Results 21 to 30 of about 1,517 (174)
A New Learning Approach to Malware Classification Using Discriminative Feature Extraction
IEEE Access, 2019 With the development of the Internet, malware has become one of the most significant threats. Recognizing specific types of malware is an important step toward effective removal.
Ya-shu Liu +3 more
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Features Engineering for Malware Family Classification Based API Call
Computers, 2022 Malware is used to carry out malicious operations on networks and computer systems. Consequently, malware classification is crucial for preventing malicious attacks.
Ammar Yahya Daeef +2 more
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Frontiers in Plant Science, 2023 Due to developments in science and technology, the field of plant protection and the information industry have become increasingly integrated, which has resulted in the creation of plant protection information systems.
Zhiguo Chen +5 more
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On Visual Hallmarks of Robustness to Adversarial Malware
CoRR, 2018 A central challenge of adversarial learning is to interpret the resulting hardened model. In this contribution, we ask how robust generalization can be visually discerned and whether a concise view of the interactions between a hardened decision map and input samples is possible.
Alex Huang +3 more
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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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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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