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Showing 10 of 10 academic articles

Machine learning in cybersecurity: a comprehensive survey

Dipankar Dasgupta, Zahid Akhtar, Sajib Sen • The Journal of Defense Modeling and Simulation Applications Methodology Technology (2020)

Today’s world is highly network interconnected owing to the pervasiveness of small personal devices (e.g., smartphones) as well as large computing devices or services (e.g., cloud computing or online banking), and thereby each passing minut...

OPENALEX DOI: https://doi.org/10.1177/1548512920951275

Machine learning in cybersecurity: A review

Anand Handa, Ashu Sharma, Sandeep K. Shukla • Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2019)

Machine learning technology has become mainstream in a large number of domains, and cybersecurity applications of machine learning techniques are plenty. Examples include malware analysis, especially for zero‐day malware detection, threat a...

OPENALEX DOI: https://doi.org/10.1002/widm.1306

Generative AI in cybersecurity: A comprehensive review of LLM applications and vulnerabilities

Mohamed Amine Ferrag, Fatima Alwahedi, Ammar Ayman Battah, Bilel Cherif et al. • Internet of Things and Cyber-Physical Systems (2025)

This paper provides a comprehensive review of the future of cybersecurity through Generative AI and Large Language Models (LLMs). We explore LLM applications across various domains, including hardware design security, intrusion detection, s...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.iotcps.2025.01.001

From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy

Maanak Gupta, Charankumar Akiri, Kshitiz Aryal, Eli Parker et al. • IEEE Access (2023)

Undoubtedly, the evolution of Generative AI (GenAI) models has been the highlight of digital transformation in the year 2022. As the different GenAI models like ChatGPT and Google Bard continue to foster their complexity and capability, it’...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1109/access.2023.3300381

Recurrent Neural Networks Based Online Behavioural Malware Detection Techniques for Cloud Infrastructure

Jeffrey C. Kimmel, Andrew D. Mcdole, Mahmoud Abdelsalam, Maanak Gupta et al. • IEEE Access (2021)

Several organizations are utilizing cloud technologies and resources to run a range of applications. These services help businesses save on hardware management, scalability and maintainability concerns of underlying infrastructure. Key clou...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3077498

Machine learning and its applications: A review

Sheena Angra, Sachin Ahuja • International Conference on Big Data Analytics and Computational Intelligence (ICBDAC) (2017)

Nowadays, large amount of data is available everywhere. Therefore, it is very important to analyze this data in order to extract some useful information and to develop an algorithm based on this analysis. This can be achieved through data m...

OPENALEX DOI: https://doi.org/10.1109/icbdaci.2017.8070809

Data on Vulnerability Detection in Android

Shivi Garg, Niyati Baliyan • Data in Brief (2019)

The data in this article have been collaborated from mainly four sources- Google Playstore,11 Google Playstore https://play.google.com/store/apps. Wandoujia22 Wandoujia apps http://www.wandoujia.com/apps. (third party app store market), AMD...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dib.2018.12.038