Results 61 to 70 of about 11,113 (232)
MalQwen: Fine Tuned LLM for Static Android Malware Analysis Report
IEEE AccessThe Android operating system continues to face escalating security challenges, primarily due to its open-source nature and the rapid proliferation of applications from untrusted sources.
Tegar Ganang Satrio Priambodo +7 more
doaj +1 more source
An Open Source, Extensible Malware Analysis Platform
MATEC Web of Conferences, 2018 A malware (such as viruses, ransomware) is the main source of bringing serious security threats to the IT systems and their users now-adays. In order to protect the systems and their legitimate users from these threats, anti-malware applications are ...
Michalopoulos P. +3 more
doaj +1 more source
A Comparative Analysis of Android Malware
Proceedings of the 5th International Conference on Information Systems Security and Privacy, 2019 In this paper, we present a comparative analysis of benign and malicious Android applications, based on static features. In particular, we focus our attention on the permissions requested by an application. We consider both binary classification of malware versus benign, as well as the multiclass problem, where we classify malware samples into their ...
Neeraj Chavan +2 more
openaire +2 more sources
, 2022 DoH-DGA-Malware-Traffic-HKD (csv_files.zip, l3-malware.csv, pcap_files.zip, and README.txt): If you use the dataset, please be sure to cite the following paper.Rikima Mitsuhashi, Yong Jin, Katsuyoshi Iida, Takahiro Shinagawa, and Yoshiaki Takai ...
Jin, Yong +4 more
core +1 more source
Classification of Malware Images Using Fine-Tunned ViT
Sakarya University Journal of Computer and Information SciencesMalware detection and classification have become critical tasks in ensuring the security and integrity of computer systems and networks. Traditional methods of malware analysis often rely on signature-based approaches, which struggle to cope with the ...
Özal Yıldırım, Oğuzhan Katar
doaj +1 more source
Behavior Abstraction in Malware Analysis [PDF]
, 2010 We present an approach for proactive malware detection by working on an abstract representation of a program behavior. Our technique consists in abstracting program traces, by rewriting given subtraces into abstract symbols representing their functionality.
Beaucamps, Philippe +2 more
openaire +2 more sources
Graph neural network‐based attack prediction for communication‐based train control systems
CAAI Transactions on Intelligence Technology, EarlyView.Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao +3 more
wiley +1 more source
Fast and Straightforward Feature Selection Method [PDF]
, 2020 Malware analysis and detection is currently one of the major topics in the information security landscape. Two main approaches to analyze and detect malware are static and dynamic analyses.
Banin, Sergii, Sergii Banin
core +1 more source
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma +4 more
wiley +1 more source
Visualization and deep-learning-based malware variant detection using OpCode-level features
, 2021 Malicious software (malware) is a major threat to the systems and networks’ security. Although anti-malware products are used to protect systems and networks against malware attacks, obfuscated malware that is capable of evading analysis and detection by
Alhashmi, A. +4 more
core +1 more source