Identifying Authorship in Malicious Binaries: Features, Challenges & Datasets

J Gray, D Sgandurra, L Cavallaro… - ACM Computing …, 2024 - dl.acm.org
Attributing a piece of malware to its creator typically requires threat intelligence. Binary
attribution increases the level of difficulty as it mostly relies upon the ability to disassemble …

ZeVigilante: Detecting Zero‐Day Malware Using Machine Learning and Sandboxing Analysis Techniques

F Alhaidari, NA Shaib, M Alsafi… - Computational …, 2022 - Wiley Online Library
For the enormous growth and the hysterical impact of undocumented malicious software,
otherwise known as Zero-Day malware, specialized practices were joined to implement …

Identification of malicious code variants based on image visualization

H Naeem, B Guo, MR Naeem, F Ullah… - Computers & Electrical …, 2019 - Elsevier
The recent increases in Internet use and the number of malicious attacks are helping
attackers generate malware variants through automated software. Because of these attacks …

A cross-platform malware variant classification based on image representation

H Naeem, B Guo, F Ullah… - KSII Transactions on …, 2019 - koreascience.kr
Recent internet development is helping malware researchers to generate malicious code
variants through automated tools. Due to this reason, the number of malicious variants is …

AI@ nti-Malware: An intelligent framework for defending against malware attacks

YW Ma, JL Chen, WH Kuo, YC Chen - Journal of Information Security and …, 2022 - Elsevier
Distinguishing among types of malware is important to understanding how they infect
computing systems, the level of threat that they pose, and means of protecting against them …

Malware detection and classification in IoT network using ANN

A Jamal, MF Hayat, M Nasir - Mehran University Research …, 2022 - search.informit.org
Internet of Things is an emerging technology in the modern world and its network is
expanding constantly. Meanwhile, IoT devices are a soft target and vulnerable to attackers …

Nation-state threat actor attribution using fuzzy hashing

M Kida, O Olukoya - IEEE Access, 2022 - ieeexplore.ieee.org
Recent years have seen a rise in state-sponsored malware. Advanced Persistent Threat
groups (APTs) have been waging a covert war with little repercussions due to the …

Malware classification using machine learning algorithms and tools

G Mahajan, B Saini, S Anand - 2019 Second international …, 2019 - ieeexplore.ieee.org
Malware classification is the process of categorizing the families of malware on the basis of
their signatures. This work focuses on classifying the emerging malwares on the basis of …

Evaluation and survey of state of the art malware detection and classification techniques: Analysis and recommendation

P Maniriho, A Mahmood… - Available at SSRN …, 2022 - papers.ssrn.com
Malware attacks are increasing worldwide and are spreading among different platforms
such as desktop and mobile. Malware can potentially damage the compromised system and …

[PDF][PDF] Applying supervised learning on malware authorship attribution

C Boot - 2019 - cs.ru.nl
Malware is a problem in current digital society, since it can cause economic or physical
damage and in the end disrupt society as a whole. Although anti-virus solutions attempt to …