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Ransomware Protection in Storage Systems: Advanced Technologies and Best Practices for Data Security

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  • Arjun Bhargav Devan

    (Independent Researcher, USA)

Abstract

Ransomware attacks have dramatically changed how organizations think about cybersecurity, with criminals increasingly targeting storage systems to cause maximum damage and disruption. This article presents novel technologies and proven practices for defending storage infrastructure against advanced ransomware campaigns. Threat actors have evolved beyond basic file encryption, deploying sophisticated multi-stage attacks that conventional security measures struggle to address within storage environments. Immutable snapshots act as a core technology for ransomware defense, building tamper-resistant data copies that stay permanently shielded from modification or removal. These solutions, when paired with zero trust principles, provide a strong defense against recurring threats that target backup and recovery systems in particular. Autonomous Ransomware Protection systems outperform human-managed security monitoring by using artificial intelligence and machine learning to detect and halt ransomware activity quickly. Behavioral evaluation engines work with anomaly detection algorithms to spot new attack types and unknown threats before major damage happens. Smart implementation needs complete strategies that mix technological solutions with organizational processes, demanding detailed evaluation of hybrid cloud environments and distributed storage setups. Ransomware protection success relies on thorough training programs, regular testing schedules, and ongoing improvements based on emerging threat intelligence gathered from real security incidents.

Suggested Citation

  • Arjun Bhargav Devan, 2025. "Ransomware Protection in Storage Systems: Advanced Technologies and Best Practices for Data Security," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 7(8), pages 124-130, July.
  • Handle: RePEc:alk:jcsts0:v:7:y:2025:i:8:id:10461
    DOI: 10.32996/jcsts.2025.7.8.15
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