Project Acronym: FuzzyBINVISTitle: Malware Detection Through Fuzzy Binary Visualization and Deep LearningAffiliation: democritus university of thracePi: Basil PapadopoulosResearch Field: mathematics and computer science
SAGMAD – A Signature Agnostic Malware Detection System Based on Binary Visualisation and Fuzzy Sets
by Saridou, Betty, Rose, Joseph Ryan, Shiaeles, Stavros and Papadopoulos, Basil
Reference:
SAGMAD – A Signature Agnostic Malware Detection System Based on Binary Visualisation and Fuzzy Sets (Saridou, Betty, Rose, Joseph Ryan, Shiaeles, Stavros and Papadopoulos, Basil), In Electronics, volume 11, 2022.
Bibtex Entry:
@article{10.3390-electronics11071044,
author = {Saridou, Betty and Rose, Joseph Ryan and Shiaeles, Stavros and Papadopoulos, Basil},
title = {SAGMAD -- A Signature Agnostic Malware Detection System Based on Binary Visualisation and Fuzzy Sets},
journal = {Electronics},
volume = {11},
year = {2022},
bibyear = {2022},
number = {7},
article-number = {1044},
url = {https://www.mdpi.com/2079-9292/11/7/1044},
doi = {10.3390/electronics11071044},
}