Generative ai for cyber security: Analyzing the potential of chatgpt, dall-e and other models for enhancing the security space

S Sai, U Yashvardhan, V Chamola, B Sikdar - IEEE Access, 2024 - ieeexplore.ieee.org
This research paper intends to provide real-life applications of Generative AI (GAI) in the
cybersecurity domain. The frequency, sophistication and impact of cyber threats have …

[PDF][PDF] Generative AI models in time varying biomedical data: a systematic review

RY He, V Sarwal, X Qiu, Y Zhuang, L Zhang… - …, 2024 - s3.ca-central-1.amazonaws.com
Background: Trajectory modeling is a longstanding challenge in the application of
computational methods to healthcare. However, traditional statistical and machine learning …

Hacking acute care: a qualitative study on the health care impacts of ransomware attacks against hospitals

LS van Boven, RWJ Kusters, D Tin… - Annals of emergency …, 2024 - Elsevier
Study objective Cyberattacks are an increasing threat to health care institutions which
potentially impair patient outcomes. Current research is limited and focuses mainly on the …

A Comprehensive Study of Generative Adversarial Networks (GAN) and Generative Pre-Trained Transformers (GPT) in Cybersecurity

S Ayyaz, SM Malik - … on Intelligent Computing in Data Sciences …, 2024 - ieeexplore.ieee.org
The evolution of Generative Artificial Intelligence (GAI) is the main highlight of digital
transformation in year 2022. With the progression of GAI techniques; Generative Adversarial …

[PDF][PDF] Beyond Vulnerabilities: A Comprehensive Survey of Adversarial Attacks Across Domains

DC Asimopoulos, P Radoglou-Grammatikis… - researchgate.net
Adversarial attacks present significant risks to machine learning (ML) systems, exploiting
model vulnerabilities and threatening the integrity, security, and trustworthiness of …