57 citations · 106 across the 10 of their papers we have counts for
11 papers
Vulnerability Detection: From Formal Verification to Large Language Models and Hybrid Approaches: A Comprehensive Overview
Norbert Tihanyi, Tamas Bisztray, Mohamed Amine Ferrag +4
Software testing and verification are critical for ensuring the reliability and security of modern software systems. Traditionally, formal verification techniques, such as model ch…
Assessing Large Language Models in Comprehending and Verifying Concurrent Programs across Memory Models
Ridhi Jain, Rahul Purandare
As concurrent programming becomes increasingly prevalent, effectively identifying and addressing concurrency issues such as data races and deadlocks is critical. This study evaluat…
Dynamic Intelligence Assessment: Benchmarking LLMs on the Road to AGI with a Focus on Model Confidence
Norbert Tihanyi, Tamas Bisztray, Richard A. Dubniczky +11
As machine intelligence evolves, the need to test and compare the problem-solving abilities of different AI models grows. However, current benchmarks are often simplistic, allowing…
Securing Tomorrow's Smart Cities: Investigating Software Security in Internet of Vehicles and Deep Learning Technologies
Ridhi Jain, Norbert Tihanyi, Mohamed Amine Ferrag
Integrating Deep Learning (DL) techniques in the Internet of Vehicles (IoV) introduces many security challenges and issues that require thorough examination. This literature review…
How secure is AI-generated Code: A Large-Scale Comparison of Large Language Models
Norbert Tihanyi, Tamas Bisztray, Mohamed Amine Ferrag +2
This study compares state-of-the-art Large Language Models (LLMs) on their tendency to generate vulnerabilities when writing C programs using a neutral zero-shot prompt. Tihanyi et…
CyberMetric: A Benchmark Dataset based on Retrieval-Augmented Generation for Evaluating LLMs in Cybersecurity Knowledge
Norbert Tihanyi, Mohamed Amine Ferrag, Ridhi Jain +2
Large Language Models (LLMs) are increasingly used across various domains, from software development to cyber threat intelligence. Understanding all the different fields of cyberse…
Why Doesn't Microsoft Let Me Sleep? How Automaticity of Windows Updates Impacts User Autonomy
Sanju Ahuja, Ridhi Jain, Jyoti Kumar
'Automating the user away' has been designated as a dark pattern in literature for performing tasks without user consent or confirmation. However, limited studies have been reporte…
Handling Communication via APIs for Microservices
Vini Kanvar, Ridhi Jain, Srikanth Tamilselvam
Enterprises in their journey to the cloud, want to decompose their monolith applications into microservices to maximize cloud benefits. Current research focuses a lot on how to par…
SecureFalcon: Are We There Yet in Automated Software Vulnerability Detection with LLMs?
Mohamed Amine Ferrag, Ammar Battah, Norbert Tihanyi +8
Software vulnerabilities can cause numerous problems, including crashes, data loss, and security breaches. These issues greatly compromise quality and can negatively impact the mar…
The FormAI Dataset: Generative AI in Software Security Through the Lens of Formal Verification
Norbert Tihanyi, Tamas Bisztray, Ridhi Jain +3
This paper presents the FormAI dataset, a large collection of 112, 000 AI-generated compilable and independent C programs with vulnerability classification. We introduce a dynamic…
A New Era in Software Security: Towards Self-Healing Software via Large Language Models and Formal Verification
Norbert Tihanyi, Ridhi Jain, Yiannis Charalambous +3
This paper introduces an innovative approach that combines Large Language Models (LLMs) with Formal Verification strategies for automatic software vulnerability repair. Initially,…