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SEER: practical memory virus scanning as a service

Published: 08 December 2014 Publication History

Abstract

Virus Scanning-as-a-Service (VSaaS) has emerged as a popular security solution for virtual cloud environments. However, existing approaches fail to scan guest memory, which can contain an emerging class of Memory-only Malware. While several host-based memory scanners are available, they are computationally less practical for cloud environments. This paper proposes SEER as an architecture for enabling Memory VSaaS for virtualized environments. SEER leverages cloud resources and technologies to consolidate and aggregate virus scanning activities to efficiently detect malware residing in memory. Specifically, SEER combines fast memory snapshotting and computation deduplication to provide practical and efficient off-host memory virus scanning. We evaluate SEER and demonstrate up to an 87% reduction in data size that must be scanned and up to 72% savings in overall scan time, compared to naively applying file-based scanning approaches. Furthermore, SEER provides a 50% reduction in scan time when using a warm cache. In doing so, SEER provides a practical solution for cloud vendors to transparently and periodically scan virtual machine memory for malware.

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Cited By

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  • (2022) Terminator: A Secure Coprocessor to Accelerate Real-Time AntiViruses Using Inspection BreakpointsACM Transactions on Privacy and Security10.1145/349453525:2(1-34)Online publication date: 4-Mar-2022
  • (2022)An Adaptive Anomaly Detection Method for Cloud Computing System2022 IEEE 5th International Conference on Electronics Technology (ICET)10.1109/ICET55676.2022.9823988(1289-1295)Online publication date: 13-May-2022
  • (2021)Challenges and pitfalls in malware researchComputers and Security10.1016/j.cose.2021.102287106:COnline publication date: 1-Jul-2021
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  1. SEER: practical memory virus scanning as a service

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    cover image ACM Other conferences
    ACSAC '14: Proceedings of the 30th Annual Computer Security Applications Conference
    December 2014
    492 pages
    ISBN:9781450330053
    DOI:10.1145/2664243
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 08 December 2014

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    ACSAC '14: Annual Computer Security Applications Conference
    December 8 - 12, 2014
    Louisiana, New Orleans, USA

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    Overall Acceptance Rate 104 of 497 submissions, 21%

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    View all
    • (2022) Terminator: A Secure Coprocessor to Accelerate Real-Time AntiViruses Using Inspection BreakpointsACM Transactions on Privacy and Security10.1145/349453525:2(1-34)Online publication date: 4-Mar-2022
    • (2022)An Adaptive Anomaly Detection Method for Cloud Computing System2022 IEEE 5th International Conference on Electronics Technology (ICET)10.1109/ICET55676.2022.9823988(1289-1295)Online publication date: 13-May-2022
    • (2021)Challenges and pitfalls in malware researchComputers and Security10.1016/j.cose.2021.102287106:COnline publication date: 1-Jul-2021
    • (2020)PHM Technology for Memory Anomalies in Cloud Computing for IaaS2020 IEEE 20th International Conference on Software Quality, Reliability and Security (QRS)10.1109/QRS51102.2020.00018(41-51)Online publication date: Dec-2020
    • (2019)A Cloud-Based Real-Time Mechanism to Protect End Hosts against MalwareApplied Sciences10.3390/app91837489:18(3748)Online publication date: 8-Sep-2019
    • (2019)Forensics‐as‐a‐Service (FaaS) in the State‐of‐the‐Art CloudSecurity, Privacy, and Digital Forensics in the Cloud10.1002/9781119053385.ch16(321-337)Online publication date: 8-Feb-2019
    • (2017)Black penguin: On the feasibility of detecting intrusion with homogeneous memory2017 IEEE Conference on Communications and Network Security (CNS)10.1109/CNS.2017.8228671(586-594)Online publication date: Oct-2017
    • (2017)Hidden process offline forensic based on memory analysis in windowsWuhan University Journal of Natural Sciences10.1007/s11859-017-1257-y22:4(346-354)Online publication date: 15-Jul-2017
    • (2015)CloudIDEAProceedings of the Confederated International Conferences on On the Move to Meaningful Internet Systems: OTM 2015 Conferences - Volume 941510.1007/978-3-319-26148-5_40(594-611)Online publication date: 26-Oct-2015

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