Results 161 to 170 of about 707,343 (186)

A Robust Ensemble Learning Approach for Malware Detection and Classification

Journal of Advanced Research in Applied Sciences and Engineering Technology
In today's Internet world, many dangers threaten people's safety online every day. One big danger is harmful software called malware, like GoldenEyes, Heartbleed, Rootkit etc.
Mayura V. Shelke, Jyoti Yogesh Deshmukh, Deepika Amol Ajalkar, R. B. Dhumal   +3 more
semanticscholar   +1 more source

PromptSAM+: Malware Detection based on Prompt Segment Anything Model

arXiv.org
Machine learning and deep learning (ML/DL) have been extensively applied in malware detection, and some existing methods demonstrate robust performance.
Xingyuan Wei, Yichen Liu, Ce Li, Ning Li, Degang Sun, Yan Wang   +5 more
semanticscholar   +1 more source

IoT Malware Detection Using Deep Learning

International Conference on Computing Communication and Networking Technologies
As digital infrastructure expands, the proliferation of malware files is escalating rapidly. Cyber-attacks have become increasingly complex and sophisticated, posing significant security challenges.
Maurya Ranjeet Jeebodh, Niyati Baliyan
semanticscholar   +1 more source

Cross-Regional Malware Detection via Model Distilling and Federated Learning

International Symposium on Recent Advances in Intrusion Detection
Machine Learning (ML) is a key part of modern malware detection pipelines, but its application is not straightforward. It involves multiple practical challenges that are frequently unaddressed by the literature works. A key challenge is the heterogeneity
Marcus Botacin, H. Gomes
semanticscholar   +1 more source

On the Performance of Malware Detection Classifiers Using Hardware Performance Counters

International Conference on Smart Communications and Networking
Malware detection using Hardware Performance Counters (HPC) has emerged as a promising solution to improve the security of computing systems as a complement to antivirus software.
Alireza Abolhasani Zeraatkar, P. Kamran, Inderpreet Kaur, Nagabindu Ramu, Tyler Sheaves, Hussain Al-Asaad   +5 more
semanticscholar   +1 more source

Down to earth! Guidelines for DGA-based Malware Detection

International Symposium on Recent Advances in Intrusion Detection
Successful malware campaigns rely on Command-and-Control (C2) infrastructure, enabling attackers to extract sensitive data and give instructions to bots.
B. Cebere, Jonathan Lasse Bennet Flueren, Silvia Sebastián, Daniel Plohmann, Christian Rossow   +4 more
semanticscholar   +1 more source

Detection Of Malware Families and classification using Machine Learning

2025 International Conference on Knowledge Engineering and Communication Systems (ICKECS)
With the increasing complexity of polymorphic, metamorphic, and zero-day malware, malware detection has become a critical cybersecurity concern. Because traditional signature-based methods are ineffective, machine learning (ML) and deep learning (DL ...
C. A. Anser Pasha, Abdul Rahman, B. Abhishek, M. Kaushik, Jinu John, Gopalakrishna   +5 more
semanticscholar   +1 more source

A New Approach for Android Malware Detection Based on Behavioral Profiling Techniques

Conference on Research, Innovation and Vision for the Future in Computing & Communication Technologies
The sharp increase in the number and types of Android malware poses a significant challenge to the development of effective Android malware detection methods.
Manh Vu Minh, Cho Do Xuan
semanticscholar   +1 more source

Malware Detection Techniques and Research Based on Image Analysis

International Conference Civil Engineering and Architecture
With the development of Internet, the speed of malware iteration is accelerating. To cope with the new scale and rapid variation, further optimize the model structure of malware detection, and improve the detection efficiency and accuracy, we establish a
Chenyu Li, Yanan Wang, Wen Quan, Xuanhao Liang   +3 more
semanticscholar   +1 more source

Comprehensive Vulnerability Detection and Malware Infection Testing Strategies for IoT Devices

IEEE Internet of Things Journal
With the increasing prevalence of Internet of Things (IoT) devices, security vulnerabilities and malware infections have emerged as significant risks.
Bo-Hao Liang, Ren-Hung Hwang, Jia-You Lin, Hsiao-Hwa Chen   +3 more
semanticscholar   +1 more source