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Identifying cyber threats to mobile-IoT applications in edge computing paradigm., , , , and . Future Gener. Comput. Syst., (2018)Increasing the Trustworthiness in the Industrial IoT Networks Through a Reliable Cyberattack Detection Model., , , and . IEEE Trans. Ind. Informatics, 16 (9): 6154-6162 (2020)Evolution of Dark Web Threat Analysis and Detection: A Systematic Approach., , , and . IEEE Access, (2020)Reinforcement Learning Approach to AIBO Robot's Decision Making Process in Robosoccer's Goal Keeper Problem., , , and . SNPD, page 24-30. IEEE Computer Society, (2011)An adaptive framework against android privilege escalation threats using deep learning and semi-supervised approaches., , , and . Appl. Soft Comput., (2020)Malware Threats and Detection for Industrial Mobile-IoT Networks., , , , and . IEEE Access, (2018)Hybrid Wrapper-Filter Approaches for Input Feature Selection Using Maximum Relevance and Artificial Neural Network Input Gain Measurement Approximation (ANNIGMA)., , and . NSS, page 442-449. IEEE Computer Society, (2010)Smokers' Characteristics and Cluster Based Quitting Rule Discovery Model for Enhancement of Government's Tobacco Control Systems., , and . PACIS, page 26. AISeL, (2010)Process Performance Evaluation Using Evolutionary Algorithm., , , , and . IKE, page 731-737. CSREA Press, (2009)Smart RFID Reader Protocol for Malware Detection., , and . SNPD, page 64-69. IEEE Computer Society, (2011)