scholarly journals A determinant fuzzy apparoach for intrusion detection system

2018 ◽  
Vol 7 (1.9) ◽  
pp. 245
Author(s):  
S. Vimala ◽  
V. Khanna ◽  
C. Nalini
Keyword(s):  
Data Collection ◽  
Intrusion Detection ◽  
False Alarm ◽  
False Alarm Rate ◽  
Great Degree ◽  
Intrusion Detection System ◽  
Detection System ◽  
Information Mining ◽  
The Past ◽  
Recognition Systems

In MANETs, versatile hubs can impart transparently to each other without the need of predefined framework. Interruption location framework is a fundamental bit of security for MANETs. It is uncommonly convincing for identifying the Intrusions and for the most part used to supplement for other security segment. That is the reason Intrusion discovery framework (IDS) is known as the second mass of assurance for any survivable framework security. The proposed fluffy based IDSs for recognition of Intrusions in MANETs are not prepared to adjust up all sort of assaults. We have examined that all proposed fluffy based IDSs are seen as to a great degree obliged segments or qualities for data collection which is specific for a particular assault. So that these IDSs are simply recognize the particular assault in MANETs. The fluffy motor may perceive blockage from channel mistake conditions, and along these lines helps the TCP blunder discovery. Examination has been made on the issues for upgrading the steady quality and precision of the decisions in MANET. This approach offers a strategy for joining remote units' estimation comes to fruition with alliance information open or priori decided at conglomerating hubs. In our investigation work, the best need was to reduce the measure of information required for getting ready and the false alarm rate. We are chiefly endeavoring to improve the execution of a present framework rather than endeavoring to supplant current Intrusion recognition systems with an information mining approach. While current mark based Intrusion identification procedures have imperatives as communicated in the past region, they do even now give basic organizations and this normal us to choose how information mining could be used as a piece of a correlative way to deal with existing measures and improves it.

Guidance for Selecting Data Collection Mechanisms for Intrusion Detection

2015 ◽  
pp. 340-370
Author(s):  
Ulf Larson ◽  
Erland Jonsson ◽  
Stefan Lindskog
Keyword(s):  
Data Collection ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Log Data ◽  
Detailed Explanation ◽  
Generic Data ◽  
Efficient Data ◽  
Efficient Data Collection

This chapter aims at providing a clear and concise picture of data collection for intrusion detection. It provides a detailed explanation of generic data collection mechanism components and the interaction with the environment, from initial triggering to output of log data records. Taxonomies of mechanism characteristics and deployment considerations are provided and discussed. Furthermore, guidelines and hints for mechanism selection and deployment are provided. Finally, this chapter presents a set of strategies for determining what data to collect, and it also discusses some of the challenges in the field. An appendix providing a classification of 50 studied mechanisms is also provided. This chapter aims at assisting intrusion detection system developers, designers, and operators in selecting mechanisms for resource-efficient data collection.

scholarly journals A Consolidated Decision Tree-Based Intrusion Detection System for Binary and Multiclass Imbalanced Datasets

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 751
Author(s):  
Ranjit Panigrahi ◽  
Samarjeet Borah ◽  
Akash Kumar Bhoi ◽  
Muhammad Fazal Ijaz ◽  
Moumita Pramanik ◽  
...  
Keyword(s):  
Intrusion Detection ◽  
Random Sampling ◽  
Intrusion Detection System ◽  
Detection System ◽  
Imbalanced Data ◽  
Mobile Technologies ◽  
Detection Methods ◽  
Main Concern ◽  
Detection Systems ◽  
Tree Construction

The widespread acceptance and increase of the Internet and mobile technologies have revolutionized our existence. On the other hand, the world is witnessing and suffering due to technologically aided crime methods. These threats, including but not limited to hacking and intrusions and are the main concern for security experts. Nevertheless, the challenges facing effective intrusion detection methods continue closely associated with the researcher’s interests. This paper’s main contribution is to present a host-based intrusion detection system using a C4.5-based detector on top of the popular Consolidated Tree Construction (CTC) algorithm, which works efficiently in the presence of class-imbalanced data. An improved version of the random sampling mechanism called Supervised Relative Random Sampling (SRRS) has been proposed to generate a balanced sample from a high-class imbalanced dataset at the detector’s pre-processing stage. Moreover, an improved multi-class feature selection mechanism has been designed and developed as a filter component to generate the IDS datasets’ ideal outstanding features for efficient intrusion detection. The proposed IDS has been validated with state-of-the-art intrusion detection systems. The results show an accuracy of 99.96% and 99.95%, considering the NSL-KDD dataset and the CICIDS2017 dataset using 34 features.

A Structured Approach to Selecting Data Collection Mechanisms for Intrusion Detection

2011 ◽  
pp. 1-39
Author(s):  
Ulf E. Larson ◽  
Erland Jonsson ◽  
Stefan Lindskog
Keyword(s):  
Data Collection ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Log Data ◽  
Detailed Explanation ◽  
Generic Data ◽  
Efficient Data ◽  
Structured Approach ◽  
Efficient Data Collection

This chapter aims at providing a clear and concise picture of data collection for intrusion detection. It provides a detailed explanation of generic data collection mechanism components and the interaction with the environment, from initial triggering to output of log data records. Taxonomies of mechanism characteristics and deployment considerations are provided and discussed. Furthermore, guidelines and hints for mechanism selection and deployment are provided. The guidelines are aimed to assist intrusion detection system developers, designers, and operators in selecting mechanisms for resource efficient data collection.

scholarly journals A Security Concept Based on Scaler Distribution of a Novel Intrusion Detection Device for Wireless Sensor Networks in a Smart Environment

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4717 ◽  
Author(s):  
Kenneth Rodolphe Chabi Boni ◽  
Lizhong Xu ◽  
Zhe Chen ◽  
Thelma Dede Baddoo
Keyword(s):  
Data Collection ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Electronic Device ◽  
Detection System ◽  
Wireless Sensor ◽  
Smart Environments ◽  
Feedback Signal ◽  
Smart Environment ◽  
Sensor Security

Following the significant improvement of technology in terms of data collection and treatment during the last decades, the notion of a smart environment has widely taken an important pedestal in the science industry. Built in order to better manage assets, smart environments provide a livable environment for users or citizens through the deployment of sensors responsible for data collection. Much research has been done to provide security to the involved data, which are extremely sensitive. However, due to the small size and the memory constraint of the sensors, many of these works are difficult to implement. In this paper, a different concept for wireless sensor security in smart environments is presented. The proposed security system, which is based on the scaler distribution of a novel electronic device, the intrusion detection system (IDS), reduces the computational functions of the sensors and therefore maximizes their efficiency. The IDS also introduces the concept of the feedback signal and “trust table” used to trigger the detection and isolation mechanism in case of attacks. Generally, it ensures the whole network security through cooperation with other IDSs and, therefore, eliminates the problem of security holes that may occur while adopting such a security technique.

Sign in / Sign up

Export Citation Format

Share Document