activity
20192026
most citedMalware Classification Using Deep Boosted Learning

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CR2026

Multimodal Multi-Agent Ransomware Analysis Using AutoGen

Asifullah Khan, Aimen Wadood, Mubashar Iqbal +1

Ransomware has become one of the most serious cybersecurity threats causing major financial losses and operational disruptions worldwide.Traditional detection methods such as stati…

eess.IV2023

A Recent Survey of Vision Transformers for Medical Image Segmentation

Asifullah Khan, Zunaira Rauf, Abdul Rehman Khan +13

Medical image segmentation plays a crucial role in various healthcare applications, enabling accurate diagnosis, treatment planning, and disease monitoring. Traditionally, convolut…

cs.CR20212 cited

Malware Classification Using Deep Boosted Learning

Muhammad Asam, Saddam Hussain Khan, Tauseef Jamal +2

Malicious activities in cyberspace have gone further than simply hacking machines and spreading viruses. It has become a challenge for a nations survival and hence has evolved to c…

cs.CR2019

Ransomware Analysis using Feature Engineering and Deep Neural Networks

Arslan Ashraf, Abdul Aziz, Umme Zahoora +2

Detection and analysis of a potential malware specifically, used for ransom is a challenging task. Recently, intruders are utilizing advanced cryptographic techniques to get hold o…

cs.CV2019

A Survey of the Recent Architectures of Deep Convolutional Neural Networks

Asifullah Khan, Anabia Sohail, Umme Zahoora +1

Deep Convolutional Neural Network (CNN) is a special type of Neural Networks, which has shown exemplary performance on several competitions related to Computer Vision and Image Pro…