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Conference Paper: SRA: Smart Recovery Advisor for Cyber Attacks

TitleSRA: Smart Recovery Advisor for Cyber Attacks
Authors
Keywordscontinuous data protection
machine learning
ransomware
storage recovery
Issue Date2021
Citation
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2021, p. 2691-2695 How to Cite?
AbstractContinuous Data Protection (CDP) is becoming instrumental in recovering applications from crypto-ransomware attacks. It enables fine-grained recovery through journaling, allowing the applications (its volumes) to recover to any previous state. While zero data loss can be achieved during recovery with CDP, the timestamp of the desired restore point, i.e., the one just prior to the attack, needs to be provided to reconstruct the volume. Such information is often unavailable in practice, and system administrators can only adopt a trial-and-error strategy to narrow down the time range of desired restore points by making multiple time-consuming recovery attempts. The recovery systems offer little guidance in pointing to the restore points containing a valid application state and reducing data loss. To address this problem, we equip the CDP-based recovery with machine intelligence. This demonstration showcases Smart Recovery Advisor (SRA), which offers interpretable, data-driven, and feedback-aware restore point recommendations that reduce the number of recovery attempts while minimizing data loss.
Persistent Identifierhttp://hdl.handle.net/10722/343345
ISSN
2023 SCImago Journal Rankings: 2.640

 

DC FieldValueLanguage
dc.contributor.authorChow, Ka Ho-
dc.contributor.authorDeshpande, Umesh-
dc.contributor.authorSeshadri, Sangeetha-
dc.contributor.authorLiu, Ling-
dc.date.accessioned2024-05-10T09:07:21Z-
dc.date.available2024-05-10T09:07:21Z-
dc.date.issued2021-
dc.identifier.citationProceedings of the ACM SIGMOD International Conference on Management of Data, 2021, p. 2691-2695-
dc.identifier.issn0730-8078-
dc.identifier.urihttp://hdl.handle.net/10722/343345-
dc.description.abstractContinuous Data Protection (CDP) is becoming instrumental in recovering applications from crypto-ransomware attacks. It enables fine-grained recovery through journaling, allowing the applications (its volumes) to recover to any previous state. While zero data loss can be achieved during recovery with CDP, the timestamp of the desired restore point, i.e., the one just prior to the attack, needs to be provided to reconstruct the volume. Such information is often unavailable in practice, and system administrators can only adopt a trial-and-error strategy to narrow down the time range of desired restore points by making multiple time-consuming recovery attempts. The recovery systems offer little guidance in pointing to the restore points containing a valid application state and reducing data loss. To address this problem, we equip the CDP-based recovery with machine intelligence. This demonstration showcases Smart Recovery Advisor (SRA), which offers interpretable, data-driven, and feedback-aware restore point recommendations that reduce the number of recovery attempts while minimizing data loss.-
dc.languageeng-
dc.relation.ispartofProceedings of the ACM SIGMOD International Conference on Management of Data-
dc.subjectcontinuous data protection-
dc.subjectmachine learning-
dc.subjectransomware-
dc.subjectstorage recovery-
dc.titleSRA: Smart Recovery Advisor for Cyber Attacks-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1145/3448016.3452766-
dc.identifier.scopuseid_2-s2.0-85108951742-
dc.identifier.spage2691-
dc.identifier.epage2695-

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