Application of Wavelets and Self-similarity to Enterprise Network Intrusion Detection and Prevention Systems

Akujuobi, Cajetan M.; Ampah, Nana K.; Sadiku, Matthew N. O.

doi:10.1109/isce.2007.4382163

Cited by 8 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many studies have shown that changes in Hurst parameters can be used for intrusion detection. According to Akujuobi et al [12], changing the Hurst parameter reduces high false positive and negative rates by setting the minimum change in the Hurst parameter as an intrusion indicator. Schleifer and Männle [13] proposed an approach to achieving high sensitivity by using the self-immunity properties in network traffic.…”

Section: Literature Reviewmentioning

confidence: 99%

Influence of Model and Traffic Pattern on Determining the Self-Similarity in IP Networks

Dymora

Mazurek

2020

Applied Sciences

View full text Add to dashboard Cite

This study aimed to determine the applicability of using selected libraries of computing environment R to establish the coefficient of self-similarity. R environment is an analytical environment with rich functionality that is used in many research and practical works concerning data analysis and knowledge discovery. Such an issue is significant in the context of contemporary wide area computer networks and the emerging type of network infrastructure IoT. This originates directly from the new nature of IoT traffic, which also has a substantial impact on Industry 4.0. It provides built-in operations facilitating data processing. The Hurst coefficient is used to evaluate traffic behavior and analyze its character. The study analyzed two cases of IoT network traffic: high and low intensity. For different sizes of time windows, we dermined the statistical Hurst exponent and compared it with standard, smoothed, and Robinson methods. The accuracy of the methods used was evaluated. Spectral regression graphs were additionally generated for selected motion variants. The obtained results were verified by Higuchi and Aggvar methods.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Influence of Model and Traffic Pattern on Determining the Self-Similarity in IP Networks

Dymora

Mazurek

2020

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Combination of expert system and statistical approach was very popular [22]. We identified from past research on using technique method with wavelet by [1] and [31], they present the technique a Hidden Markov Model (HMM) to model sensor, in 2009, Friaz-Martinez [9] proposed with incrementallearning algorithm, Yaron in 2006 [32], present Pattern-matching algorithm. Additionally proposal [33], they experiment data with artificial immune algorithm, and proposal Myint in 2009 [34] uses incremental learning based solutions.…”

Section: )mentioning

confidence: 99%

Characterizing Network Intrusion Prevention System

Stiawan¹,

Idris²,

Abdullah³

2011

IJCA

View full text Add to dashboard Cite

In the last few years, the Internet has experienced explosive growth. Along with the widespread evolution of new emerging services, the quantity and impact of attacks have been continuously increases, attackers continuously find vulnerabilities at various levels, from the network it self to operating system and applications, exploit the to crack system and services. Defense system and network monitoring has becomes essential component of computer security to predict and prevent attacks. Unlike traditional Intrusion Detection System (IDS), Intrusion Prevention System (IPS) has additional features to secure computer network system. In this paper, we present mapping problem and challenges of IPS. When this study was started in late 2000, there are some models and theories have been developed. Unfortunately, only a few works have done mapping the problem in IPS area, especially in hybrid mechanism. Throughout this paper, we summarize the main current methods and the promising and interesting future directions and challenges research field in IPS.

show abstract

“…This situation has resulted in huge financial losses to various enterprises over the past few years, thereby stepping up research work in the area of network security as demonstrated in Akujuobi and Ampah (2007), Akujuobi et al (2007aAkujuobi et al ( , 2007bAkujuobi et al ( , 2007c, Ampah et al (2011), Hixon and Gruenbacher (2004), Kayacik et al (2004) and Janakiraman et al (2003).…”

Section: Introductionmentioning

confidence: 99%

An intrusion detection technique based on continuous binary communication channels

Ampah

Akujuobi

Sadiku

et al. 2011

IJSN

View full text Add to dashboard Cite

Choosing Intrusion Detection Systems (IDSs) is difficult owing to the availability of different IDS techniques, the nature of attacks and the inability of IDS techniques to guarantee total security. The use of Intrusion Prevention Systems (IPSs) as a first line of defence does not prevent all attacks, so IDSs are needed as a second line of defence. Anomaly and signature-based techniques are the main approaches employed by IDSs. This new IDS technique is based on two main anomaly detection techniques: statistical and predictive pattern generation techniques. This IDS will detect both known and unknown attacks using signature-based and anomaly techniques.

show abstract

Application of Wavelets and Self-similarity to Enterprise Network Intrusion Detection and Prevention Systems

Cited by 8 publications

References 10 publications

Influence of Model and Traffic Pattern on Determining the Self-Similarity in IP Networks

Influence of Model and Traffic Pattern on Determining the Self-Similarity in IP Networks

Characterizing Network Intrusion Prevention System

An intrusion detection technique based on continuous binary communication channels

Contact Info

Product

Resources

About