Conceptio
›
Archive
›
Springer Nature OA
Springer Nature OA
open access
Enhanced Consistency Bi-directional GAN (CBiGAN) for malware anomaly detection
Wijayasiri, Thesath et al.
Springer Nature OA · Papers · License: Open Access
Open Source ↗
Computer Science, Computer Science, general, Cybercrime, Computer Applications
This document is indexed with metadata only — full text is not available in the archive for this record.
Open the official source ↗
Related documents
JSCoherence: detecting obfuscated malicious JavaScript via data-dependent statement pairs
#667020
From perception to reaction: an RLCC-engine-driven cybersecurity framework for smart agricultural ecosystems
#667023
Correction: Context is key for cybersecurity: leveraging external knowledge for process model explanation via LLMs
#667025
A PRISMA-based Systematic Review of Artificial Intelligence in Healthcare, its Applications and Challenges
#667027
Seeing only what we can see: why cyber strategy may be built on illusion
#667028
Record
· ID 174845
Retrieved via
Conceptio
— every document is proof-bundled with source, license, and retrieval metadata.