computer-vision

Cyber Attack Detection

3260 papers • 126 benchmarks • 313 datasets

Cybersecurity attacks prediction using deep learning

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in cyber-attack-detection

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Use these libraries to find cyber-attack-detection models and implementations

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Most implemented papers

Deep Anomaly Detection with Deviation Networks

Guansong Pang, Anton van den Hengel, Chunhua Shen•Wed Jul 24 2019

A novel anomaly detection framework and its instantiation that can be trained substantially more data-efficiently and achieves significantly better anomaly scoring than state-of-the-art competing methods is introduced.

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Improving SIEM for Critical SCADA Water Infrastructures Using Machine Learning

Hanan Hindy, Ethan Bayne, X. Bellekens, David Brosset, A. Seeam•Wed Sep 05 2018

This paper presents a model that detects anomaly events in a water system controlled by SCADA, and helps in accelerating the mitigation process by notifying the operator with additional information when an anomaly occurs.

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Online Cyber-Attack Detection in Smart Grid: A Reinforcement Learning Approach

Mehmet Necip Kurt, Oyetunji E. Ogundijo, Chong Li, Xiaodong Wang•Thu Sep 13 2018

This paper forms the online attack/anomaly detection problem as a partially observable Markov decision process (POMDP) problem and proposes a universal robust online detection algorithm using the framework of model-free reinforcement learning (RL) for POMDPs.

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Cyber Attack Detection thanks to Machine Learning Algorithms

A. Delplace, Sheryl M Hermoso, K. Anandita•Thu Jan 16 2020

This paper explores Machine Learning as a viable solution by examining its capabilities to classify malicious traffic in a network by analyzes five different machine learning algorithms against NetFlow dataset containing common botnets.

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A Transfer Learning and Optimized CNN Based Intrusion Detection System for Internet of Vehicles

Li Yang, A. Shami•Wed Jan 26 2022

A transfer learning and ensemble learning-based IDS is proposed for IoV systems using convolutional neural networks (CNNs) and hyper-parameter optimization techniques and shows the effectiveness of the proposed IDS for cyber-attack detection in both intra-vehicle and external vehicular networks.

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A Deep Multi-Modal Cyber-Attack Detection in Industrial Control Systems

Sepideh Bahadoripour, Ethan MacDonald, H. Karimipour•Mon Apr 03 2023

Results using the Secure Water Treatment (SWaT) system show that the proposed model can outperform existing single modality models and recent works in the literature by achieving 0.99 precision,0.98 recall, and 0.98 f-measure, which shows the effectiveness of using both modalities in a combined model for detecting cyber-attacks.

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