CIMDS: adapting postprocessing techniques of associative classification for malware detection

Y Ye, T Li, Q Jiang, Y Wang - IEEE Transactions on Systems …, 2010 - ieeexplore.ieee.org
Malware is software designed to infiltrate or damage a computer system without the owner's
informed consent (eg, viruses, backdoors, spyware, trojans, and worms). Nowadays …

Hierarchical associative classifier (HAC) for malware detection from the large and imbalanced gray list

Y Ye, T Li, K Huang, Q Jiang, Y Chen - Journal of Intelligent Information …, 2010 - Springer
Nowadays, numerous attacks made by the malware (eg, viruses, backdoors, spyware,
trojans and worms) have presented a major security threat to computer users. Currently, the …

Malware detection based on code visualization and two-level classification

V Moussas, A Andreatos - Information, 2021 - mdpi.com
Malware creators generate new malicious software samples by making minor changes in
previously generated code, in order to reuse malicious code, as well as to go unnoticed from …

Intelligent file scoring system for malware detection from the gray list

Y Ye, T Li, Q Jiang, Z Han, L Wan - Proceedings of the 15th ACM …, 2009 - dl.acm.org
Currently, the most significant line of defense against malware is anti-virus products which
focus on authenticating valid software from a white list, blocking invalid software from a black …

Advanced windows methods on malware detection and classification

D Rabadi, SG Teo - Proceedings of the 36th Annual Computer Security …, 2020 - dl.acm.org
Application Programming Interfaces (APIs) are still considered the standard accessible data
source and core wok of the most widely adopted malware detection and classification …

A novel malware analysis framework for malware detection and classification using machine learning approach

K Sethi, SK Chaudhary, BK Tripathy… - Proceedings of the 19th …, 2018 - dl.acm.org
Nowadays, the digitization of the world is under a serious threat due to the emergence of
various new and complex malware every day. Due to this, the traditional signature-based …

Malware classification using byte sequence information

B Jung, T Kim, EG Im - Proceedings of the 2018 Conference on …, 2018 - dl.acm.org
The number of new malware and new malware variants have been increasing continuously.
Security experts analyze malware to capture the malicious properties of malware and to …

SBMDS: an interpretable string based malware detection system using SVM ensemble with bagging

Y Ye, L Chen, D Wang, T Li, Q Jiang… - Journal in computer …, 2009 - Springer
Malicious executables are programs designed to infiltrate or damage a computer system
without the owner's consent, which have become a serious threat to the security of computer …

Association rule-based malware classification using common subsequences of API calls

G D'Angelo, M Ficco, F Palmieri - Applied Soft Computing, 2021 - Elsevier
Emerging malware pose increasing challenges to detection systems as their variety and
sophistication continue to increase. Malware developers use complex techniques to …

A new malware detection system using machine learning techniques for API call sequences

MA Jerlin, K Marimuthu - Journal of Applied Security Research, 2018 - Taylor & Francis
The detection and classification of malwares in windows executables is an important and
demanding task in the field of data mining. The malwares can easily damage the system by …