activity
20162024
most citedRansomware Detection and Classification Strategies

32 citations · 43 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE20245 cited

LLM-Powered Code Vulnerability Repair with Reinforcement Learning and Semantic Reward

Nafis Tanveer Islam, Joseph Khoury, Andrew Seong +4

In software development, the predominant emphasis on functionality often supersedes security concerns, a trend gaining momentum with AI-driven automation tools like GitHub Copilot.…

cs.CR2023

Ransomware Detection Using Federated Learning with Imbalanced Datasets

Aldin Vehabovic, Hadi Zanddizari, Nasir Ghani +5

Ransomware is a type of malware which encrypts user data and extorts payments in return for the decryption keys. This cyberthreat is one of the most serious challenges facing organ…

cs.CR20236 cited

IoT Threat Detection Testbed Using Generative Adversarial Networks

Farooq Shaikh, Elias Bou-Harb, Aldin Vehabovic +3

The Internet of Things(IoT) paradigm provides persistent sensing and data collection capabilities and is becoming increasingly prevalent across many market sectors. However, most I…

cs.CR202332 cited

Ransomware Detection and Classification Strategies

Aldin Vehabovic, Nasir Ghani, Elias Bou-Harb +2

Ransomware uses encryption methods to make data inaccessible to legitimate users. To date a wide range of ransomware families have been developed and deployed, causing immense dama…

cs.CY2016

Towards the Leveraging of Data Deduplication to Break the Disk Acquisition Speed Limit

Hannah Wolahan, Claudio Chico Lorenzo, Elias Bou-Harb +1

Digital forensic evidence acquisition speed is traditionally limited by two main factors: the read speed of the storage device being investigated, i.e., the read speed of the disk,…