Intrusion detection methods based on integrated deep learning model

[1]  Saumendra Sengupta,et al.  Hybrid Intrusion Detection System Using Machine Learning Techniques in Cloud Computing Environments , 2019, 2019 IEEE 17th International Conference on Software Engineering Research, Management and Applications (SERA).

[2]  Gürsel Serpen,et al.  Host-based misuse intrusion detection using PCA feature extraction and kNN classification algorithms , 2018, Intell. Data Anal..

[3]  Mounir Ghogho,et al.  Deep learning approach for Network Intrusion Detection in Software Defined Networking , 2016, 2016 International Conference on Wireless Networks and Mobile Communications (WINCOM).

[4]  Muttukrishnan Rajarajan,et al.  Host-Based Intrusion Detection for VANETs: A Statistical Approach to Rogue Node Detection , 2016, IEEE Transactions on Vehicular Technology.

[5]  Naiqi Wu,et al.  SVM-DT-based adaptive and collaborative intrusion detection , 2018, IEEE/CAA Journal of Automatica Sinica.

[6]  Richard A. Kemmerer,et al.  State Transition Analysis: A Rule-Based Intrusion Detection Approach , 1995, IEEE Trans. Software Eng..

[7]  Qi Shi,et al.  A Deep Learning Approach to Network Intrusion Detection , 2018, IEEE Transactions on Emerging Topics in Computational Intelligence.

[8]  Anazida Zainal,et al.  A Model for Adaptive and Distributed Intrusion Detection for Cloud Computing , 2018, 2018 Seventh ICT International Student Project Conference (ICT-ISPC).

[9]  Daniel Rosa Canêdo Canêdo,et al.  Intrusion Detection System in Ad Hoc Networks with Artificial Neural Networks and Algorithm K-Means , 2019, IEEE Latin America Transactions.

[10]  Shaoguo Wen,et al.  NOMA Codebook Optimization by Batch Gradient Descent , 2019, IEEE Access.

[11]  Dezhi Han,et al.  Design of intrusion detection system based on improved ABC_elite and BP neural networks , 2019, Comput. Sci. Inf. Syst..

[12]  Majid Sarrafzadeh,et al.  Dynamic Feature Acquisition Using Denoising Autoencoders , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[13]  Umi Kalsom Yusof,et al.  Filter-Based Multi-Objective Feature Selection Using NSGA III and Cuckoo Optimization Algorithm , 2020, IEEE Access.

[14]  Na Wang,et al.  Building a Cloud IDS Using an Efficient Feature Selection Method and SVM , 2019, IEEE Access.

[15]  Han Yu,et al.  Research on Network Intrusion Detection Based on Support Vector Machine Optimized with Grasshopper Optimization Algorithm , 2019, 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS).

[16]  Cheng Wu,et al.  Semi-Supervised and Unsupervised Extreme Learning Machines , 2014, IEEE Transactions on Cybernetics.

[17]  Ehsan Namjoo,et al.  LR-HIDS: logistic regression host-based intrusion detection system for cloud environments , 2018, Journal of Ambient Intelligence and Humanized Computing.

[18]  Xuewen Xia,et al.  Efficient Feature Selection Algorithm Based on Particle Swarm Optimization With Learning Memory , 2019, IEEE Access.

[19]  Jon Atli Benediktsson,et al.  Feature Selection Based on Hybridization of Genetic Algorithm and Particle Swarm Optimization , 2015, IEEE Geoscience and Remote Sensing Letters.

[20]  Shiyong Cui,et al.  A Comparative Study of Bag-of-Words and Bag-of-Topics Models of EO Image Patches , 2015, IEEE Geoscience and Remote Sensing Letters.

[21]  Pascal Vincent,et al.  Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  S. Mercy Shalinie,et al.  Design of cognitive fog computing for intrusion detection in Internet of Things , 2018, Journal of Communications and Networks.

[23]  Pierre-Francois Marteau,et al.  Sequence Covering for Efficient Host-Based Intrusion Detection , 2017, IEEE Transactions on Information Forensics and Security.

[24]  C. L. Philip Chen,et al.  Fuzzy Restricted Boltzmann Machine for the Enhancement of Deep Learning , 2015, IEEE Transactions on Fuzzy Systems.

[25]  Seyedali Mirjalili,et al.  Binary Multi-Objective Grey Wolf Optimizer for Feature Selection in Classification , 2020, IEEE Access.

[26]  Georges Kaddoum,et al.  Intrusion Detection for Cyber–Physical Systems Using Generative Adversarial Networks in Fog Environment , 2020, IEEE Internet of Things Journal.

[27]  Kiseon Kim,et al.  Genetic convolutional neural network for intrusion detection systems , 2020, Future Gener. Comput. Syst..

[28]  Jabeen Sultana,et al.  Intrusion Detection Based on Autoencoder and Isolation Forest in Fog Computing , 2020, IEEE Access.

[29]  Yaxi Liu,et al.  An Efficient Stochastic Gradient Descent Algorithm to Maximize the Coverage of Cellular Networks , 2019, IEEE Transactions on Wireless Communications.

[30]  Hyejeong Hong,et al.  A memory-efficient parallel string matching for intrusion detection systems , 2009, IEEE Communications Letters.

[31]  Hongbin Yu,et al.  Feature Extraction and Analysis of Natural Language Processing for Deep Learning English Language , 2020, IEEE Access.

[32]  Arun Kumar Sangaiah,et al.  A real-time and ubiquitous network attack detection based on deep belief network and support vector machine , 2020, IEEE/CAA Journal of Automatica Sinica.

[33]  Jin Liu,et al.  Applications of deep learning to MRI images: A survey , 2018, Big Data Min. Anal..

[34]  Jun Du,et al.  Speech Enhancement Based on Teacher–Student Deep Learning Using Improved Speech Presence Probability for Noise-Robust Speech Recognition , 2019, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[35]  Yu Lasheng,et al.  Deep Learning Approach Combining Sparse Autoencoder With SVM for Network Intrusion Detection , 2018, IEEE Access.

[36]  Marc Frappier,et al.  Intrusion Detection Systems: A Cross-Domain Overview , 2019, IEEE Communications Surveys & Tutorials.

[37]  Stefan C. Kremer,et al.  Network intrusion detection system based on recursive feature addition and bigram technique , 2018, Comput. Secur..

[38]  Yee Whye Teh,et al.  A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.

[39]  Geoffrey E. Hinton.  Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.

[40]  Jiasong Wu,et al.  Quaternion softmax classifier , 2014 .

[41]  S Messaoud,et al.  Online GMM Clustering and Mini-Batch Gradient Descent Based Optimization for Industrial IoT 4.0 , 2020, IEEE Transactions on Industrial Informatics.

[42]  J. Rene Beulah,et al.  A Hybrid Feature Selection Method for Improved Detection of Wired/Wireless Network Intrusions , 2017, Wireless personal communications.

[43]  Albert Y. Zomaya,et al.  An Industrial Network Intrusion Detection Algorithm Based on Multifeature Data Clustering Optimization Model , 2020, IEEE Transactions on Industrial Informatics.