Immune inspired framework for ad hoc network security

Mohamed, Yasir Abdelgadir; Abdullah, Azween

doi:10.1109/icca.2009.5410147

Cited by 8 publications

(6 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mohamed and Abdullah (2009) presented an AIS-based security framework for securing mobile ad hoc networks, which is scalable, robust, and has traits of distributability, second response and self-recovery. Their architecture resolved some limitations found in the previous related studies such as scalability and bandwidth conservation [55].…”

Section: Artificial Immune System Applicationsmentioning

confidence: 72%

Applications of Artificial Intelligence Techniques to Combating Cyber Crimes: A Review

Dilek¹,

Çakır²,

Aydin³

2015

IJAIA

129

View full text Add to dashboard Cite

With the advances in information technology (IT) criminals are using cyberspace to commit numerous cyber crimes. Cyber infrastructures are highly vulnerable to intrusions and other threats. Physical devices and human intervention are not sufficient for monitoring and protection of these infrastructures; hence, there is a need for more sophisticated cyber defense systems that need to be flexible, adaptable and robust, and able to detect a wide variety of threats and make intelligent real-time decisions. Numerous bio-inspired computing methods of Artificial Intelligence have been increasingly playing an important role in cyber crime detection and prevention. The purpose of this study is to present advances made so far in the field of applying AI techniques for combating cyber crimes, to demonstrate how these techniques can be an effective tool for detection and prevention of cyber attacks, as well as to give the scope for future work.

show abstract

Section: Artificial Immune System Applicationsmentioning

confidence: 72%

Applications of Artificial Intelligence Techniques to Combating Cyber Crimes: A Review

Dilek¹,

Çakır²,

Aydin³

2015

IJAIA

129

View full text Add to dashboard Cite

show abstract

“…IoT-Based Network Intrusion Detection Systems ((References: [54,58,62,63,64,65,66,67,68,69,99,100,101]) Disparate Membership Inference Attacks (Reference: [35]) Analysis of Open Source Datasets for IDS (Reference: [23,27]) Hybrid Deep Learning Model for IDS (Reference: [32]) Smart Home Anomaly-Based IDS ( Reference: [36]) The research articles meticulously examined in this study have been judiciously classified according to their quartile rankings, providing invaluable insights into the academic influence and eminence of these esteemed publications. The quartile categorization, elegantly portrayed in Fig.…”

Section: ) Cluster 4: Other Topicsmentioning

confidence: 99%

From Bytes to Insights: A Systematic Literature Review on Unraveling IDS Datasets for Enhanced Cybersecurity Understanding

Khanan,

Abdelgadir Mohamed,

Mohamed

et al. 2024

IEEE Access

View full text Add to dashboard Cite

In the wake of the expanding digital realm, the imperative for robust cybersecurity measures has burgeoned significantly. This extensive investigation digs into the complicated realm of cybersecurity datasets, with the goal of improving our understanding and implementation of these critical tools. This study's comprehensive evaluation of 37 distinct datasets shows a complicated world in which no one dataset stands out as totally suitable for all uses. A precise balance must be struck between crucial dataset qualities such as diversity, authenticity, and usefulness. Using a complete assessment technique, this paper illuminates the challenges and possibilities that developers and researchers face in the field of cybersecurity datasets. Although some databases accurately identify certain forms of cyberattacks, their coverage may not include the whole range of cyber threats. On the other hand, datasets with a strong emphasis on accurate portrayal may forgo comprehensiveness or practical use. This intricacy is heightened by the dynamic and sophisticated nature of cyber threats, emphasizing the delicate balance required between accuracy and practicality. The study emphasizes the necessity of selecting datasets strategically and contextually for cybersecurity studies, with the goal of matching research objectives with the most appropriate dataset selections. Furthermore, it emphasizes the need of continual cooperation and innovation within the cybersecurity community in developing datasets that accurately represent the ever-changing nature of cyber threats. After analyzing 37 cybersecurity datasets, it is obvious that no one dataset can meet all of the field's unique demands, demonstrating the need of a flexible, adaptable, and developing dataset for intrusion detection systems (IDS). This inquiry offers a critical assessment of dataset characteristics and their related issues, providing essential insights for academics, professionals, and dataset creators, enabling the construction of a more resilient and adaptable cybersecurity infrastructure.

show abstract

“…The immune inspired comprehensive security frameworks are presented by Mohamed and Abdullah in with a combined approach of negative selection, clonal selection, and danger theory. These frameworks are divided into three main sections: detection part, blocking/isolation part, and recovery section.…”

Section: Intrusion Detection Techniquesmentioning

confidence: 99%

“…These schemes suffer from high‐computational complexity due to processing the high volume and dimensional data in distributed environment. The AIS‐based IDSs focus on recognition of self and nonself patterns . However, these schemes should remove the antigens after recognition as in human immune system.…”

Section: Intrusion Detection Techniquesmentioning

confidence: 99%

Intrusion detection in mobile ad hoc networks: techniques, systems, and future challenges

Kumar

Dutta

2016

Security Comm Networks

View full text Add to dashboard Cite

In recent years, Mobile Ad hoc NETworks (MANETs) have generated great interest among researchers in the development of theoretical and practical concepts, and their implementation under several computing environments. However, MANETs are highly susceptible to various security attacks due to their inherent characteristics. In order to provide adequate security against multi-level attacks, the researchers are of the opinion that detection-based schemes should be incorporated in addition to traditionally used prevention techniques because prevention-based techniques cannot prevent the attacks from compromised internal nodes. Intrusion detection system is an effective defense mechanism that detects and prevents the security attacks at various levels. This paper tries to provide a structured and comprehensive survey of most prominent intrusion detection techniques of recent past and present for MANETs in accordance with technology layout and detection algorithms. These detection techniques are broadly classified into nine categories based on their primary detection engine/(s). Further, an attempt has been made to compare different intrusion detection techniques with their operational strengths and limitations. Finally, the paper concludes with a number of future research directions in the design and implementation of intrusion detection systems for MANETs.

show abstract

Immune inspired framework for ad hoc network security

Cited by 8 publications

References 8 publications

Applications of Artificial Intelligence Techniques to Combating Cyber Crimes: A Review

Applications of Artificial Intelligence Techniques to Combating Cyber Crimes: A Review

From Bytes to Insights: A Systematic Literature Review on Unraveling IDS Datasets for Enhanced Cybersecurity Understanding

Intrusion detection in mobile ad hoc networks: techniques, systems, and future challenges

Contact Info

Product

Resources

About