Results 51 to 60 of about 6,970 (211)

Linux malware analysis

, 2021
The scope of this thesis is the study of Malware Analysis on Linux environments in a systematic and detailed manner, based on SAMA methodology. Moreover, the ENISA guidelines were advised for creating a modular laboratory, capable of isolating the infected VMs and providing them with Internet connection or a simulated one by applying the appropriate ...
openaire   +2 more sources

A Machine Learning Framework for Detecting and Preventing Cyber‐Attacks in Industrial Cyber‐Physical Systems

Engineering Reports, Volume 8, Issue 1, January 2026.
Proposed cyber physical system security framework. ABSTRACT The increasing adoption of cyber‐physical systems (CPS) in Industry 4.0 has heightened vulnerability to cyber threats. This study proposes a machine learning–based intrusion detection framework, DBID‐Net, to effectively identify and prevent attacks in CPS environments. The framework integrates
Anurag Sinha, Rejuwan Shamim, Mihika Mahendra, Trupti Mohota, G. Madhukar Rao, Mohammad Nadeem Ahmed, Mohammad Rashid Hussain, Satyam Solanki, Tanish Ranjan, Bhaskar, Mini Kumari, Karan Dixit, Vyom Modi, Syed Immamul Ansarullah, Mohd Asif Shah   +14 more
wiley   +1 more source

Classification of Malware Images Using Fine-Tunned ViT

Sakarya University Journal of Computer and Information Sciences
Malware 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

Detection of Cyber Malware Attack Based on Network Traffic Features Using Neural Network

Khazanah Informatika, 2020
Various techniques have been developed to detect cyber malware attacks, such as behavior based method which utilizes the analysis of permissions and system calls made by a process.
Ventje Jeremias Lewi Engel, Evan Joshua, Mychael Maoeretz Engel   +2 more
doaj   +1 more source

Android Platform Malware Analysis [PDF]

International Journal of Advanced Computer Science and Applications, 2015
Mobile devices have evolved from simple devices, which are used for a phone call and SMS messages to smartphone devices that can run third party applications. Nowadays, malicious software, which is also known as malware, imposes a larger threat to these mobile devices.
Khalid Alfalqi, Rubayyi Alghamdi, Mofareh Waqdan   +2 more
openaire   +1 more source

Explainable AI With Imbalanced Learning Strategies for Blockchain Transaction Fraud Detection

Engineering Reports, Volume 8, Issue 1, January 2026.
Research methodology pipeline for blockchain fraud detection. ABSTRACT Blockchain networks now support billions of dollars in daily transactions, making reliable and transparent fraud detection essential for maintaining user trust and financial stability.
Ahmed Abbas Jasim Al‐Hchaimi, M. A. Khalifa, Walid El‐Shafai   +2 more
wiley   +1 more source

MalQwen: Fine Tuned LLM for Static Android Malware Analysis Report

IEEE Access
The 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, Angela Oryza Prabowo, Annisa Dwi Puspitarini, Raihan Adam Handoyo Winarso, Nur Aisyah, Mohammad Yoga Pratama, Diana Purwitasari, Baskoro Adi Pratomo   +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., Ieronymakis V., Khan M.T., Serpanos D.   +3 more
doaj   +1 more source

Exploiting Vision Transformer and Ensemble Learning for Advanced Malware Classification

Engineering Reports, Volume 8, Issue 1, January 2026.
Overview of the proposed RF–ViT ensemble for multi‐class malware classification. Textual (BoW/byte‐frequency) and visual representations are combined via a product rule, achieving improved accuracy and robustness over individual models. ABSTRACT Malware remains a significant concern for modern digital systems, increasing the need for reliable and ...
Fadi Makarem, Rida El Chall, Abed Ellatif Samhat, Khouloud Samrouth, Nader Bakir   +4 more
wiley   +1 more source

ZeVigilante: Detecting Zero-Day Malware Using Machine Learning and Sandboxing Analysis Techniques [PDF]

, 2022
Fahd Alhaidari, Nouran Abu Shaib, Maram Alsafi, Haneen Alharbi, Majd Alawami, Reem Aljindan, Atta Rahman, Rachid Zagrouba   +7 more
openalex   +1 more source