Advancing cybersecurity: a comprehensive review of AI-driven detection techniques

Journal Of Big Data, Journal Year: 2024, Volume and Issue: 11(1)

Published: Aug. 4, 2024

Abstract As the number and cleverness of cyber-attacks keep increasing rapidly, it's more important than ever to have good ways detect prevent them. Recognizing cyber threats quickly accurately is crucial because they can cause severe damage individuals businesses. This paper takes a close look at how we use artificial intelligence (AI), including machine learning (ML) deep (DL), alongside metaheuristic algorithms better. We've thoroughly examined over sixty recent studies measure effective these AI tools are identifying fighting wide range threats. Our research includes diverse array cyberattacks such as malware attacks, network intrusions, spam, others, showing that ML DL methods, together with algorithms, significantly improve well find respond We compare methods out what they're where could improve, especially face new changing cyber-attacks. presents straightforward framework for assessing Methods in threat detection. Given complexity threats, enhancing regularly ensuring strong protection critical. evaluate effectiveness limitations current proposed models, addition algorithms. vital guiding future enhancements. We're pushing smart flexible solutions adapt challenges. The findings from our suggest protecting against will rely on continuously updating stay ahead hackers' latest tricks.

Language: Английский

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An Improved Pelican Optimization - Kernel Extreme Learning Machine for Highly Accurate State of Charge Estimation of Lithium-Ion Batteries in Energy Storage Systems

Published: Jan. 1, 2025

Language: Английский

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Velocity Paused Particle Swarm Optimization-based Intelligent Long Short-Term Memory Framework for Intrusion Detection System in Internet of Medical Things

Arabian Journal for Science and Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 26, 2025

Language: Английский

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Enhancing IoT Security Using GA-HDLAD: A Hybrid Deep Learning Approach for Anomaly Detection

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(21), P. 9848 - 9848

Published: Oct. 28, 2024

The adoption and use of the Internet Things (IoT) have increased rapidly over recent years, cyber threats in IoT devices also become more common. Thus, development a system that can effectively identify malicious attacks reduce security has topic great importance. One most serious comes from botnets, which commonly attack by interrupting networks required for to run. There are number methods be used improve identifying unknown patterns networks, including deep learning machine approaches. In this study, an algorithm named genetic with hybrid learning-based anomaly detection (GA-HDLAD) is developed, aim improving botnets within environment. GA-HDLAD technique addresses problem high dimensionality using during feature selection. Hybrid detect botnets; approach combination recurrent neural (RNNs), extraction techniques (FETs), attention concepts. Botnet involve complex (HDL) method detect. Moreover, FETs model ensures features extracted spatial data, while temporal dependencies captured RNNs. Simulated annealing (SA) utilized select hyperparameters necessary HDL approach. experimentally assessed benchmark botnet dataset, findings reveal provides superior results comparison existing methods.

Language: Английский

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AI: The Future of Social Engineering!

European Conference on Cyber Warfare and Security, Journal Year: 2024, Volume and Issue: 23(1)

Published: June 21, 2024

Abstract: Artificial intelligence (AI) is at the forefront of computer science today. Everyone talking about AI and how it way future. Companies are using machine learning (ML)algorithms to enhance their business offerings, which showing promise in realm improved efficiency. The potential benefit a fully developed exceptional, but so threats that poses. While developers various forms eager be first create functional, truly intelligent AI, they do not always consider negative possibilities creates. ChatGPT was recently used hack itself exposed vulnerability its open-source library. In addition hacks exploits, also being support social engineering efforts by creating more convincing attacks. Whether attack duplicate person's voice convince loved one send gift card get them out jail or if simply scrape person’s media develop precise method attack, concern will for nefarious purposes genuinely profound. This paper case study looking into improve engineering. A literature review conducted identify researchers already seeing project future threats. here stay, brings existential, imperative these realized, defensive measures developed. looks efficacy

Language: Английский

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