Risk Mitigation Approach to Cyber Threat using AI-Driven Models for the Evolving Threat Landscape

British Journal of Computer Networking and Information Technology, Journal Year: 2025, Volume and Issue: 8(1), P. 14 - 29

Published: Jan. 17, 2025

This systematic review examines the effectiveness of AI-driven models in mitigating evolving cyber threats, using PRISMA framework to analyze studies published between 2019 and 2024. The focuses on machine learning techniques, including supervised, unsupervised, deep learning. Findings show that excels detecting complex threats like Advance Persistent Threats (APTs) zero-day vulnerabilities, while supervised (deep is also a type learning, so be specific) effective for known but struggles with new attack types. Unsupervised adapts well dynamic environments has higher false positive rates. proposes multi-layered combining AI traditional security measures enhanced threat detection response. A hybrid approach recommended as most strategy, though challenges data quality algorithmic bias must addressed optimal implementation.

Language: Английский

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Research on digital system for identifying on-site operations of power infrastructure based on time-stamped measurements (TSM)

Journal of Computational Methods in Sciences and Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 27, 2025

The effective tracking and management of on-site operations in power infrastructure (PI) is critical for assuring operational reliability avoiding service interruptions. Traditional monitoring systems are frequently constrained by human error, slow response times, the inability to give real-time data on system conditions. This research uses a digital identify PI, utilizing Time-Stamped Measurements (TSM) provide problem identification. suggested architecture made up both software hardware parts that work together collect, process, evaluate concurrently fault detection condition estimate PI. Various types sensors installed throughout grid collect operating characteristics such as current, temperature, voltage, performance metrics. collection TSM an important step proposed since it provides precise, time-based required reliable identification analysis. communicate IoT devices or gateways employ communication protocols Wi-Fi deliver main server cloud server. Before analysis, raw pre-processed, normalization feature extraction using Fast Fourier Transform (FFT). Intelligent Genetic Energy Valley Optimizer (IntGen-EVO) used detect defects real time time-stamped data. framework demonstrates superior accuracy (98.7%), precision (98.3%), recall (98%), F1-score (98.4%) compared traditional methods, significantly enhancing PI system. findings demonstrate method accurate concurrent insights into infrastructure’s state, allowing preventive maintenance rapid problems. Therefore, described this solution increasing effectiveness management.

Language: Английский

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АНАЛИЗ РИСКОВ И НАПРАВЛЕНИЙ ИХ УСТРАНЕНИЯ ДЛЯ НАЦИОНАЛЬНОЙ КРИТИЧЕСКОЙ ИНФОРМАЦИОННОЙ ИНФРАСТРУКТУРЫ В УСЛОВИЯХ РОСТА УГРОЗ БЕЗОПАСНОСТИ

Вестник НИЯУ МИФИ, Journal Year: 2025, Volume and Issue: 14(1), P. 78 - 83

Published: Feb. 25, 2025

Language: Русский

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Future Trends in AI Security

Advances in information security, privacy, and ethics book series, Journal Year: 2025, Volume and Issue: unknown, P. 229 - 262

Published: Feb. 14, 2025

Cybersecurity is enriched due to Artificial Intelligence (AI), which provides better real-time threat detection and anomaly identification, response systems. As attackers grow more sophisticated leverage AI in creating malware. The present study gives an overview of the future threats associated with AI-driven attacks challenges faced by existing cybersecurity countermeasures. Additionally, it also analyses feasibility using capabilities like predictive intelligence, advanced quantum computing for some these emerging threats. For such as, we need user permissions rights on this application, should take into consideration privacy policies while designing security as well. To end, get ready against risks a proactive adaptive approach needed stressing collaboration between industry, academia well global entities.

Language: Английский

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Cybersecurity Risks and Defense for a European Energy Retail Business: A Case Study Using FMEA and Bowtie Incident Analysis

Information Security Journal A Global Perspective, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 29

Published: April 30, 2025

Language: Английский

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Strategic management of solar generation for solar electric vehicle charging in microgrids using deep reinforcement learning

Journal of Renewable and Sustainable Energy, Journal Year: 2025, Volume and Issue: 17(3)

Published: May 1, 2025

The integration of solar electric vehicles (SEVs) into microgrids, particularly those enriched with photovoltaic (PV) systems, presents unique challenges due to the inherent variability in energy and dynamic consumption patterns SEVs. This study aims address these complexities by developing an advanced operational framework that enhances management flows within leveraging capabilities modern artificial intelligence. Utilizing a deep double Q-network (DDQN), this research introduces sophisticated method dynamically adapt fluctuations generation SEV demands, ensuring efficiency, sustainability, grid stability. methodology encompasses detailed mathematical modeling generation, consumption, storage dynamics, integrated environmental economic constraints simulate realistic microgrid scenarios. DDQN is employed optimize distribution strategies real-time, based on predictive analytics responsive control mechanisms. approach not only copes stochastic nature renewable sources usage but also capitalizes aspects improve overall performance. paper contributes novel management, for systems incorporating SEVs PV generation. By optimizing interplay between power availability charging requirements, provides strategic insights can guide infrastructure investments tactics, promoting more efficient economically viable systems. proposed models are expected significantly advance field paving way development smarter, resilient urban environments.

Language: Английский

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Emerging Innovations in AI and Green Computing for Cybersecurity

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 17 - 38

Published: Feb. 28, 2025

Future trends in AI and green computing for security are crucial areas of research development the realm information technology. The integration artificial intelligence (AI) machine learning (ML) cloud is a significant trend that enhancing data operational efficiency. envisioned to play pivotal role empowering intelligent, adaptive, autonomous management 5G beyond networks, enabling faster more accurate decisions. Additionally, at forefront triggering digital innovations address emerging threats post-COVID-19 world. Moreover, proactive use predicting preventing cyberattacks before they occur promising approach measures. As continues advance, it expected have transformative influence on military power, strategic competition, international security. as force multipliers defensive offensive cyber weapons anticipated revolutionize cybersecurity.

Language: Английский

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Optimizing Energy Infrastructure with AI Technology: A Literature Review

Open Journal of Applied Sciences, Journal Year: 2024, Volume and Issue: 14(12), P. 3516 - 3544

Published: Jan. 1, 2024

Language: Английский

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Leveraging Artificial Intelligence (AI) for the Maintenance of Science Laboratory Equipment

Deleted Journal, Journal Year: 2024, Volume and Issue: 16(1), P. 131 - 148

Published: Oct. 28, 2024

The dire need for proper maintenance of Science Laboratory Equipment (SLE) to attain efficiency, optimal results and durability cannot be overemphasized. To that end, this study proposes the leveraging AI optimization efficiency in SLE. relied on both primary secondary data. data were sourced from twenty (SL) professionals, while repositories, databases websites internet. mixed method alongside plausible descriptive statistical tools was employed. analysis shows SLE can optimized made efficient by such purposes. Regrettably, public sector organizations are yet significantly integrate into concludes has capacity optimize enhance It calls stakeholders field SL make concerted efforts government should help provide technologies concerned sponsor training people technical know-how using sustaining these cutting-edge SL.

Language: Английский

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Impact of AI on Architecture: An Exploratory Thematic Analysis

Deleted Journal, Journal Year: 2024, Volume and Issue: 16(1), P. 117 - 130

Published: Oct. 28, 2024

The huge impact of artificial intelligence (AI) on various spheres is commonly attested in the literature. This study informed by dire need for more research increased adoption AI and awareness it architectural activities. It aimed at exploring architecture, with a view to drawing evidence from extant studies determine extent its positive architecture. Literature review process, interpretive devices, content thematic analyses are employed show scholarly arguments concern. Being an exploratory research, method qualitative approach employed. relies observation secondary data, focusing their preoccupations relation arguments. data sourced online only reputable repositories databases. analysis demonstrates that has been impacting positively broad field capacity optimize transform architecture industry innovations, results, efficiency, performance, productivity. concludes other cutting-edge technologies, as technological transforming charges government stakeholders ensure significant increase about AI, impact, ethical concerns. Ethical governance pragmatic measures can help address concerns associated AI.

Language: Английский

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