Results 11 to 20 of about 12,725 (233)
Semantics-aware malware detection [PDF]
2005 IEEE Symposium on Security and Privacy (S&P'05), 2005 A malware detector is a system that attempts to determine whether a program has malicious intent. In order to evade detection, malware writers (hackers) frequently use obfuscation to morph malware. Malware detectors that use a pattern-matching approach (such as commercial virus scanners) are susceptible to obfuscations used by hackers.
Mihai Christodorescu +4 more
core +3 more sources
A Comprehensive Review on Malware Detection Approaches
IEEE Access, 2020 According to the recent studies, malicious software (malware) is increasing at an alarming rate, and some malware can hide in the system by using different obfuscation techniques.
Ömer Aslan, Refik Samet
exaly +3 more sources
A Survey on Malware and Malware Detection Systems [PDF]
International Journal of Computer Applications, 2013 Lately, a new kind of war takes place between the security community and malicious software developers, the security specialists use all possible techniques, methods and strategies to stop and remove the threats while the malware developers utilize new ...
Ali M. A. Abuagoub +2 more
openaire +2 more sources
A Survey on ML Techniques for Multi-Platform Malware Detection: Securing PC, Mobile Devices, IoT, and Cloud Environments. [PDF]
Sensors (Basel)Malware has emerged as a significant threat to end-users, businesses, and governments, resulting in financial losses of billions of dollars. Cybercriminals have found malware to be a lucrative business because of its evolving capabilities and ability to ...
Ferdous J +3 more
europepmc +2 more sources
A survey of IoT malware and detection methods based on static features
ICT Express, 2020 Due to a lack of security design as well as the specific characteristics of IoT devices such as the heterogeneity of processor architecture, IoT malware detection has to deal with very unique challenges, especially on detecting cross-architecture IoT ...
Quoc-Dung Ngo, Huy-Trung Nguyen
exaly +3 more sources
LEDA-Layered Event-Based Malware Detection Architecture. [PDF]
Sensors (Basel)The rapid increase in new malware necessitates effective detection methods. While machine learning techniques have shown promise for malware detection, most research focuses on identifying malware through the content of executable files or full behavior ...
Portase RM +3 more
europepmc +2 more sources
Packed malware variants detection using deep belief networks [PDF]
MATEC Web of Conferences, 2020 Malware is one of the most serious network security threats. To detect unknown variants of malware, many researches have proposed various methods of malware detection based on machine learning in recent years.
Zhang Zhigang +3 more
doaj +1 more source
MalFuzz: Coverage-guided fuzzing on deep learning-based malware classification model.
PLoS ONE, 2022 With the continuous development of deep learning, more and more domains use deep learning technique to solve key problems. The security issues of deep learning models have also received more and more attention.
Yuying Liu +4 more
doaj +2 more sources
A Survey and Evaluation of Android-Based Malware Evasion Techniques and Detection Frameworks
Information, 2023 Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware.
Parvez Faruki +5 more
doaj +1 more source
IEEE Access, 2023 Malware has emerged as a cyber security threat that continuously changes to target computer systems, smart devices, and extensive networks with the development of information technologies.
Nor Zakiah Gorment +3 more
doaj +1 more source