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Guest Editorial Introduction to the Special Issue on Deep Learning Models for Safe and Secure Intelligent Transportation Systems

Alireza Jolfaei, Neeraj Kumar, Min Chen, Krishna Kant
2021 IEEE transactions on intelligent transportation systems (Print)  
He was a Research Professor with the Center for Secure Information Systems, George Mason University.  ...  His research interests include energy efficiency, robustness, and security in cyber and cyber-physical systems.  ...  network (GAN) model using controller area network message blocks and an enhanced GAN discriminator.  ... 
doi:10.1109/tits.2021.3090721 fatcat:c2o2vno6bjbnxdn6y4zm7ztmvq

Towards digital cognitive clones for the decision-makers: adversarial training experiments

Mariia Golovianko, Svitlana Gryshko, Vagan Terziyan, Tuure Tuunanen
2021 Procedia Computer Science  
) and a smart digital adversary as a challenger (generator of sophisticated decision situations, emergencies and attacks, which supposedly catalyzes the cloning process).  ...  ) and a smart digital adversary as a challenger (generator of sophisticated decision situations, emergencies and attacks, which supposedly catalyzes the cloning process).  ...  experience, supply chain and asset management: simulations with the self-managed "digital customers" and digitalized processes can be used to obtain the optimal settings in real-world environments and improving  ... 
doi:10.1016/j.procs.2021.01.155 fatcat:74qe4vvcurbftco53z45baupoq

GenAtSeq GAN with Heuristic Reforms for Knowledge Centric Network with Browsing Characteristics Learning, Individual Tracking and Malware Detection with Website2Vec

Chiranjib Sur
2020 SN Computer Science  
Our contributions are in the architectural definition of Generalized Attentive Sequential Generative Adversarial Network (GenAtSeq-GAN), identification of log characteristics for discrimination, and the  ...  Our proposed GAN network is characterized for the detection of individuals through dissimilarity between real and generated samples and quantification of detected difference, both of which enhanced learning  ...  Network researcher is empowering these networks through several improvements in technology like deciding the right path, improved and situation-aware stitching systems, effective network coding, distribution  ... 
doi:10.1007/s42979-020-00234-8 fatcat:tyowypduvrczrpieyhh2wycsau

Generative Adversarial Networks: A Literature Review

2020 KSII Transactions on Internet and Information Systems  
Finally, drawing on the reviewed literature, we provide a broader outlook of this research direction.  ...  Along with the idea of "generative" and "adversarial", researchers are trying to apply Generative Adversarial Networks to the security field.  ...  Under GAN framework, RL method based on strategy gradient is still adopted, which greatly improves the performance of information retrieval.  ... 
doi:10.3837/tiis.2020.12.001 fatcat:yvafa3j5ofdkbdp7xblxegxlpy

Multimedia Security Situation Prediction Based on Optimization of Radial Basis Function Neural Network Algorithm

Gan Chen, Qiangyi Li
2022 Computational Intelligence and Neuroscience  
Aiming at the problem of prediction accuracy in network situation awareness, a network security situation prediction method based on a generalized radial basis function (RBF) neural network is proposed  ...  Simulation experiments show that this method can obtain situation prediction results more accurately and improve the active security protection of network security.  ...  Some research results have been made in the field of network security situation prediction at home and abroad.  ... 
doi:10.1155/2022/6314262 pmid:35432511 pmcid:PMC9012625 fatcat:mcwxdlkgwbbo5kvlsu6yngg2h4

Data augmentation through multivariate scenario forecasting in Data Centers using Generative Adversarial Networks [article]

Jaime Pérez, Patricia Arroba, José M. Moya
2022 arXiv   pre-print
For this purpose, we will implement a powerful generative algorithm: Generative Adversarial Networks (GANs).  ...  This paper proposes a time-series data augmentation methodology based on synthetic scenario forecasting within the Data Center.  ...  Methodology Implemented GAN Training Improvements In the following, we describe the GAN training improvements found in the literature that have been implemented for this research.  ... 
arXiv:2201.06147v2 fatcat:tbeoxnmqnfhvbjtxiouemnaede

AE-CGAN Model based High Performance Network Intrusion Detection System

JooHwa Lee, KeeHyun Park
2019 Applied Sciences  
In this paper, a high-performance network intrusion detection system based on deep learning is proposed for situations in which there are significant imbalances between normal and abnormal traffic.  ...  Based on the unsupervised learning models autoencoder (AE) and the generative adversarial networks (GAN) model during deep learning, the study aim is to solve the imbalance of data and intrusion detection  ...  We used GAN to solve the data imbalance, and the above research differed in that it developed the IDS by making malicious data based on GAN.  ... 
doi:10.3390/app9204221 fatcat:b7xszqyzy5cwnnztjf2tdo4o7y

Learning-based Intrusion Detection System for On-Board Vehicle Communication

Tobia Fiorese, Pietro Montino
2021 Italian Conference on Cybersecurity  
The second includes a discriminator that has been trained exploiting the Generative Adversarial Network (GAN) paradigm, to distinguish among the attack-free situation and an anomalous situation.  ...  Since the introduction of many external interfaces in modern vehicles exposes users to the risk of cyber-attacks, the need of focus on security is concrete.  ...  A CAN packet is broadcasted to the entire network, and only some ECUs will process the packet based on the ID received.  ... 
dblp:conf/itasec/FioreseM21 fatcat:tvz6wn5c4jc5pe3gjv3zgvj6gq

Spectrum of Advancements and Developments in Multidisciplinary Domains for Generative Adversarial Networks (GANs)

Syed Khurram Jah Rizvi, Muhammad Ajmal Azad, Muhammad Moazam Fraz
2021 Archives of Computational Methods in Engineering  
The survey paper summarizes the recent applications and developments in the domain of Generative Adversarial Networks (GANs) i.e. a back propagation based neural network architecture for generative modeling  ...  GANs is one of the most highlighted research avenue due to its synthetic data generation capabilities and benefits of representations comprehended irrespective of the application.  ...  Acknowledgements The authors would like to express their gratitude for the institutional support and research grant of Higher Education Commission (HEC) of Pakistan under International Research Support  ... 
doi:10.1007/s11831-021-09543-4 pmid:33824572 pmcid:PMC8017345 fatcat:efjw24635vdlbgj26bezu4y5sq

Dazzle: Using Optimized Generative Adversarial Networks to Address Security Data Class Imbalance Issue [article]

Rui Shu, Tianpei Xia, Laurie Williams, Tim Menzies
2022 arXiv   pre-print
Conclusion: Based on this study, we would suggest the use of optimized GANs as an alternative method for security vulnerability data class imbalanced issues.  ...  Goal: To help security practitioners address software security data class imbalanced issues and further help build better prediction models with resampled datasets.  ...  We recommend using optimized GANs for security vulnerability dataset class rebalancing purposes based on this study.  ... 
arXiv:2203.11410v2 fatcat:nyt3w6g7r5goxntayoux4wwusq

Network-Simulated Generation of Human Faces with Expressions and Orientations for Deep Learning Classification

network (WGAN) is presented.  ...  The application using ResNet-50 and RetinaNet as a pre-model for the prediction and detection of the human faces revealed a rapid prediction time and accuracy during the assessment test.  ...  Synthetic-image-based Deep Learning method For predicting human faces, the ResNet50 pre-model by Microsoft Research is used [21], which exhibits a rapid prediction time and high accuracy.  ... 
doi:10.35940/ijitee.b7491.129219 fatcat:qegapcmrbfbd3jkxrxmil7oble

Deep Learning-Based Solutions for 5G Network and 5G-Enabled Internet of Vehicles: Advances, Meta-Data Analysis, and Future Direction

Mubarak S. Almutairi, Akif Akgul
2022 Mathematical Problems in Engineering  
The deep learning algorithm solutions for security, energy, resource management, 5G-enabled IoV, and mobile network in 5G communication systems were presented including several other applications.  ...  However, it prompted new challenges on the 5G network cybersecurity defense system, resource management, energy, cache, and mobile network, therefore making the existing approaches obsolete to tackle the  ...  [84] predicted next packet time based on traffic trace using LSTM. e LSTM predicts the dynamic sleep time in discontinuous reception in 5G networks. It is found to improve power savings. Chen et al  ... 
doi:10.1155/2022/6855435 fatcat:i2rzrbvt4bbwpgebuwhisgilyu

Generative Adversarial Networks (GANs) in networking: A comprehensive survey & evaluation

Hojjat Navidan, Parisa Fard Moshiri, Mohammad Nabati, Reza Shahbazian, Seyed Ali Ghorashi, Vahid Shah-Mansouri, David Windridge
2021 Computer Networks  
Given their relative ease of use, it is therefore natural that researchers in the field of networking (which has seen extensive application of deep learning methods) should take an interest in GAN-based  ...  Despite the recency of their conception, Generative Adversarial Networks (GANs) constitute an extensively researched machine learning sub-field for the creation of synthetic data through deep generative  ...  [80] proposed Tran-GAN, a GAN-based transfer learning method for social tie prediction that seeks to uncover latent information in social networks.  ... 
doi:10.1016/j.comnet.2021.108149 fatcat:4ekgil24ijha3evmzruez63tdq

ICISCAE 2019 Table of Contents

2019 2019 2nd International Conference on Information Systems and Computer Aided Education (ICISCAE)  
Traffic Prediction Model Based on Neural Network Jianyong Fan, Dejun Mu, Yang Liu 554 IS284 Research and Design of Key Management System in Power Distribution Network Based on Quantum Private Communication  ...  Neural Network Fault Diagnosis Based on UKF Algorithm for Sallen-Key Bandpass Filter Circuit Xusheng Gan, Jingjuan Sun, Shuangfeng Li IS292 The Method of Thread Defect Detection Based on Machine Vision  ... 
doi:10.1109/iciscae48440.2019.9075543 fatcat:hwdx6lgqebdytdxphw562s465e

Behavior Prediction of Traffic Actors for Intelligent Vehicle using Artificial Intelligence Techniques: A Review

Suresh Kolekar, Shilpa Gite, Biswajeet Pradhan, Ketan Kotecha
2021 IEEE Access  
Minor misbehavior of these vehicles on the busy roads may lead to an accident. Due to this, there is a need for vehicle behavior research work in today's era.  ...  behavior prediction of surrounding traffic actors for secure and accurate intelligent vehicle navigation.  ...  Based on input representation, output type, and prediction model, various researchers have used different approaches.  ... 
doi:10.1109/access.2021.3116303 fatcat:spra4jjme5ezdpjhmn4uyptwva
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