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Machine Learning Based Ransomware Detection Using Storage Access Patterns Obtained From Live-forensic Hypervisor., and . IoTSMS, page 393-398. IEEE, (2019)Energy Reduction of BTB by Focusing on Number of Branches per Cache Line., , and . J. Inf. Process., 24 (3): 492-503 (2016)LogDrive: a proactive data collection and analysis framework for time-traveling forensic investigation in IaaS cloud environments., , , and . J. Cloud Comput., (2018)A preactivating mechanism for a VT-CMOS cache using address prediction., , , , and . ISLPED, page 247-250. ACM, (2002)A prototype implementation and evaluation of the malware detection mechanism for IoT devices using the processor information., , , and . Int. J. Inf. Sec., 19 (1): 71-81 (2020)Defense Method of HTTP GET Flood Attack by Adaptively Controlling Server Resources Depending on Different Attack Intensity., , , and . J. Inf. Process., 24 (5): 802-815 (2016)HTTP-GET Flood Prevention Method by Dynamically Controlling Multiple Types of Virtual Machine Resources., , and . J. Inf. Process., 23 (5): 655-663 (2015)Detection of the DNS Water Torture Attack by Analyzing Features of the Subdomain Name., , , , and . J. Inf. Process., 24 (5): 793-801 (2016)An On-Chip Multiprocessor Architecture with a Non-Blocking Synchronization Mechanism., , , , and . EUROMICRO, page 1432-1440. IEEE Computer Society, (1999)Improvement of Data Utilization Efficiency for Cache Memory by Compressing Frequent Bit Sequences., , and . IEICE Trans. Electron., 99-C (8): 936-946 (2016)