SAGMAD – A Signature Agnostic Malware Detection System Based on Binary Visualisation and Fuzzy Sets (bibtex)

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,
call={preparatory},
acronym={FuzzyBINVIS},
fulltitle={Malware Detection Through Fuzzy Binary Visualization and Deep Learning},
pi={Basil Papadopoulos},
affiliation={Democritus University of Thrace},
researchfield={Mathematics and Computer Science},
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}
}