[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 …
Using convolutional neural networks for classification of malware represented as images
The number of malicious files detected every year are counted by millions. One of the main
reasons for these high volumes of different files is the fact that, in order to evade detection …
reasons for these high volumes of different files is the fact that, in order to evade detection …
Humans vs. machines in malware classification
Humans vs. Machines in Malware Classification Page 1 This paper is included in the
Proceedings of the 32nd USENIX Security Symposium. August 9–11, 2023 • Anaheim, CA, USA …
Proceedings of the 32nd USENIX Security Symposium. August 9–11, 2023 • Anaheim, CA, USA …
Automating reverse engineering with machine learning techniques
B Anderson, C Storlie, M Yates, A McPhall - Proceedings of the 2014 …, 2014 - dl.acm.org
Malware continues to be an ongoing threat, with millions of unique variants created every
year. Unlike the majority of this malware, Advanced Persistent Threat (APT) malware is …
year. Unlike the majority of this malware, Advanced Persistent Threat (APT) malware is …
Subroutine based detection of APT malware
J Sexton, C Storlie, B Anderson - Journal of Computer Virology and …, 2016 - Springer
Statistical detection of mass malware has been shown to be highly successful. However, this
type of malware is less interesting to cyber security officers of larger organizations, who are …
type of malware is less interesting to cyber security officers of larger organizations, who are …
Bayesian models applied to cyber security anomaly detection problems
JA Perusquía, JE Griffin, C Villa - International Statistical …, 2022 - Wiley Online Library
Cyber security is an important concern for all individuals, organisations and governments
globally. Cyber attacks have become more sophisticated, frequent and dangerous than ever …
globally. Cyber attacks have become more sophisticated, frequent and dangerous than ever …
Malware resistant data protection in hyper-connected networks: A survey
Data protection is the process of securing sensitive information from being corrupted,
compromised, or lost. A hyperconnected network, on the other hand, is a computer …
compromised, or lost. A hyperconnected network, on the other hand, is a computer …
Execution trace analysis using ltl-fo
We explore of use of the tool BeepBeep, a monitor for the temporal logic LTL-FO^+, in
interpreting assembly traces, focusing on security-related applications. LTL-FO^+ is an …
interpreting assembly traces, focusing on security-related applications. LTL-FO^+ is an …
Identifying metamorphic virus using n-grams and hidden markov model
SP Thunga, RK Neelisetti - 2015 International Conference on …, 2015 - ieeexplore.ieee.org
Computer virus is a rapidly evolving threat to the computing community. These viruses fall
into different categories and it is generally believed that metamorphic viruses are extremely …
into different categories and it is generally believed that metamorphic viruses are extremely …
A classification system for visualized malware based on multiple autoencoder models
J Lee, J Lee - IEEE Access, 2021 - ieeexplore.ieee.org
In this paper, we propose a classification system that uses multiple autoencoder models for
identifying malware images. It is crucial to accurately classify malware before we can deploy …
identifying malware images. It is crucial to accurately classify malware before we can deploy …