A Comprehensive Study on Machine Learning Algorithms for Wireless Sensor Network Security
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[1] Jitender Grover,et al. Security issues in Wireless Sensor Network — A review , 2016, 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO).
[2] Hong-Tzer Yang,et al. Load Identification in Neural Networks for a Non-intrusive Monitoring of Industrial Electrical Loads , 2007, CSCWD.
[3] Mariano García Otero,et al. Detection of wormhole attacks in wireless sensor networks using range-free localization , 2012, 2012 IEEE 17th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD).
[4] Tao Liu,et al. Data-driven link quality prediction using link features , 2014, TOSN.
[5] D.M. Mount,et al. An Efficient k-Means Clustering Algorithm: Analysis and Implementation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[6] Jean Hennebert,et al. A Survey on Intrusive Load Monitoring for Appliance Recognition , 2014, 2014 22nd International Conference on Pattern Recognition.
[7] Ran Wolff,et al. Noname manuscript No. (will be inserted by the editor) In-Network Outlier Detection in Wireless Sensor Networks , 2022 .
[8] Mohsen Guizani,et al. Machine learning in the Internet of Things: Designed techniques for smart cities , 2019, Future Gener. Comput. Syst..
[9] Kalaiarasi Sonai Muthu,et al. Classification Algorithms in Human Activity Recognition using Smartphones , 2012 .
[10] John Langford,et al. Agnostic Active Learning Without Constraints , 2010, NIPS.
[11] Yong Wang,et al. Predicting link quality using supervised learning in wireless sensor networks , 2007, MOCO.
[12] Wang Ke,et al. Attribute-based clustering for information dissemination in wireless sensor networks , 2005, 2005 Second Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2005. IEEE SECON 2005..
[13] Richard Demo Souza,et al. A Survey of Machine Learning Techniques Applied to Self-Organizing Cellular Networks , 2017, IEEE Communications Surveys & Tutorials.
[14] Cyrus Shahabi,et al. The Clustered AGgregation (CAG) technique leveraging spatial and temporal correlations in wireless sensor networks , 2007, TOSN.
[15] Majid Alotaibi. Security to wireless sensor networks against malicious attacks using Hamming residue method , 2019, EURASIP J. Wirel. Commun. Netw..
[16] Yusheng Ji,et al. An Area-Based Approach for Node Replica Detection in Wireless Sensor Networks , 2012, 2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications.
[17] Ian H. Witten,et al. Data mining: practical machine learning tools and techniques with Java implementations , 2002, SGMD.
[18] Demis Hassabis,et al. Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm , 2017, ArXiv.
[19] Sanju Islam,et al. A Secure Framework for IoT Smart Home by Resolving Session Hijacking , 2020 .
[20] Qi Hao,et al. Deep Learning for Intelligent Wireless Networks: A Comprehensive Survey , 2018, IEEE Communications Surveys & Tutorials.
[21] Robert H. Deng,et al. Detecting node replication attacks in mobile sensor networks: theory and approaches , 2012, Secur. Commun. Networks.
[22] Walid Saad,et al. Learning How to Communicate in the Internet of Things: Finite Resources and Heterogeneity , 2016, IEEE Access.
[23] Davide Brunelli,et al. Wireless Sensor Networks , 2012, Lecture Notes in Computer Science.
[24] Xiaofan Li,et al. A Survey on Deep Learning Techniques in Wireless Signal Recognition , 2019, Wirel. Commun. Mob. Comput..
[25] Anastasios A. Economides,et al. Detecting Sybil attacks in wireless sensor networks using UWB ranging-based information , 2015, Expert Syst. Appl..
[26] Y.A. Sekercioglu,et al. Detecting Selective Forwarding Attacks in Wireless Sensor Networks using Support Vector Machines , 2007, 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information.
[27] Steve Hanneke,et al. Theory of Disagreement-Based Active Learning , 2014, Found. Trends Mach. Learn..
[28] Duc A. Tran,et al. Localization In Wireless Sensor Networks Based on Support Vector Machines , 2008, IEEE Transactions on Parallel and Distributed Systems.
[29] João B. Martins,et al. An approach to localization scheme of wireless sensor networks based on artificial neural networks and Genetic Algorithms , 2012, 10th IEEE International NEWCAS Conference.
[30] Qiuwei Yang,et al. Survey of Security Technologies on Wireless Sensor Networks , 2015, J. Sensors.
[31] Carey L. Williamson,et al. Offline/realtime traffic classification using semi-supervised learning , 2007, Perform. Evaluation.
[32] Mehmet Demirci,et al. A Review of Machine Learning Solutions to Denial-of-Services Attacks in Wireless Sensor Networks , 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).
[33] Yifeng Zhu,et al. Localization using neural networks in wireless sensor networks , 2008, MOBILWARE.
[34] David Silver,et al. Deep Reinforcement Learning with Double Q-Learning , 2015, AAAI.
[35] Ursula Challita,et al. Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial , 2017, IEEE Communications Surveys & Tutorials.
[36] Antonio Liotta,et al. Ensembles of incremental learners to detect anomalies in ad hoc sensor networks , 2015, Ad Hoc Networks.
[37] Erkki Mäkinen,et al. A Neural Network Model to Minimize the Connected Dominating Set for Self-Configuration of Wireless Sensor Networks , 2009, IEEE Transactions on Neural Networks.
[38] Mingxuan Sun,et al. Intelligent wireless communications enabled by cognitive radio and machine learning , 2017, China Communications.
[39] Timothy J. O'Shea,et al. Semi-supervised radio signal identification , 2016, 2017 19th International Conference on Advanced Communication Technology (ICACT).
[40] Carlos León,et al. Giving neurons to sensors. QoS management in wireless sensors networks. , 2006, 2006 IEEE Conference on Emerging Technologies and Factory Automation.
[41] Yi Min Zhou,et al. A Trust-Aware and Location-Based Secure Routing Protocol for WSN , 2013, ICRA 2013.
[42] Anis Koubaa,et al. Radio Link Quality Estimation in Low-Power Wireless Networks , 2013, Springer Briefs in Electrical and Computer Engineering.
[43] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[44] Miguel A. Labrador,et al. A Survey on Human Activity Recognition using Wearable Sensors , 2013, IEEE Communications Surveys & Tutorials.
[45] Ying-Chang Liang,et al. Applications of Deep Reinforcement Learning in Communications and Networking: A Survey , 2018, IEEE Communications Surveys & Tutorials.
[46] Ingrid Moerman,et al. A survey on Machine Learning-based Performance Improvement of Wireless Networks: PHY, MAC and Network layer , 2020, Electronics.
[47] Mohsen Guizani,et al. Deep Learning for IoT Big Data and Streaming Analytics: A Survey , 2017, IEEE Communications Surveys & Tutorials.
[48] Yingshu Li,et al. Real time clustering of sensory data in wireless sensor networks , 2009, 2009 IEEE 28th International Performance Computing and Communications Conference.
[49] Yong Guan,et al. Lightweight Location Verification Algorithms for Wireless Sensor Networks , 2013, IEEE Transactions on Parallel and Distributed Systems.
[50] Nirvana Meratnia,et al. Adaptive and Online One-Class Support Vector Machine-Based Outlier Detection Techniques for Wireless Sensor Networks , 2009, 2009 International Conference on Advanced Information Networking and Applications Workshops.
[51] Diana Bohm,et al. Computer And Information Security Handbook , 2016 .