[HTML][HTML] The rise of machine learning for detection and classification of malware: Research developments, trends and challenges
The struggle between security analysts and malware developers is a never-ending battle
with the complexity of malware changing as quickly as innovation grows. Current state-of-the …
with the complexity of malware changing as quickly as innovation grows. Current state-of-the …
A survey on malware detection using data mining techniques
In the Internet age, malware (such as viruses, trojans, ransomware, and bots) has posed
serious and evolving security threats to Internet users. To protect legitimate users from these …
serious and evolving security threats to Internet users. To protect legitimate users from these …
Adversarial attacks against Windows PE malware detection: A survey of the state-of-the-art
Malware has been one of the most damaging threats to computers that span across multiple
operating systems and various file formats. To defend against ever-increasing and ever …
operating systems and various file formats. To defend against ever-increasing and ever …
RS-Del: Edit distance robustness certificates for sequence classifiers via randomized deletion
Randomized smoothing is a leading approach for constructing classifiers that are certifiably
robust against adversarial examples. Existing work on randomized smoothing has focused …
robust against adversarial examples. Existing work on randomized smoothing has focused …
Using hybrid artificial intelligence and evolutionary optimization algorithms for estimating soybean yield and fresh biomass using hyperspectral vegetation indices
Recent advanced high-throughput field phenoty** combined with sophisticated big data
analysis methods have provided plant breeders with unprecedented tools for a better …
analysis methods have provided plant breeders with unprecedented tools for a better …
Gotcha-sly malware! scorpion a metagraph2vec based malware detection system
Due to its severe damages and threats to the security of the Internet and computing devices,
malware detection has caught the attention of both anti-malware industry and researchers …
malware detection has caught the attention of both anti-malware industry and researchers …
A Survey of strategy-driven evasion methods for PE malware: transformation, concealment, and attack
The continuous proliferation of malware poses a formidable threat to the cyberspace
landscape. Researchers have proffered a multitude of sophisticated defense mechanisms …
landscape. Researchers have proffered a multitude of sophisticated defense mechanisms …
Applying NLP techniques to malware detection in a practical environment
M Mimura, R Ito - International Journal of Information Security, 2022 - Springer
Executable files still remain popular to compromise the endpoint computers. These
executable files are often obfuscated to avoid anti-virus programs. To examine all suspicious …
executable files are often obfuscated to avoid anti-virus programs. To examine all suspicious …
Securedroid: Enhancing security of machine learning-based detection against adversarial android malware attacks
With smart phones being indispensable in people's everyday life, Android malware has
posed serious threats to their security, making its detection of utmost concern. To protect …
posed serious threats to their security, making its detection of utmost concern. To protect …
Arms race in adversarial malware detection: A survey
Malicious software (malware) is a major cyber threat that has to be tackled with Machine
Learning (ML) techniques because millions of new malware examples are injected into …
Learning (ML) techniques because millions of new malware examples are injected into …