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Relevant bibliographies by topics / AI in Cybersecurity

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Academic literature on the topic 'AI in Cybersecurity'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "AI in Cybersecurity"

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Çakır, Ahmet Mert. "AI Driven Cybersecurity." Human Computer Interaction 8, no. 1 (2024): 119. https://doi.org/10.62802/jg7gge06.

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The advent of Artificial Intelligence (AI) has revolutionized the field of cybersecurity by introducing advanced mechanisms for detecting, preventing, and mitigating cyber threats. This research explores the intersection of AI and cybersecurity, highlighting the transformative potential of AI-driven solutions in combating increasingly sophisticated cyberattacks. By leveraging machine learning, deep learning, and neural network algorithms, AI enhances real-time threat detection, predictive analytics, and anomaly detection across diverse digital infrastructures. This study evaluates current AI-d

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Kim, Geunhye, and Kyudong Park. "Effect of AI." Tehnički glasnik 18, no. 1 (2024): 29–36. http://dx.doi.org/10.31803/tg-20230218142012.

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Abstract: Artificial intelligence (AI) is considered a vital factor that will fundamentally alter the cybersecurity environment. AI technology is progressing much faster than expected, and AI-based security services are being introduced into the global security market on a daily basis. However, how AI can contribute to the cybersecurity field and what changes it will bring remain unknown. Nonetheless, cybersecurity is not merely a technical issue but also a process for dealing with regulations, policies, and security risks; therefore, the introduction of AI technology introduction can make a f

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Puthal, Deepak, and Saraju Mohanty. "Cybersecurity Issues in AI." IEEE Consumer Electronics Magazine 10, no. 4 (2021): 33–35. http://dx.doi.org/10.1109/mce.2021.3066828.

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Samara Simha Reddy Beesam and Suchitha Reddy Aeniga. "Bridging AI and Cybersecurity." International Journal of Science and Research Archive 14, no. 2 (2025): 1179–85. https://doi.org/10.30574/ijsra.2025.14.2.0382.

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This has led to an entirely new era of quicker-than-extremely-quick firm AI will probably come, which in turn looms every great improvement in cybersecurity practice. Built into a security system: AI not only means that massive filing cabinets can be replaced by microfiche readers which are good enough for government work--it also adds incredible capabilities to the stored data itself. This means that although the quantities of data may soar a million billion-fold in any single category at a given point nowadays all those same numbers still do not cause a corresponding increase in different ty

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Rios-Campos, Carlos, Sonia Carmina Venegas Paz, Gonzalo Orozco Vilema, et al. "Cybersecurity and artificial intelligence (AI)." South Florida Journal of Development 5, no. 8 (2024): e4276. http://dx.doi.org/10.46932/sfjdv5n8-021.

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The general objective of the research was to determine the advances related to the cybersecurity and artificial intelligence (AI). The specific objectives of the research are to identify the countries that invest the most in cybersecurity and the most prominent organizations in cybersecurity worldwide. Methodology, in this research, 37 documents have been selected, carried out in the period 2018 – 2024; including: scientific articles, review articles and information from websites of recognized organizations. Results, AI and cybersecurity are two very important aspects today, so it is necessary

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Shahid, Shahabuddin. "Vulnerabilities of AI in Cybersecurity." International Journal of Scientific Engineering and Research 13, no. 6 (2025): 31–32. https://doi.org/10.70729/se25604130052.

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Abel Uzoka, Emmanuel Cadet, and Pascal Ugochukwu Ojukwu. "Applying artificial intelligence in Cybersecurity to enhance threat detection, response, and risk management." Computer Science & IT Research Journal 5, no. 10 (2024): 2511–38. http://dx.doi.org/10.51594/csitrj.v5i10.1677.

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This paper explores the application of Artificial Intelligence (AI) in cybersecurity, emphasizing its potential to enhance threat detection, response, and risk management. The study's primary objective is to analyze how AI-driven tools and techniques can improve the efficiency and effectiveness of cybersecurity measures in organizations. Employing a comprehensive literature review and case study analysis, the research investigates current AI applications in threat detection, including machine learning algorithms, anomaly detection systems, and predictive analytics. The findings reveal that AI

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Rathod, Sachin Dashrath. "AI In Enhancing Cyber Security." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem04063.

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Abstract:- Artificial intelligence( AI) is a important technology that helps cybersecurity armies automate repetitive tasks, accelerate trouble discovery and response, and meliorate the delicacy of their conduct to strengthen the security posture against various security issues and cyberattacks. This composition presents a regular literature review and a detailed analysis of AI use cases for cybersecurity provisioning. The review reacted in 2395 studies, of which 236 were linked as primary. This composition classifies the linked AI use cases predicated on a NIST cybersecurity frame using a the

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Quiana Bradshaw. "Cybersecurity in Artificial Intelligence." World Journal of Advanced Research and Reviews 27, no. 1 (2025): 1735–44. https://doi.org/10.30574/wjarr.2025.27.1.2703.

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We are currently living in an emerging technological society in today’s society. AI has grown to a level where it is being used in a variety of fields, including banking, customer service, education, and law enforcement. What are some of the risks with cybersecurity issues and artificial intelligence? What kind of impact does artificial intelligence have on cybersecurity? Are there some drawbacks and limitations when using AI for cybersecurity? When using Artificial intelligence, it has provided many profound ways to implement measures of cybersecurity. There are some ways that AI improves the

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Student, Speaker: Isaik Agudelo Watstein, and Advisor: Leon Guillermo Marin Ortega Faculty. "CYBERSECURITY WITH A SOCIAL VISION PROTECTING RIGHTS IN THE DIGITAL AGE." International Journal of Engineering Technology Research & Management (IJETRM) 09, no. 05 (2025): 302–9. https://doi.org/10.5281/zenodo.15468798.

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Nowadays, cybersecurity goes beyond computers and focuses on safeguarding people’s dignity and individualrights. Since we rely more on digital tools and AI, cybersecurity's social, ethical, and legal sides need to beconsidered with priority. This article addresses how cybersecurity ties in with the dignity of people and cites lawssuch as Law 1273 from 2009 and Law 1581 from 2012 in the context of Colombia. In addition, it analyzes theworldwide effects of the Budapest Treaty and compares them to international efforts like the CCPA in the UnitedStates. The study highlights that AI can assi

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Dissertations / Theses on the topic "AI in Cybersecurity"

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SORO, FRANCESCA. "An AI and data-driven approach to unwanted network traffic inspection." Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2950486.

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Stegner, Wayne. "Context-Aware Malware Detection Using Topic Modeling." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin162766765703398.

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Ziani, Zineb. "AI and HPC Convergence for Enhanced Anomaly Detection." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPASG006.

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La détection des anomalies, une branche de l'IA, vise à identifier des instances ou des motifs dans les données qui s'écartent de la norme. Cette capacité est essentielle dans divers secteurs, notamment la finance, où elle aide à identifier la fraude ; la santé, où elle détecte les conditions anormales ; et la maintenance prédictive, où elle anticipe les pannes d'équipement. En cybersécurité, la détection des anomalies permet d'identifier les comportements suspects et aide à prévenir les intrusions en analysant les motifs inhabituels dans le trafic réseau. Les techniques existantes, telles que

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Abu-Shaqra, Baha. "Technoethics and Sensemaking: Risk Assessment and Knowledge Management of Ethical Hacking in a Sociotechnical Society." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40393.

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Cyber attacks by domestic and foreign threat actors are increasing in frequency and sophistication. Cyber adversaries exploit a cybersecurity skill/knowledge gap and an open society, undermining the information security/privacy of citizens and businesses and eroding trust in governments, thus threatening social and political stability. The use of open digital hacking technologies in ethical hacking in higher education and within broader society raises ethical, technical, social, and political challenges for liberal democracies. Programs teaching ethical hacking in higher education are steadily

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Books on the topic "AI in Cybersecurity"

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Sikos, Leslie F., ed. AI in Cybersecurity. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-98842-9.

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Pan, Zhixin, and Prabhat Mishra. Explainable AI for Cybersecurity. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-46479-9.

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Sharma, Dilli Prasad, Arash Habibi Lashkari, Mahdi Daghmehchi Firoozjaei, Samaneh Mahdavifar, and Pulei Xiong. Understanding AI in Cybersecurity and Secure AI. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-91524-6.

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Sarker, Iqbal H. AI-Driven Cybersecurity and Threat Intelligence. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-54497-2.

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Yafooz, Wael M. S., and Yousef Al-Gumaei, eds. AI-Driven: Social Media Analytics and Cybersecurity. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-80334-5.

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Stamp, Mark, and Martin Jureček, eds. Machine Learning, Deep Learning and AI for Cybersecurity. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-83157-7.

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Nedjah, Nadia, Ahmed A. Abd El-Latif, Brij B. Gupta, and Luiza M. Mourelle, eds. Robotics and AI for Cybersecurity and Critical Infrastructure in Smart Cities. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96737-6.

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Jahankhani, Hamid, ed. Cybersecurity Challenges in the Age of AI, Space Communications and Cyborgs. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-47594-8.

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Shandilya, Shishir Kumar, Fernando Ortiz-Rodriguez, Smita Shandilya, and Gerardo Romero. AI, Cybersecurity and Data Science for Drone and Unmanned Aerial Vehicles. Chapman and Hall/CRC, 2025. https://doi.org/10.1201/9781003481584.

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Naik, Nitin, Paul Jenkins, Shaligram Prajapat, and Paul Grace, eds. Contributions Presented at The International Conference on Computing, Communication, Cybersecurity and AI, July 3–4, 2024, London, UK. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-74443-3.

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Book chapters on the topic "AI in Cybersecurity"

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Jøsang, Audun. "AI and Cybersecurity." In Cybersecurity. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-68483-8_15.

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Sharma, Rohan. "AI Cybersecurity." In AI and the Boardroom. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0796-1_18.

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Mohanty, Soumendra, and Sachin Vyas. "Cybersecurity and AI." In How to Compete in the Age of Artificial Intelligence. Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3808-0_6.

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Badhwar, Raj. "AI for Cybersecurity." In The CISO’s Next Frontier. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75354-2_4.

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Das, Ravindra. "Review of Cybersecurity Metrics." In Generative AI. CRC Press, 2024. http://dx.doi.org/10.1201/9781003503781-4.

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Merat, Soorena. "AI Mimicry and Impressioning." In Cybersecurity 2050. CRC Press, 2025. https://doi.org/10.1201/9781003641506-4.

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Wendt, Donnie W. "AI for Defense." In The Cybersecurity Trinity. Apress, 2024. https://doi.org/10.1007/979-8-8688-0947-7_3.

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Wendt, Donnie W. "AI Is Everywhere." In The Cybersecurity Trinity. Apress, 2024. https://doi.org/10.1007/979-8-8688-0947-7_1.

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Sikos, Leslie F. "OWL Ontologies in Cybersecurity: Conceptual Modeling of Cyber-Knowledge." In AI in Cybersecurity. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98842-9_1.

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Sikos, Leslie F., Dean Philp, Catherine Howard, Shaun Voigt, Markus Stumptner, and Wolfgang Mayer. "Knowledge Representation of Network Semantics for Reasoning-Powered Cyber-Situational Awareness." In AI in Cybersecurity. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98842-9_2.

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Conference papers on the topic "AI in Cybersecurity"

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Ilieva, Roumiana, and Gloria Stoilova. "Challenges of AI-Driven Cybersecurity." In 2024 XXXIII International Scientific Conference Electronics (ET). IEEE, 2024. http://dx.doi.org/10.1109/et63133.2024.10721572.

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Zhang, Cynthia, Ranjan Pal, Corwin Nicholson, and Michael Siegel. "(Gen)AI Versus (Gen)AI in Industrial Control Cybersecurity." In 2024 Winter Simulation Conference (WSC). IEEE, 2024. https://doi.org/10.1109/wsc63780.2024.10838831.

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AlOmar, Ban, and Zouheir Trabelsi. "Integrating Generative AI in Cybersecurity Curricula." In 2025 IEEE Global Engineering Education Conference (EDUCON). IEEE, 2025. https://doi.org/10.1109/educon62633.2025.11016426.

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Baiardi, Fabrizio, Salvatore Ruggieri, and Vincenzo Sammartino. "AI-enabled Cybersecurity using Synthetic Data." In 2025 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 2025. https://doi.org/10.1109/percomworkshops65533.2025.00055.

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Al Balawi, Mohammad, Mohammad Alnabhan, and Mohammed S. Atoum. "Generative AI for Advanced Malware Detection." In 2024 4th Intelligent Cybersecurity Conference (ICSC). IEEE, 2024. https://doi.org/10.1109/icsc63108.2024.10895965.

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Barton, Richard, P. W. C. Prasad, Indra Seher, and Amr Elchouemi. "Artificial Intelligence (AI) in Cybersecurity and Inhibitors to AI Adoption." In 2024 International Conference on Intelligent Education and Intelligent Research (IEIR). IEEE, 2024. https://doi.org/10.1109/ieir62538.2024.10959777.

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Tingare, Bhagyashree Ashok, G. Prasanna Lakshmi, Vijayshri Khedkar, Rakesh Thoppaen Suresh Babu, Tarun Dhar Diwan, and Pravin B. Khatkale. "Responsible AI on National Cybersecurity Strategy with Enhancement of Cybersecurity in Education." In 2024 International Conference on Intelligent & Innovative Practices in Engineering & Management (IIPEM). IEEE, 2024. https://doi.org/10.1109/iipem62726.2024.10925807.

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Rasheed, Ahmad, and Mohammad Alnabhan. "Detection of Botnet Attacks on IoT Using AI." In 2024 International Jordanian Cybersecurity Conference (IJCC). IEEE, 2024. https://doi.org/10.1109/ijcc64742.2024.10847293.

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Patel, Advait, Pravin Pandey, Hariharan Ragothaman, Ramasankar Molleti, and Ajay Tanikonda. "Securing Cloud AI Workloads: Protecting Generative AI Models from Adversarial Attacks." In 2025 IEEE 4th International Conference on AI in Cybersecurity (ICAIC). IEEE, 2025. https://doi.org/10.1109/icaic63015.2025.10848877.

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Jabbar, Haidar, Samir Al-Janabi, and Francis Syms. "AI-Integrated Cyber Security Risk Management Framework for IT Projects." In 2024 International Jordanian Cybersecurity Conference (IJCC). IEEE, 2024. https://doi.org/10.1109/ijcc64742.2024.10847294.

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Reports on the topic "AI in Cybersecurity"

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Sharkov, George, and Christina Todorova. AI against COVID-19, AI and Cybersecurity, and Misusing AI. Procon, 2021. http://dx.doi.org/10.11610/cybsec05.

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Martinez, Cindy, and Micah Musser. U.S. Demand for Talent at the Intersection of AI and Cybersecurity. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/2020ca009.

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As demand for cybersecurity experts in the United States has grown faster than the supply of qualified workers, some organizations have turned to artificial intelligence to bolster their overwhelmed cyber teams. Organizations may opt for distinct teams that specialize exclusively in AI or cybersecurity, but there is a benefit to having employees with overlapping experience in both domains. This data brief analyzes hiring demand for individuals with a combination of AI and cybersecurity skills.

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Pasupuleti, Murali Krishna. Securing AI-driven Infrastructure: Advanced Cybersecurity Frameworks for Cloud and Edge Computing Environments. National Education Services, 2025. https://doi.org/10.62311/nesx/rrv225.

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Abstract: The rapid adoption of artificial intelligence (AI) in cloud and edge computing environments has transformed industries by enabling large-scale automation, real-time analytics, and intelligent decision-making. However, the increasing reliance on AI-powered infrastructures introduces significant cybersecurity challenges, including adversarial attacks, data privacy risks, and vulnerabilities in AI model supply chains. This research explores advanced cybersecurity frameworks tailored to protect AI-driven cloud and edge computing environments. It investigates AI-specific security threats,

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Buchanan, Ben. A National Security Research Agenda for Cybersecurity and Artificial Intelligence. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/2020ca001.

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Machine learning advances are transforming cyber strategy and operations. This necessitates studying national security issues at the intersection of AI and cybersecurity, including offensive and defensive cyber operations, the cybersecurity of AI systems, and the effect of new technologies on global stability.

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Lohn, Andrew. Hacking AI: A Primer for Policymakers on Machine Learning Cybersecurity. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/2020ca006.

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Machine learning systems’ vulnerabilities are pervasive. Hackers and adversaries can easily exploit them. As such, managing the risks is too large a task for the technology community to handle alone. In this primer, Andrew Lohn writes that policymakers must understand the threats well enough to assess the dangers that the United States, its military and intelligence services, and its civilians face when they use machine learning.

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Cary, Dakota. China’s CyberAI Talent Pipeline. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/2020ca017.

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To what extent does China’s cultivation of talent in cybersecurity and AI matter in terms of competitiveness with other countries? Right now, it seems to have an edge: China’s 11 World-Class Cybersecurity Schools offer more classes on artificial intelligence and machine learning than do the 20 U.S. universities certified as Centers of Academic Excellence in Cyber Operations. This policy brief recommends tracking 13 research grants from the National Science Foundation that attempt to integrate AI into cybersecurity curricula.

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Pasupuleti, Murali Krishna. Quantum Intelligence: Machine Learning Algorithms for Secure Quantum Networks. National Education Services, 2025. https://doi.org/10.62311/nesx/rr925.

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Abstract: As quantum computing and quantum communication technologies advance, securing quantum networks against emerging cyber threats has become a critical challenge. Traditional cryptographic methods are vulnerable to quantum attacks, necessitating the development of AI-driven security solutions. This research explores the integration of machine learning (ML) algorithms with quantum cryptographic frameworks to enhance Quantum Key Distribution (QKD), post-quantum cryptography (PQC), and real-time threat detection. AI-powered quantum security mechanisms, including neural network-based quantum

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Lohn, Andrew, Anna Knack, Ant Burke, and Krystal Jackson. Autonomous Cyber Defense. Center for Security and Emerging Technology, 2023. http://dx.doi.org/10.51593/2022ca007.

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The current AI-for-cybersecurity paradigm focuses on detection using automated tools, but it has largely neglected holistic autonomous cyber defense systems — ones that can act without human tasking. That is poised to change as tools are proliferating for training reinforcement learning-based AI agents to provide broader autonomous cybersecurity capabilities. The resulting agents are still rudimentary and publications are few, but the current barriers are surmountable and effective agents would be a substantial boon to society.

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Pasupuleti, Murali Krishna. AI and Quantum-Nano Frontiers: Innovations in Health, Sustainability, Energy, and Security. National Education Services, 2025. https://doi.org/10.62311/nesx/rr525.

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Abstract: This research report explores transformative advancements at the intersection of Artificial Intelligence (AI), Quantum Computing, and Nanotechnology, focusing on breakthrough innovations in health, sustainability, energy, and global security. By integrating quantum algorithms, AI-driven analytics, and advanced nanomaterials, this report highlights revolutionary solutions in precision medicine, predictive diagnostics, sustainable energy storage, universal water purification, and cybersecurity. Real-world case studies and emerging technologies such as graphene-based nanomaterials, quan

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Pasupuleti, Murali Krishna. Smart Nanomaterials and AI-Integrated Grids for Sustainable Renewable Energy. National Education Services, 2025. https://doi.org/10.62311/nesx/rr1025.

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Abstract: The transition to sustainable and intelligent renewable energy systems is being driven by advancements in smart nanomaterials and AI-integrated smart grids. Nanotechnology has enabled the development of high-performance energy materials, such as graphene, perovskites, quantum dots, and MXenes, which enhance the efficiency, durability, and scalability of renewable energy solutions. Simultaneously, AI-driven smart grids leverage machine learning, deep learning, and digital twins to optimize energy distribution, predictive maintenance, and real-time load balancing in renewable energy ne

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