A literature survey shows that the number of malware attacks is gradually growing over the years due to the growing trend of Internet of Medical Things (IoMT) devices. To detect and classify malware ...

Delve into the implications of AI in architecture: a tool that redefines creativity while risking the depth and intent behind design.

The research, and topic of the presentation, focused on malware detection and the challenges faced by existing techniques to identify complex malware behavior. Rabadi, along with co-authors Jia Yi Loo ...

Malware is a constant attack to consumer gadgets, and it targets a wide range of file types and operating systems. To combat this, researchers have put much effort into creating malware detection ...

Many researchers attempted to find lightweight architectures for leaf disease detection for low-resource computational devices. Arun and Umamaheswari (2023) presented a lightweight architecture using ...

A new approach for malware classification combines deep learning with fuzzy hashing. Fuzzy hashes identify similarities among malicious files and a deep learning methodology inspired by natural ...

Microsoft and Intel Labs work on STAMINA, a new deep learning approach for detecting and classifying malware.

Hackers could disguise malware as patient protected health information in MRI and CT scan images saved in the digital imaging and communications in medicine file format, Bleeping Computer reports.