Results 31 to 40 of about 465,682 (204)
Review of malware detection and classification visualization techniques
网络与信息安全学报, 2023 With the rapid advancement of technology, network security faces a significant challenge due to the proliferation of malicious software and its variants.These malicious software use various technical tactics to deceive or bypass traditional detection ...
Jinwei WANG, Zhengjia CHEN, Xue XIE, Xiangyang LUO, Bin MA
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Benign-salient Region Based End-to-End Adversarial Malware Generation Method [PDF]
Jisuanji kexueMalware detection methods combining visualization techniques and deep learning have gained widespread attention due to their high accuracy and low cost.However,deep learning models are vulnerable to adversarial attacks,where intentional small-scale ...
YUAN Mengjiao, LU Tianliang, HUANG Wanxin, HE Houhan
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A Classification System for Visualized Malware Based on Multiple Autoencoder Models
IEEE Access, 2021 In this paper, we propose a classification system that uses multiple autoencoder models for identifying malware images. It is crucial to accurately classify malware before we can deploy appropriate countermeasures to prevent them from spreading.
Jongkwan Lee, Jongdeog Lee
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Malware Detection Using Binary Visualization and Neural Networks [PDF]
E3S Web of Conferences, 2023 Any programme or code that is damaging to our systems or networks is known as Malware or malicious software. Malware attempts to infiltrate, damage, or destroy our gadgets such as computers, networks, tablets, and so on. Malware may also grant partial or
Jonnala Yamini Devi +4 more
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Classification and Analysis of Android Malware Images Using Feature Fusion Technique
IEEE Access, 2021 The super packed functionalities and artificial intelligence (AI)-powered applications have made the Android operating system a big player in the market.
Jaiteg Singh +5 more
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BinSlayer: Accurate Comparison of Binary Executables [PDF]
, 2013 As the volume of malware inexorably rises, comparison of binary code is of increasing importance to security analysts as a method of automatically classifying new malware samples; purportedly new examples of malware are frequently a simple evolution of ...
Martial Bourquin +5 more
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A Deep Learning Framework for Three-Dimensional Malware Image Classification
Applied SciencesThe rapid growth of sophisticated malware, including polymorphic, metamorphic, and zero-day threats, has made traditional signature-based and heuristic detection methods increasingly insufficient in modern desktop computing environments. As cyber threats
Muharrem Aslantas +3 more
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Efficient Malware Analysis Using Subspace-Based Methods on Representative Image Patterns
IEEE Access, 2023 In this paper, we propose a new framework for classifying and visualizing malware files using subspace-based methods. The rise of advanced malware poses a significant threat to internet security, increasing the pressure on traditional cybersecurity ...
Djafer Yahia M Benchadi +2 more
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MalGrid: Visualization of Binary Features in Large Malware Corpora
MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM), 2022 The number of malware is constantly on the rise. Though most new malware are modifications of existing ones, their sheer number is quite overwhelming. In this paper, we present a novel system to visualize and map millions of malware to points in a 2-dimensional (2D) spatial grid. This enables visualizing relationships within large malware datasets that
Tajuddin Manhar Mohammed +4 more
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Studying direct-touch interaction for 2D flow visualization [PDF]
, 2015 Traditionally, scientific visualization research concentrates on the development and improvement of interactive techniques to support expert data analysis.
Hinrichs, Uta +2 more
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