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[1] George C. Hadjichristofi,et al. Internet of Things: Security vulnerabilities and challenges , 2015, 2015 IEEE Symposium on Computers and Communication (ISCC).
[2] Yue Zhang,et al. APPA: An anonymous and privacy preserving data aggregation scheme for fog-enhanced IoT , 2019, J. Netw. Comput. Appl..
[3] Zilong Ye,et al. Secure the internet of things with challenge response authentication in fog computing , 2017, 2017 IEEE 36th International Performance Computing and Communications Conference (IPCCC).
[4] Jie Gu,et al. An effective intrusion detection framework based on SVM with feature augmentation , 2017, Knowl. Based Syst..
[5] Jiming Chen,et al. Smart community: an internet of things application , 2011, IEEE Communications Magazine.
[6] H. Vincent Poor,et al. Mobile offloading game against smart attacks , 2016, 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).
[7] Ran Wolff,et al. Noname manuscript No. (will be inserted by the editor) In-Network Outlier Detection in Wireless Sensor Networks , 2022 .
[8] Lalu Banoth,et al. A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection , 2017 .
[9] Muttukrishnan Rajarajan,et al. A survey of intrusion detection techniques in Cloud , 2013, J. Netw. Comput. Appl..
[10] Ning Wang,et al. Physical-Layer Authentication Based on Extreme Learning Machine , 2017, IEEE Communications Letters.
[11] Hwee Pink Tan,et al. Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications , 2014, IEEE Communications Surveys & Tutorials.
[12] Dechang Pi,et al. A Novel Kernel SVM Algorithm with Game Theory for Network Intrusion Detection , 2017, KSII Trans. Internet Inf. Syst..
[13] Jiankun Hu,et al. A novel statistical technique for intrusion detection systems , 2018, Future Gener. Comput. Syst..
[14] Erdogan Dogdu,et al. Context-Aware Computing, Learning, and Big Data in Internet of Things: A Survey , 2018, IEEE Internet of Things Journal.
[15] Miguel López-Benítez,et al. Prototype for multidisciplinary research in the context of the Internet of Things , 2017, J. Netw. Comput. Appl..
[16] Hannu Tenhunen,et al. International Conference on Ambient Systems , Networks and Technologies ( ANT 2015 ) SEA : A Secure and E ffi cient Authentication and Authorization Architecture for IoT-Based Healthcare Using Smart Gateways , 2015 .
[17] Manuel Díaz,et al. State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing , 2016, J. Netw. Comput. Appl..
[18] Abdolreza Mirzaei,et al. Intrusion detection using fuzzy association rules , 2009, Appl. Soft Comput..
[19] Igor Kotenko,et al. Neural network approach to forecast the state of the Internet of Things elements , 2015, 2015 XVIII International Conference on Soft Computing and Measurements (SCM).
[20] Tommaso Melodia,et al. Securing the Internet of Things in the Age of Machine Learning and Software-Defined Networking , 2018, IEEE Internet of Things Journal.
[21] Hadis Karimipour,et al. Robust Massively Parallel Dynamic State Estimation of Power Systems Against Cyber-Attack , 2018, IEEE Access.
[22] Heena Rathore,et al. Bio-inspired machine learning based Wireless Sensor Network security , 2013, 2013 World Congress on Nature and Biologically Inspired Computing.
[23] Amutha Prabakar Muniyandi,et al. Network Anomaly Detection by Cascading K-Means Clustering and C4.5 Decision Tree algorithm , 2012 .
[24] Bing Liu,et al. Lifelong Learning for Sentiment Classification , 2015, ACL.
[25] Lixiang Li,et al. Nearest neighbors based density peaks approach to intrusion detection , 2018 .
[26] Ali Dehghantanha,et al. Fuzzy pattern tree for edge malware detection and categorization in IoT , 2019, J. Syst. Archit..
[27] Yong Bai,et al. The Anonymization Protection Algorithm Based on Fuzzy Clustering for the Ego of Data in the Internet of Things , 2017, J. Electr. Comput. Eng..
[28] Zhu Han,et al. PHY-Layer Authentication With Multiple Landmarks With Reduced Overhead , 2018, IEEE Transactions on Wireless Communications.
[29] Neelam Sharma,et al. INTRUSION DETECTION USING NAIVE BAYES CLASSIFIER WITH FEATURE REDUCTION , 2012 .
[30] Hadis Karimipour,et al. Cyber intrusion detection by combined feature selection algorithm , 2019, J. Inf. Secur. Appl..
[31] Xuemin Shen,et al. Channel-Based Sybil Detection in Industrial Wireless Sensor Networks: A Multi-Kernel Approach , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.
[32] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[33] Rui Zhang,et al. Detecting Poisoning Attacks on Machine Learning in IoT Environments , 2018, 2018 IEEE International Congress on Internet of Things (ICIOT).
[34] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[35] Ayushi Gupta,et al. Survey on Machine Learning based scheduling in Cloud Computing , 2017, ISMSI '17.
[36] V. J. Jincy,et al. Classification Mechanism for IoT Devices towards Creating a Security Framework , 2014, ISI.
[37] Liang Xiao,et al. IoT Security Techniques Based on Machine Learning: How Do IoT Devices Use AI to Enhance Security? , 2018, IEEE Signal Processing Magazine.
[38] Soo-Mook Moon,et al. Work-in-progress: cloud-based machine learning for IoT devices with better privacy , 2017, 2017 International Conference on Embedded Software (EMSOFT).
[39] Ming-Yang Su,et al. Real-time anomaly detection systems for Denial-of-Service attacks by weighted k-nearest-neighbor classifiers , 2011, Expert Syst. Appl..
[40] Heng Tao Shen,et al. Principal Component Analysis , 2009, Encyclopedia of Biometrics.
[41] Flavio Esposito,et al. Stochastic delay forecasts for edge traffic engineering via Bayesian Networks , 2017, 2017 IEEE 16th International Symposium on Network Computing and Applications (NCA).
[42] Ali Feizollah,et al. Evaluation of machine learning classifiers for mobile malware detection , 2014, Soft Computing.
[43] Soma Bandyopadhyay,et al. IoT-Privacy: To be private or not to be private , 2014, 2014 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).
[44] Manas Ranjan Patra,et al. NETWORK INTRUSION DETECTION USING NAÏVE BAYES , 2007 .
[45] Cristina Alcaraz,et al. Analysis of Security Threats, Requirements, Technologies and Standards in Wireless Sensor Networks , 2009, FOSAD.
[46] Junaid Qadir,et al. Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges , 2017, IEEE Access.
[47] Athanasios V. Vasilakos,et al. Security of the Internet of Things: perspectives and challenges , 2014, Wireless Networks.
[48] Smruti R. Sarangi,et al. Internet of Things: Architectures, Protocols, and Applications , 2017, J. Electr. Comput. Eng..
[49] Athanasios V. Vasilakos,et al. Data Mining for the Internet of Things: Literature Review and Challenges , 2015, Int. J. Distributed Sens. Networks.
[50] Liang Xiao,et al. Cloud-Based Malware Detection Game for Mobile Devices with Offloading , 2017, IEEE Transactions on Mobile Computing.
[51] Soma Bandyopadhyay,et al. Why not keep your personal data secure yet private in IoT?: Our lightweight approach , 2015, 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).
[52] Walaa Hamouda,et al. A Critical Review of Practices and Challenges in Intrusion Detection Systems for IoT: Toward Universal and Resilient Systems , 2018, IEEE Communications Surveys & Tutorials.
[53] Henry Leung,et al. Intelligent Anomaly Detection for Large-scale Smart Grids , 2019, 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE).
[54] Georg Carle,et al. Traffic Anomaly Detection Using K-Means Clustering , 2007 .
[55] Antonio Liotta,et al. Ensembles of incremental learners to detect anomalies in ad hoc sensor networks , 2015, Ad Hoc Networks.
[56] Olivier Markowitch,et al. A machine learning approach against a masked AES , 2014, Journal of Cryptographic Engineering.
[57] Albert Y. Zomaya,et al. A Dimension Reduction Model and Classifier for Anomaly-Based Intrusion Detection in Internet of Things , 2017, 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech).
[58] Sotiris B. Kotsiantis,et al. Decision trees: a recent overview , 2011, Artificial Intelligence Review.
[59] Siome Goldenstein,et al. An approach to the correlation of security events based on machine learning techniques , 2013, Journal of Internet Services and Applications.
[60] Kathleen Goeschel,et al. Reducing false positives in intrusion detection systems using data-mining techniques utilizing support vector machines, decision trees, and naive Bayes for off-line analysis , 2016, SoutheastCon 2016.
[61] Petros Spachos,et al. Microlocation for Smart Buildings in the Era of the Internet of Things: A Survey of Technologies, Techniques, and Approaches , 2018, IEEE Signal Processing Magazine.
[62] Daihee Park,et al. Traffic flooding attack detection with SNMP MIB using SVM , 2008, Comput. Commun..
[63] Venkata Dinavahi,et al. On false data injection attack against dynamic state estimation on smart power grids , 2017, 2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE).
[64] Kevin Ashton,et al. That ‘Internet of Things’ Thing , 1999 .
[65] Paul Mühlethaler,et al. A Lightweight Forwarding Strategy for Named Data Networking in Low-end IoT , 2019, J. Netw. Comput. Appl..
[66] Yiwei Thomas Hou,et al. Proximity-Based Security Techniques for Mobile Users in Wireless Networks , 2013, IEEE Transactions on Information Forensics and Security.
[67] Sushmita Ruj,et al. A Comprehensive Survey on Attacks, Security Issues and Blockchain Solutions for IoT and IIoT , 2020, J. Netw. Comput. Appl..
[68] H. Vincent Poor,et al. Two-dimensional anti-jamming communication based on deep reinforcement learning , 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[69] Henry Leung,et al. A Deep and Scalable Unsupervised Machine Learning System for Cyber-Attack Detection in Large-Scale Smart Grids , 2019, IEEE Access.
[70] Ong Bi Lynn,et al. Internet of Things (IoT): Taxonomy of security attacks , 2016, 2016 3rd International Conference on Electronic Design (ICED).
[71] Andrew P. Bradley,et al. The use of the area under the ROC curve in the evaluation of machine learning algorithms , 1997, Pattern Recognit..
[72] ZhangShichao,et al. Efficient kNN classification algorithm for big data , 2016 .
[73] Rashid Mehmood,et al. Data Fusion and IoT for Smart Ubiquitous Environments: A Survey , 2017, IEEE Access.
[74] Hongbo Liu,et al. Smart User Authentication through Actuation of Daily Activities Leveraging WiFi-enabled IoT , 2017, MobiHoc.
[75] Zhi Chen,et al. A lightweight attribute-based encryption scheme for the Internet of Things , 2015, Future Gener. Comput. Syst..
[76] Mazliza Othman,et al. Internet of Things security: A survey , 2017, J. Netw. Comput. Appl..
[77] Wei Li,et al. Network Intrusion Detection Based on Random Forest and Support Vector Machine , 2017, 22017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC).
[78] Khair Eddin Sabri,et al. Hierarchical architecture and protocol for mobile object authentication in the context of IoT smart cities , 2018, J. Netw. Comput. Appl..
[79] Lars Bauer,et al. From Cloud Down to Things: An Overview of Machine Learning in Internet of Things , 2019, IEEE Internet of Things Journal.
[80] Muhammad Khurram Khan,et al. Trust and reputation for Internet of Things: Fundamentals, taxonomy, and open research challenges , 2019, J. Netw. Comput. Appl..
[81] Lan Wang,et al. Securing wireless implantable devices for healthcare: Ideas and challenges , 2009, IEEE Communications Magazine.
[82] Kwangjo Kim,et al. Improving Detection of Wi-Fi Impersonation by Fully Unsupervised Deep Learning , 2017, WISA.
[83] Wei-Yang Lin,et al. Intrusion detection by machine learning: A review , 2009, Expert Syst. Appl..
[84] Markus Jakobsson,et al. Implicit Authentication through Learning User Behavior , 2010, ISC.
[85] Lida Xu,et al. The internet of things: a survey , 2014, Information Systems Frontiers.
[86] Arun Kumar Sangaiah,et al. Performance evaluation of IoT middleware , 2018, J. Netw. Comput. Appl..
[87] Myung-Sup Kim,et al. Traffic Flooding Attack Detection on SNMP MIB Using SVM , 2008 .
[88] Marimuthu Palaniswami,et al. Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..
[89] Paul Jones,et al. Secrets and Lies: Digital Security in a Networked World , 2002 .
[90] Lianbing Deng,et al. Mobile network intrusion detection for IoT system based on transfer learning algorithm , 2018, Cluster Computing.
[91] Ali Dehghantanha,et al. A survey on internet of things security: Requirements, challenges, and solutions , 2019, Internet Things.
[92] Rodrigo Roman,et al. Securing the Internet of Things , 2017, Smart Cards, Tokens, Security and Applications, 2nd Ed..
[93] Simon A. Dobson,et al. Adaptive middleware for autonomic systems , 2006, Ann. des Télécommunications.
[94] Mamun Bin Ibne Reaz,et al. A novel SVM-kNN-PSO ensemble method for intrusion detection system , 2016, Appl. Soft Comput..
[95] Do Van Thanh,et al. Strengthening Mobile Network Security Using Machine Learning , 2016, MobiWIS.
[96] Gisung Kim,et al. A novel hybrid intrusion detection method integrating anomaly detection with misuse detection , 2014, Expert Syst. Appl..
[97] M. A. Jabbar,et al. Random Forest Modeling for Network Intrusion Detection System , 2016 .
[98] Dana Kulic,et al. Data augmentation of wearable sensor data for parkinson’s disease monitoring using convolutional neural networks , 2017, ICMI.
[99] B. B. Zaidan,et al. A review of smart home applications based on Internet of Things , 2017, J. Netw. Comput. Appl..
[100] Sotiris B. Kotsiantis,et al. Supervised Machine Learning: A Review of Classification Techniques , 2007, Informatica.
[101] D. R. Cutler,et al. Utah State University From the SelectedWorks of , 2017 .
[102] Hanan Elazhary,et al. Internet of Things (IoT), mobile cloud, cloudlet, mobile IoT, IoT cloud, fog, mobile edge, and edge emerging computing paradigms: Disambiguation and research directions , 2019, J. Netw. Comput. Appl..
[103] Ahmad-Reza Sadeghi,et al. IoT SENTINEL: Automated Device-Type Identification for Security Enforcement in IoT , 2016, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS).
[104] Adi Shamir,et al. IoT Goes Nuclear: Creating a ZigBee Chain Reaction , 2017, 2017 IEEE Symposium on Security and Privacy (SP).
[105] Tao Jiang,et al. A Lightweight Authenticated Communication Scheme for Smart Grid , 2016, IEEE Sensors Journal.
[106] Myung-Sup Kim,et al. Linear SVM-Based Android Malware Detection for Reliable IoT Services , 2014, J. Appl. Math..
[107] Yuval Elovici,et al. ProfilIoT: a machine learning approach for IoT device identification based on network traffic analysis , 2017, SAC.
[108] G. Priya,et al. EFFICIENT KNN CLASSIFICATION ALGORITHM FOR BIG DATA , 2017 .
[109] Dimitris Kanellopoulos,et al. Association Rules Mining: A Recent Overview , 2006 .
[110] Peng Wang,et al. AsDroid: detecting stealthy behaviors in Android applications by user interface and program behavior contradiction , 2014, ICSE.
[111] Michael I. Jordan,et al. Machine learning: Trends, perspectives, and prospects , 2015, Science.
[112] Shusen Yang,et al. A survey on the ietf protocol suite for the internet of things: standards, challenges, and opportunities , 2013, IEEE Wireless Communications.
[113] Shu Yang,et al. A survey on application of machine learning for Internet of Things , 2018, International Journal of Machine Learning and Cybernetics.
[114] Ling Shi,et al. SINR-Based DoS Attack on Remote State Estimation: A Game-Theoretic Approach , 2017, IEEE Transactions on Control of Network Systems.
[115] Sanjay Ghemawat,et al. MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.
[116] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[117] Anil K. Jain. Data clustering: 50 years beyond K-means , 2008, Pattern Recognit. Lett..
[118] Roman Beck,et al. Does Cloud Computing Matter? An Analysis of the Cloud Model Software-as-a-Service and Its Impact on Operational Agility , 2013, 2013 46th Hawaii International Conference on System Sciences.
[119] D.R. Hush,et al. Progress in supervised neural networks , 1993, IEEE Signal Processing Magazine.
[120] Sudharman K. Jayaweera,et al. A Survey on Machine-Learning Techniques in Cognitive Radios , 2013, IEEE Communications Surveys & Tutorials.
[121] Weihua Zhuang,et al. PHY-Layer Spoofing Detection With Reinforcement Learning in Wireless Networks , 2016, IEEE Transactions on Vehicular Technology.
[122] Abhishek Singh,et al. A walkthrough of the emerging IoT paradigm: Visualizing inside functionalities, key features, and open issues , 2019, J. Netw. Comput. Appl..
[123] Yuval Elovici,et al. Detection of Unauthorized IoT Devices Using Machine Learning Techniques , 2017, ArXiv.
[124] Xiaolei Dong,et al. Security and Privacy for Cloud-Based IoT: Challenges , 2017, IEEE Communications Magazine.
[125] Roksana Boreli,et al. A Host-Based Intrusion Detection and Mitigation Framework for Smart Home IoT Using OpenFlow , 2016, 2016 11th International Conference on Availability, Reliability and Security (ARES).
[126] Elisa Bertino,et al. Botnets and Internet of Things Security , 2017, Computer.
[127] Rodrigo Roman,et al. On the features and challenges of security and privacy in distributed internet of things , 2013, Comput. Networks.
[128] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[129] Richard E. Overill,et al. Detection of known and unknown DDoS attacks using Artificial Neural Networks , 2016, Neurocomputing.
[130] Neminath Hubballi,et al. OCPAD: One class Naive Bayes classifier for payload based anomaly detection , 2016, Expert Syst. Appl..
[131] Alexandre X. Falcão,et al. Data clustering as an optimum‐path forest problem with applications in image analysis , 2009, Int. J. Imaging Syst. Technol..
[132] Xiangjian He,et al. A System for Denial-of-Service Attack Detection Based on Multivariate Correlation Analysis , 2014, IEEE Transactions on Parallel and Distributed Systems.
[133] Vangelis Gazis,et al. A Survey of Standards for Machine-to-Machine and the Internet of Things , 2017, IEEE Communications Surveys & Tutorials.
[134] Lemuria Carter,et al. literature review of RFID-enabled healthcare applications and issues amuel , 2013 .
[135] Randy H. Katz,et al. Above the Clouds: A Berkeley View of Cloud Computing , 2009 .
[136] Ying Wah Teh,et al. Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges , 2018, Expert Syst. Appl..
[137] Ganesh K. Venayagamoorthy,et al. Neural network based secure media access control protocol for wireless sensor networks , 2009, 2009 International Joint Conference on Neural Networks.
[138] Parvez Faruki,et al. Network Intrusion Detection for IoT Security Based on Learning Techniques , 2019, IEEE Communications Surveys & Tutorials.
[139] Amir Masoud Rahmani,et al. Service composition approaches in IoT: A systematic review , 2018, J. Netw. Comput. Appl..
[140] Ravi Sankar,et al. A Survey of Intrusion Detection Systems in Wireless Sensor Networks , 2014, IEEE Communications Surveys & Tutorials.
[141] Siobhán Clarke,et al. Middleware for Internet of Things: A Survey , 2016, IEEE Internet of Things Journal.
[142] Seetha Hari,et al. Learning From Imbalanced Data , 2019, Advances in Computer and Electrical Engineering.
[143] Tomasz Imielinski,et al. Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.
[144] Seyed Mojtaba Hosseini Bamakan,et al. An effective intrusion detection framework based on MCLP/SVM optimized by time-varying chaos particle swarm optimization , 2016, Neurocomputing.
[145] Haider Abbas,et al. Trust models of internet of smart things: A survey, open issues, and future directions , 2019, J. Netw. Comput. Appl..
[146] David Gil,et al. Internet of Things: A Review of Surveys Based on Context Aware Intelligent Services , 2016, Sensors.
[147] Tahir Mehmood,et al. Machine learning algorithms in context of intrusion detection , 2016, 2016 3rd International Conference on Computer and Information Sciences (ICCOINS).
[148] Sidi-Mohammed Senouci,et al. A lightweight anomaly detection technique for low-resource IoT devices: A game-theoretic methodology , 2016, 2016 IEEE International Conference on Communications (ICC).
[149] Chakib Bekara,et al. Security Issues and Challenges for the IoT-based Smart Grid , 2014, FNC/MobiSPC.
[150] Shrinath,et al. SECURITY FOR IoT SYSTEMS USING MACHINE LEARNING , 2018 .
[151] Sherali Zeadally,et al. Securing Internet of Things (IoT) with machine learning , 2019, Int. J. Commun. Syst..
[152] Tai-Myung Chung,et al. ProFiOt: Abnormal Behavior Profiling (ABP) of IoT devices based on a machine learning approach , 2017, 2017 27th International Telecommunication Networks and Applications Conference (ITNAC).
[153] Naveen K. Chilamkurti,et al. Distributed attack detection scheme using deep learning approach for Internet of Things , 2017, Future Gener. Comput. Syst..
[154] G. C. Tiao,et al. Bayesian inference in statistical analysis , 1973 .
[155] Ahmed Khattab,et al. Securing the Internet of Things and Wireless Sensor Networks via Machine Learning: A Survey , 2018, 2018 International Conference on Computer and Applications (ICCA).
[156] Athanasios V. Vasilakos,et al. The role of big data analytics in Internet of Things , 2017, Comput. Networks.
[157] Wei Ni,et al. Anatomy of Threats to the Internet of Things , 2019, IEEE Communications Surveys & Tutorials.
[158] Qiang He,et al. An IoT-Oriented data placement method with privacy preservation in cloud environment , 2018, J. Netw. Comput. Appl..
[159] Gaetano Marrocco,et al. RFID Technology for IoT-Based Personal Healthcare in Smart Spaces , 2014, IEEE Internet of Things Journal.
[160] Sushma Jain,et al. A survey towards an integration of big data analytics to big insights for value-creation , 2018, Inf. Process. Manag..
[161] Shan Suthaharan,et al. Big data classification: problems and challenges in network intrusion prediction with machine learning , 2014, PERV.
[162] Dimitrios Zissis,et al. Intelligent security on the edge of the cloud , 2017, 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC).
[163] Yu Yang,et al. Study and application on the architecture and key technologies for IOT , 2011, 2011 International Conference on Multimedia Technology.
[164] Peng Liu,et al. The Effect of IoT New Features on Security and Privacy: New Threats, Existing Solutions, and Challenges Yet to Be Solved , 2018, IEEE Internet of Things Journal.
[165] Geir M. Køien,et al. Cyber Security and the Internet of Things: Vulnerabilities, Threats, Intruders and Attacks , 2015, J. Cyber Secur. Mobil..
[166] Juan E. Tapiador,et al. Security and privacy issues in implantable medical devices: A comprehensive survey , 2015, J. Biomed. Informatics.
[167] Miao Wu,et al. Research on the architecture of Internet of Things , 2010, 2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE).
[168] Amr M. Youssef,et al. Security Tradeoffs in Cyber Physical Systems: A Case Study Survey on Implantable Medical Devices , 2016, IEEE Access.
[169] Tarik Taleb,et al. A Survey on Emerging SDN and NFV Security Mechanisms for IoT Systems , 2019, IEEE Communications Surveys & Tutorials.
[170] Shikha Agrawal,et al. Survey on Anomaly Detection using Data Mining Techniques , 2015, KES.
[171] Muttukrishnan Rajarajan,et al. Android Security: A Survey of Issues, Malware Penetration, and Defenses , 2015, IEEE Communications Surveys & Tutorials.
[172] Luigi Atzori,et al. Friendship Selection in the Social Internet of Things: Challenges and Possible Strategies , 2015, IEEE Internet of Things Journal.
[173] Laurence T. Yang,et al. Data Mining for Internet of Things: A Survey , 2014, IEEE Communications Surveys & Tutorials.
[174] Mohiuddin Ahmed,et al. A survey of network anomaly detection techniques , 2016, J. Netw. Comput. Appl..
[175] Jugal K. Kalita,et al. Network Anomaly Detection: Methods, Systems and Tools , 2014, IEEE Communications Surveys & Tutorials.
[176] Ricardo Neisse,et al. Physical layer authentication of Internet of Things wireless devices through permutation and dispersion entropy , 2017, 2017 Global Internet of Things Summit (GIoTS).
[177] Sean Carlisto de Alvarenga,et al. A survey of intrusion detection in Internet of Things , 2017, J. Netw. Comput. Appl..
[178] Flauzac Olivier,et al. New Security Architecture for IoT Network , 2015, ANT/SEIT.
[179] Soma Bandyopadhyay,et al. Role Of Middleware For Internet Of Things: A Study , 2011 .
[180] Nick Feamster,et al. Machine Learning DDoS Detection for Consumer Internet of Things Devices , 2018, 2018 IEEE Security and Privacy Workshops (SPW).
[181] Antonio Iera,et al. From "smart objects" to "social objects": The next evolutionary step of the internet of things , 2014, IEEE Communications Magazine.
[182] Rui L. Aguiar,et al. A secure IoT management architecture based on Information-Centric Networking , 2016, J. Netw. Comput. Appl..
[183] J. Ross Quinlan,et al. Induction of Decision Trees , 1986, Machine Learning.
[184] Walid Saad,et al. Jamming in the Internet of Things: A Game-Theoretic Perspective , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).
[185] Randy H. Katz,et al. A view of cloud computing , 2010, CACM.