[HTML][HTML] The rise of machine learning for detection and classification of malware: Research developments, trends and challenges

D Gibert, C Mateu, J Planes - Journal of Network and Computer …, 2020 - Elsevier
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 …

A survey on malware detection using data mining techniques

Y Ye, T Li, D Adjeroh, SS Iyengar - ACM Computing Surveys (CSUR), 2017 - dl.acm.org
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 …

Adversarial attacks against Windows PE malware detection: A survey of the state-of-the-art

X Ling, L Wu, J Zhang, Z Qu, W Deng, X Chen… - Computers & …, 2023 - Elsevier
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 …

RS-Del: Edit distance robustness certificates for sequence classifiers via randomized deletion

Z Huang, NG Marchant, K Lucas… - Advances in …, 2023 - proceedings.neurips.cc
Randomized smoothing is a leading approach for constructing classifiers that are certifiably
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

M Yoosefzadeh-Najafabadi, D Tulpan, M Eskandari - Remote Sensing, 2021 - mdpi.com
Recent advanced high-throughput field phenoty** combined with sophisticated big data
analysis methods have provided plant breeders with unprecedented tools for a better …

Gotcha-sly malware! scorpion a metagraph2vec based malware detection system

Y Fan, S Hou, Y Zhang, Y Ye… - Proceedings of the 24th …, 2018 - dl.acm.org
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 …

A Survey of strategy-driven evasion methods for PE malware: transformation, concealment, and attack

J Geng, J Wang, Z Fang, Y Zhou, D Wu, W Ge - Computers & Security, 2024 - Elsevier
The continuous proliferation of malware poses a formidable threat to the cyberspace
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 …

Securedroid: Enhancing security of machine learning-based detection against adversarial android malware attacks

L Chen, S Hou, Y Ye - Proceedings of the 33rd Annual Computer …, 2017 - dl.acm.org
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 …

Arms race in adversarial malware detection: A survey

D Li, Q Li, Y Ye, S Xu - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
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 …