Metaheuristic Techniques in Attack and Defense Strategies for Cybersecurity: A Systematic Review

Salas-Fernández, Agustín; Crawford, Broderick; Soto, Ricardo; Misra, Sanjay

doi:10.1007/978-3-030-72236-4_18

Cited by 5 publications

(2 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, in the context of information security systems, [24] puts forth multi-criteria cost optimization method, employing the vector-evaluated genetic algorithm. Researchers in [25], driven by the escalating interaction in cyberspace, have devised optimization techniques for both attack and defense. These optimization approaches leverage artificial intelligence techniques powered by metaheuristics to identify and detect threats and attacks.…”

Section: Related Workmentioning

confidence: 99%

An Integral Cybersecurity Approach Using a Many-Objective Optimization Strategy

Salinas,

Soto,

Crawford

et al. 2023

IEEE Access

Self Cite

View full text Add to dashboard Cite

Data networks and computing devices have experienced exponential growth. Within a short span of time, they have opened new digital frontiers while also bringing forth new threats. These threats have the potential to increase costs and disrupt regular operations. Choosing a cybersecurity plan to address these threats requires balancing direct and indirect costs against the benefits of implementation and subsequent operation. In this study, we propose an efficient strategy for designing networking topologies by incorporating a Security Information and Event Management System. This system consists of a central server and Network Intrusion Detection Sensors, which gather data and promptly transmit information regarding suspicious activities to the server. The server then takes immediate action in case of incidents. To determine the optimal number and placement of sensors, a many-objective optimization approach is employed. The problem is mathematically modeled using linear programming. To solve the optimization problem, swarm intelligence techniques such as the particle swarm optimizer, the bat algorithm, and the black hole method are utilized. Various test scenarios were created by presenting low, medium, and complex instances of conventional networks. The results obtained using the black hole bio-inspired algorithm were particularly satisfying, surpassing the performance and resolution of the other methods.

show abstract

Section: Related Workmentioning

confidence: 99%

An Integral Cybersecurity Approach Using a Many-Objective Optimization Strategy

Salinas,

Soto,

Crawford

et al. 2023

IEEE Access

Self Cite

View full text Add to dashboard Cite

show abstract

“…A significant portion of the optimization in threat identification is due to the reduction of features during the training stage. Metaheuristics are important in decreasing these characteristics [15,16]. The use of intelligent algorithms in the development of cyber security models to detect various sorts of assaults is researched to improve performance.…”

mentioning

confidence: 99%

An enhanced mechanism for detection of Domain Name System‐based distributed reflection denial of service attacks depending on modified metaheuristic algorithms and adaptive thresholding techniques

et al. 2022

View full text Add to dashboard Cite

The rapid growth of the number of devices connected to the Internet and the increasing demand for electronic services have led to a huge growth in the number of cyberattacks targeting cyberspace and the development of their methodology. Therefore, there must be mechanisms, laws, and rules regulating the work of these applications and protecting them from electronic attacks. The Domain Name System (DNS) has several vulnerabilities that can be exploited by cyber attackers to launch their attacks, and the most important one of these vulnerabilities is that the response size is always greater than the size of the request. According to reports published by numerous security companies, distributed reflection denial of service (DRDoS) attacks against DNS are regarded as one of the most hazardous and rapidly spreading threats in recent years. An enhanced mechanism that is able to detect DNS-based DRDoS attacks that exploit the DNS responses to launch their attacks is proposed. The proposed mechanism was designed based on modified metaheuristic optimization algorithms and an adaptive threshold. This mechanism consists of two models and four stages. The first model is called 'Proactive Feature Selection,' and the second model is called 'Evolving Dynamic Fuzzy Clustering.' The four stages of the proposed mechanism are: the preprocessing stage, feature selection stage, detection stage, and enhancement stage. The new mechanism has been implemented on the CICDDoS2019 standard dataset and achieves a detection accuracy of 95.44% with a false-positive rate of 0.22%. The results show that the new mechanism is better than others depending on the detection accuracy and false positives. | INTRODUCTIONWith the increase in the number of Internet-connected assets, the effect of distributed denial of service (DDoS) attacks increases proportionately. Due to the nature of this extremely disruptive attack, the level to which its service quality is disrupted and degraded is uncertain [1]. As a result of the widespread use of these services, cyberattacks on the infrastructure of the systems that utilise them become an attractive target [2,3].DDoS Attack is the most frequently used type of cyberattack to disrupt these services [4]. Recent years have seen an explosion in the growth of information security infrastructure and services, such as payment gateways, search engines, banks, and social media websites. This has resulted in an exponential increase in network traffic, increasing Internet misuse. In addition to, security and privacy concerns instil fear in end users, preventing them from using online services [5]. Although proposals and implementations for information security management haveThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract