A survey of intrusion detection from the perspective of intrusion datasets and machine learning techniques

Singh, Geeta; Khare, Neelu

doi:10.1080/1206212x.2021.1885150

Cited by 54 publications

(22 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this section we reports a brief description about the dataset on which the proposed method is applied. The choice of the selected datasets derive from a preliminary study of the state of the art on IDS issues, reveling that KDD99, UNSW-NB15 and CSE-CIC-IDS are the most important benchmarks for evaluating new algorithms [21]- [29]. We also propose to apply the innovative proposed methodology to a novel dataset generated and released in 2022, representative of IIoT applications.…”

Section: A Brief Description Of the Selected Datasetsmentioning

confidence: 99%

Design and Testing Novel One-Class Classifier Based on Polynomial Interpolation With Application to Networking Security

Dini

Begni

Ciavarella³

et al. 2022

IEEE Access

View full text Add to dashboard Cite

This work exploits the concept of one-class classifier applied to the problem of anomaly detection in communication networks. The article presents the design of an innovative anomaly detection algorithm based on polynomial interpolation technique and statistical analysis. The innovative method is applied to datasets largely used in the scientific community for bench-marking such as KDD99, UNSW-NB15 and CSE-CIC-IDS-2018, and further evaluated with application to a novel available dataset EDGE-IIOTSET 2022. The paper also reports experimental results showing that the proposed methodology outperforms classic one-class classifiers, such as Extreme Learning Machine and Support Vector Machine models, and rule-based intrusion detection system like SNORT. With respect to binary classifiers, this work has the advantage of not requiring any a-priori knowledge about attacks and is based on the collection of only normal data traffic.

show abstract

Section: A Brief Description Of the Selected Datasetsmentioning

confidence: 99%

Design and Testing Novel One-Class Classifier Based on Polynomial Interpolation With Application to Networking Security

Dini

Begni

Ciavarella³

et al. 2022

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Particularly, IDS still the most effective mechanism to detect and analyze suspicious activities that occur in WSNs [2,9]. An IDS automates the detection of intrusion activities that can compromise the confidentiality, availability, and integrity of WSN through bypassing the security mechanisms [15,18]. IDS agent performs an important task for securing network from intrusive attacks.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Intrusion Detection Approach for Wireless Sensor Networks

Owaimer¹,

Tanira²,

Hatab³

et al. 2022

AJECE

View full text Add to dashboard Cite

Wireless Sensor Networks (WSNs) are vulnerable to various kinds of security attacks that can compromise many nodes and therefore the performance of the network may be degraded. Failures to prevent intrusions could also decrease the credibility of security services, e.g., data confidentiality, integrity, and availability. Traditional Intrusion Detection Systems (IDS) suffer from many issues in performance and increased overhead which are considered the main challenge in WSNs. The common architecture of WSN is that nodes are organized into a set of clusters; each one contains a set of nodes with a specialized node called Cluster Head (CH) node which is responsible for managing activities through the cluster and communicating with other nodes and a Base Station (BS). The CH plays a critical role in the case attacking WSN in the two cases; signature-based and anomaly-based. This paper proposes an efficient hybrid IDS to analyze and secure WSN in multiple phases because it combines the best features of two different approaches to achieve better performance. In the proposed approach, BS evaluates and updates attacks information for the entire network which is the main advantage where BS doesn't suffer from any limitations in sensor nodes. Moreover, BS selects CH among other nodes based on power capabilities and computational resources. The efficiency and adaptability of the proposed method have been tested by simulation experiments deployed on JiST/Swans simulation. The experimental results show that the proposed system is efficient with acceptable performance in comparison with other hybrid IDSs. The experimental evaluation also expresses that the proposed technique reduces the communication costs on the cluster head (CH) which improves the lifetime of the entire WSN.

show abstract

Section: Introductionmentioning

confidence: 99%