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Real-time Detection of Data Corruption
A proactive approach to data resilience requires identifying threats at the first possible opportunity, before they can infiltrate your systems and wreak havoc. IBM scientists and engineers have recently developed new techniques for scanning data as it arrives inside an IBM FlashSystem array, measuring the entropy or randomness of the data to help identify specific kinds of encrypted data that could be evidence of malware. IBM Fellow Andy Walls explains how this kind of technology could help organizations protect themselves from current and future malware infections.
play_circle_outlineUtilizing a Proactive Approach to Data Resilience, Threat Identification, and IBM's Enhanced Flash Array Scanning Techniques
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play_circle_outlineNeed for detection of intrusions in block storage devices
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play_circle_outlineInsights into IBM Scientists' Challenges in Developing Real-Time Data Corruption Detection for Enhanced Cybersecurity
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play_circle_outlineUtilizing Shannon Entropy: Monitoring Data Disorder & Identifying Encryption with Implications for Storage Administrators
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play_circle_outlineExploring the Link between Monitoring Entropy, Compression, Access Patterns, and Users in the Detection of Anomalies and Ransomware Attacks
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play_circle_outlineEnhancing Data Security and Analysis: Flexibility, Adaptiveness, and AI Integration in Real-Time Detection Systems
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play_circle_outlineInferencing at the Edge and in Applications: Harnessing the Power of Data in the Cloud
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play_circle_outlineExploring the Adoption Considerations and Cost Reduction of Storage, Tech Development, and Anomaly Detection
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play_circle_outlineExploring the Unique Capability of Block Storage Devices and the Computational Storage Advantage of the FlashCore Module
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play_circle_outlineExploring Data Collection, Analysis, and Storage: Safeguarding Customers and Fueling Innovation in the Stack
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play_circle_outlineFinding Satisfaction and Gratification: Unleashing the Mission to Protect Customers and Society