Filters








2,000 Hits in 5.3 sec

Detection and Isolation of DoS and Integrity Cyber Attacks in Cyber-Physical Systems with a Neural Network-Based Architecture

Carlos M. Paredes, Diego Martínez-Castro, Vrani Ibarra-Junquera, Apolinar González-Potes
2021 Electronics  
Based on the above, this work proposes an architecture based on artificial neural networks for detection and isolation of cyber attacks Denial of Service (DoS) and integrity in CPS.  ...  This flexibility opens a large gap that affects the security of control systems since the new communication links can be used by people to generate attacks that produce risk in these applications.  ...  In this work, a new architecture for DoS and integrity cyber attacks detection and isolation in Cyber Physical Systems using one-dimensional Convolutional Neural Networks was presented, thereby overcoming  ... 
doi:10.3390/electronics10182238 fatcat:umer5y2fcvg3bmelq5uunm7m2a

On the performance metrics for cyber-physical attack detection in smart grid

Sayawu Yakubu Diaba, Miadreza Shafie-khah, Mohammed Elmusrati
2022 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
In this paper, we have deployed an intrusion detection system to detect cyber-physical attacks in the SCADA system concatenating the Convolutional Neural Network and Gated Recurrent Unit as a collective  ...  So far security measures deployed for SCADA systems detect cyber-attacks, however, the performance metrics are not up to the mark.  ...  Introduction Most of the Intrusion Detection Systems (IDS) used in Supervisory Control and Data Acquisition (SCADA) in power distribution networks are currently concentrated on the cyber sector by ignoring  ... 
doi:10.1007/s00500-022-06761-1 fatcat:gbukjb2rpfhtzakp6ih7rg3rha

Deep Learning-Based Intrusion Detection for Distributed Denial of Service Attack in Agriculture 4.0

Mohamed Amine Ferrag, Lei Shu, Hamouda Djallel, Kim-Kwang Raymond Choo
2021 Electronics  
In this paper, we propose a deep learning-based intrusion detection system for DDoS attacks based on three models, namely, convolutional neural networks, deep neural networks, and recurrent neural networks  ...  Security researchers are involved in this topic to ensure the safety of the system since an adversary can initiate many cyber attacks, such as DDoS attacks to making a service unavailable and then injecting  ...  [21] an anomaly detection system, named ADS, for detecting cyber attacks in the industrial internet of things.  ... 
doi:10.3390/electronics10111257 fatcat:xojjd57fwrhdjgy67u5ne2roum

A Layer Image Auditing System Secured by Blockchain

Jinwoo Song, Young Moon
2021 Procedia Manufacturing  
computer networks in CPMS opens new doors for adversaries to compromise various components in an attack detection system.  ...  LIAS consists of a pre-processing system and a Multilayer Perceptron Neural Network (MLP).  ...  Nomenclature CPMS Cyber-Physical Manufacturing System AM Additive Manufacturing LIAS Layer Image Auditing System MLP Multilayer Perceptron Neural Network IDS Intrusion Detection System CNN Convolution  ... 
doi:10.1016/j.promfg.2021.06.059 fatcat:w7oaxfv4rfdobix2dztfgsjjuq

A Novel Cyber-attack Leads Prediction System using Cascaded R2CNN Model

P. Shanmuga Prabha, S. Magesh Kumar
2022 International Journal of Advanced Computer Science and Applications  
The proposed model is represented as R2CNN that acts as the cascaded combination of Gradient boosted regression detector with recurrent convolution neural network for pattern prediction.  ...  The features are tested for correlation with the trained dataset and evaluate the early prediction of Cyber-attacks in the massive connected IoT devices.  ...  ., [11] evaluated a deep recurrent neural network model for detecting the cyber-attacks in internet controlled devices using traffic data of network.  ... 
doi:10.14569/ijacsa.2022.0130260 fatcat:b44tzg26ejhv7ngrfwmz4lixjm

Hybrid Deep Learning: An Efficient Reconnaissance and Surveillance Detection Mechanism in SDN

Jahanzaib Malik, Adnan Akhunzada, Iram Bibi, Muhammad Imran, Arslan Musaddiq, Sung Won Kim
2020 IEEE Access  
However, the centralized control intelligence and programmability is primarily a potential target for the evolving cyber threats and attacks to throw the entire network into chaos.  ...  INDEX TERMS Security, hybrid deep learning model, software defined networks, long short-term memory, convolutional neural network.  ...  Besides, intrusion detection system (IDS) is a basic tool used to identify different cyber-attacks inside a system.  ... 
doi:10.1109/access.2020.3009849 fatcat:5p767sq2zvdojomdgg77wjs7cm

Siamese Neural Network Based Few-Shot Learning for Anomaly Detection in Industrial Cyber-Physical Systems

Xiaokang Zhou, Wei Liang, Shohei Shimizu, Jianhua Ma, Qun Jin
2020 IEEE Transactions on Industrial Informatics  
In this study, we propose a Few-Shot Learning model with Siamese Convolution Neural Network (FSL-SCNN), to alleviate the over-fitting issue and enhance the accuracy for intelligent anomaly detection in  ...  With the increasing population of Industry 4.0, both AI and smart techniques have been applied and become hotly discussed topics in industrial Cyber-Physical Systems (CPS).  ...  [6] considered a covert attack for service degradation, and introduced a backtracking search optimization algorithm to deal with the system identification attack in cyber-physical control systems.  ... 
doi:10.1109/tii.2020.3047675 fatcat:ndlbl65nr5bl7aq4qpmvqqeiwu

2021 Index IEEE Transactions on Industrial Informatics Vol. 17

2021 IEEE Transactions on Industrial Informatics  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Note that the item title is found only under the primary entry in the Author Index.  ...  ., +, TII Jan. 2021 596-605 Evolutionary Deep Belief Network for Cyber-Attack Detection in Industrial Automation and Control System.  ... 
doi:10.1109/tii.2021.3138206 fatcat:ulsazxgmpfdmlivigjqgyl7zre

Reinforcement Learning for Industrial Control Network Cyber Security Orchestration [article]

John Mern, Kyle Hatch, Ryan Silva, Jeff Brush, Mykel J. Kochenderfer
2021 arXiv   pre-print
In this work, we present techniques to scale deep reinforcement learning to solve the cyber security orchestration problem for large industrial control networks.  ...  Defending computer networks from cyber attack requires coordinating actions across multiple nodes based on imperfect indicators of compromise while minimizing disruptions to network operations.  ...  Introduction Cyber attacks have been increasingly targeting computer networks that are integrated with industrial control systems (ICS) [1] .  ... 
arXiv:2106.05332v1 fatcat:jkegyyu63ng2db5x7ccb4a3aee

Deep anomaly detection for industrial systems: a case study

Feng Xue, Weizhong Yan, Tianyi Wang, Hao Huang, Bojun Feng
2020 Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM  
We explore the use of deep neural networks for anomaly detection of industrial systems where the data are multivariate time series measurements.  ...  Also, Support Vector Data Description (SVDD) method is adapted to such anomaly detection settings with deep neural networks.  ...  CONCLUSION In this paper, we described a setup on using deep neural networks for anomaly detection for industrial systems.  ... 
doi:10.36001/phmconf.2020.v12i1.1186 fatcat:mtseixwucjebdjbnzli356c6rm

Technical research of detection algorithmically generated malicious domain names using machine learning methods

Hieu Duc Ho, Huong Van Ho
2020 Journal of Science and Technology on Information security  
Abstract— In recent years, many malware use domain generation algorithm for generating a large of domains to maintain their Command and Control (C&C) network infrastructure.  ...  In this paper, we present an approach for detecting malicious domain names using machine learning methods.  ...  In deep learning, a convolutional neural network is a class of deep neural networks, most commonly applied to analyzing visual imagery [10] .  ... 
doi:10.54654/isj.v7i1.54 fatcat:ylef3oc5rfgi5btholtbur4hga

Table of Contents

2021 IEEE Transactions on Industrial Informatics  
Han 6832 Contactless Fall Detection Using Time-Frequency Analysis and Convolutional Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Zeadally7075 Voice-Transfer Attacking on Industrial Voice Control Systems in 5G-Aided IIoT Domain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ... 
doi:10.1109/tii.2021.3092213 fatcat:y5utlj44oncrdgmwoqgobqozie

Review of Anomaly Detection Systems in Industrial Control Systems Using Deep Feature Learning Approach

Raogo Kabore, Adlès Kouassi, Rodrigue N'goran, Olivier Asseu, Yvon Kermarrec, Philippe Lenca
2021 Engineering  
Industrial Control Systems (ICS) or SCADA networks are increasingly targeted by cyber-attacks as their architectures shifted from proprietary hardware, software and protocols to standard and open sources  ...  Among the countermeasures to mitigate the threats, anomaly detection systems play an important role as they can help detect even unknown attacks.  ...  Introduction Industrial Control Systems (ICS) are used to monitor and control industrial sys-R. Kabore [2] .  ... 
doi:10.4236/eng.2021.131003 fatcat:dypnktvjszad3nw6yjjuwgeeum

Sensors and Pattern Recognition Methods for Security and Industrial Applications

Michał Choraś, Rafał Kozik, Marek Pawlicki
2022 Sensors  
The method reaches 98% recall and could be used to aid train control systems.  ...  In 'Face Presentation Attack Detection Using Deep Background Subtraction' [2] , Benlamoudi et al. present a detection method against those kinds of attacks.  ... 
doi:10.3390/s22165968 pmid:36015729 pmcid:PMC9415009 fatcat:qsre3whppvhyxodywel6ugiw2i

Convolutional Neural Network for Intrusion Detection System In Cyber Physical Systems [article]

Gael Kamdem De Teyou, Junior Ziazet
2019 arXiv   pre-print
The extensive use of Information and Communication Technology in critical infrastructures such as Industrial Control Systems make them vulnerable to cyber-attacks.  ...  Therefore, in this paper, we take advantage of recent progress in deep learning to build a convolutional neural networks that can detect intrusions in cyber physical system.  ...  INTRODUCTION Industrial Control System (ICS) are critical components facilitating operations in vital industries such as water, electricity, oil and gas, transportation and manufacturing known as critical  ... 
arXiv:1905.03168v2 fatcat:zphm4s4fbvblncdwvxhugijw6q
« Previous Showing results 1 — 15 out of 2,000 results