When malware is packin'heat; limits of machine learning classifiers based on static analysis features

H Aghakhani, F Gritti, F Mecca, M Lindorfer… - Network and …, 2020 - par.nsf.gov
Machine learning techniques are widely used in addition to signatures and heuristics to
increase the detection rate of anti-malware software, as they automate the creation of …

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 …

A close look at a daily dataset of malware samples

X Ugarte-Pedrero, M Graziano… - ACM Transactions on …, 2019 - dl.acm.org
The number of unique malware samples is growing out of control. Over the years, security
companies have designed and deployed complex infrastructures to collect and analyze this …

Improving Security Tasks Using Compiler Provenance Information Recovered At the Binary-Level

Y Du, O Alrawi, K Snow, M Antonakakis… - Proceedings of the 2023 …, 2023 - dl.acm.org
The complex optimizations supported by modern compilers allow for compiler provenance
recovery at many levels. For instance, it is possible to identify the compiler family and …

Malpedia: a collaborative effort to inventorize the malware landscape

D Plohmann, M Clauss, S Enders… - The Journal on …, 2017 - cyberjournal.cecyf.fr
For more than a decade now, a perpetual influx of new malware samples can be observed.
To analyze this flood effectively, static analysis is still one of the most important methods …

On the effectiveness of perturbations in generating evasive malware variants

B **, J Choi, JB Hong, H Kim - IEEE Access, 2023 - ieeexplore.ieee.org
Malware variants are generated using various evasion techniques to bypass malware
detectors, so it is important to understand what properties make them evade malware …

Analysing the fall 2020 Emotet campaign

C Patsakis, A Chrysanthou - arxiv preprint arxiv:2011.06479, 2020 - arxiv.org
In this report, we analyse the latest campaign of Emotet that had a significant impact in
several countries worldwide. We leverage the data of a specifically crafted dataset, which …

[HTML][HTML] Evaluation of printable character-based malicious PE file-detection method

M Mimura - Internet of Things, 2022 - Elsevier
Printable characters extracted from portable executable (PE) files are a common surface
analysis feature. String extraction is a supplemental feature for malware analysis. Recent …

HawkEye: cross-platform malware detection with representation learning on graphs

P Xu, Y Zhang, C Eckert, A Zarras - … 14–17, 2021, Proceedings, Part III 30, 2021 - Springer
Malicious software, widely known as malware, is one of the biggest threats to our
interconnected society. Cybercriminals can utilize malware to carry out their nefarious tasks …

Combining static and dynamic analysis to improve machine learning-based malware classification

R Chanajitt, B Pfahringer… - 2021 IEEE 8th …, 2021 - ieeexplore.ieee.org
Windows Portable Executable files can be malformed for malicious purposes. There are
many ways and tricks to circumvent standard security detection and protection measures …