Detection of Unknown DDoS Attacks with Deep Learning and Gaussian Mixture Model

Article Telecommunications

Ensemble machine learning approaches for webshell detection in Internet of things environments

Binbin Yong et al.

Summary: The Internet of things (IoT) is a system made up of a large number of interconnected sensor devices that can be used for data exchange, intelligent identification, and management, playing a crucial role in improving living quality and standards. However, IoT is vulnerable to cyberattacks from the Internet, making network security essential. This article utilizes machine learning models to detect webshell and discusses detection methods in different IoT environments for building secure solutions. Extensive experiments verify the effectiveness of webshell intrusion detection, with simulation results showing the suitability of certain methods for lightweight and heavyweight IoT scenarios.

TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES (2022)

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Article Computer Science, Artificial Intelligence

Recent Advances in Open Set Recognition: A Survey

Chuanxing Geng et al.

Summary: This paper provides a comprehensive survey of existing open set recognition techniques, covering various aspects such as related definitions, models representations, datasets, evaluation criteria, and algorithm comparisons. It also briefly analyzes the relationships between OSR and its related tasks, highlights the limitations of existing approaches, and points out some promising subsequent research directions in this field.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2021)

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Article Physics, Multidisciplinary

An Efficient DenseNet-Based Deep Learning Model for Malware Detection

Jeyaprakash Hemalatha et al.

Summary: This study presents an efficient malware detection system based on deep learning, which improves classification performance by visualizing malware as images and addresses the challenges of traditional methods in identifying new malware and handling class imbalance. Experimental results demonstrate that the system can efficiently detect new samples with lower false-positive rates and computational time.

ENTROPY (2021)

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Article Computer Science, Information Systems