Static Malware Analysis in Encrypted Domain

Taeyoon Hwang, Ji Won Yoon

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    In the cloud computing environments, a server can handle a lot of data which an individuals cannot process. Therefore, many users upload data to the server and receive the results after computing the uploaded data. In the case of malware detection, the user uploads the suspicious file to the server and checks the file. However, if the file being examined is a document, there is a vulnerability that the data will be exposed to the server. Therefore, In this paper, we propose a computational matching algorithm in encrypted domain. We apply this technique to actual malware detection using the homomorphic encryption. And we measure the detection speed of string signatures with varying lengths and the time to detect string signatures from real malware.

    Original languageEnglish
    Title of host publicationICTC 2019 - 10th International Conference on ICT Convergence
    Subtitle of host publicationICT Convergence Leading the Autonomous Future
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages47-52
    Number of pages6
    ISBN (Electronic)9781728108926
    DOIs
    Publication statusPublished - 2019 Oct
    Event10th International Conference on Information and Communication Technology Convergence, ICTC 2019 - Jeju Island, Korea, Republic of
    Duration: 2019 Oct 162019 Oct 18

    Publication series

    NameICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future

    Conference

    Conference10th International Conference on Information and Communication Technology Convergence, ICTC 2019
    Country/TerritoryKorea, Republic of
    CityJeju Island
    Period19/10/1619/10/18

    Bibliographical note

    Publisher Copyright:
    © 2019 IEEE.

    Keywords

    • Homomorphic Encryption
    • Malware detection
    • Pattern matching
    • String signature

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Networks and Communications
    • Computer Science Applications
    • Information Systems and Management
    • Management of Technology and Innovation
    • Safety, Risk, Reliability and Quality
    • Media Technology
    • Control and Optimization

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