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Blockchain in Cybersecurity Realm: An Overview.

, , , and . Blockchain Cybersecurity, Trust and Privacy, volume 79 of Advances in Information Security, Springer, (2020)

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Privacy Preserving Abnormality Detection: A Deep Learning Approach., , , and . Handbook of Big Data Privacy, Springer, (2020)Big Data and Internet of Things Security and Forensics: Challenges and Opportunities., , and . Handbook of Big Data and IoT Security, Springer, (2019)An Ensemble of Deep Recurrent Neural Networks for Detecting IoT Cyber Attacks Using Network Traffic., , , , and . IEEE Internet Things J., 7 (9): 8852-8859 (2020)Proactive Detection of Query-based Adversarial Scenarios in NLP Systems., , , , and . AISec@CCS, page 103-113. ACM, (2022)IIoT Deep Malware Threat Hunting: From Adversarial Example Detection to Adversarial Scenario Detection., , , , , and . IEEE Trans. Ind. Informatics, 18 (12): 8477-8486 (2022)A multiview learning method for malware threat hunting: windows, IoT and android as case studies., , , , , , , and . World Wide Web, 23 (2): 1241-1260 (2020)RAT Hunter: Building Robust Models for Detecting Remote Access Trojans Based on Optimum Hybrid Features., , , , , , and . Handbook of Big Data Privacy, Springer, (2020)A Hybrid Deep Generative Local Metric Learning Method for Intrusion Detection., , , , , and . Handbook of Big Data Privacy, Springer, (2020)To Boost Graph Clustering Based on Power Iteration by Removing Outliers., and . DaEng, volume 285 of Lecture Notes in Electrical Engineering, page 249-258. Springer, (2013)Detecting crypto-ransomware in IoT networks based on energy consumption footprint., , , and . J. Ambient Intell. Humaniz. Comput., 9 (4): 1141-1152 (2018)