• Login
    View Item 
    •   Home
    • Research from April 2016
    • Computing
    • View Item
    •   Home
    • Research from April 2016
    • Computing
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UOBREPCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalDepartmentThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalDepartment

    My Account

    LoginRegister

    About

    AboutLearning ResourcesResearch Graduate SchoolResearch InstitutesUniversity Website

    Statistics

    Display statistics

    Effective methods to detect metamorphic malware: a systematic review

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Authors
    Irshad, Mustafa
    al-Khateeb, Haider
    Mansour, Ali
    Ashawa, Moses
    Hamisu, Muhammad
    Affiliation
    University of Bedfordshire
    Issue Date
    2018-04-12
    Subjects
    CFG
    control flow graph
    metaphoric malware
    API call graph
    opcode
    malware detection
    
    Metadata
    Show full item record
    Abstract
    The succeeding code for metamorphic malware is routinely rewritten to remain stealthy and undetected within infected environments. This characteristic is maintained by means of encryption and decryption methods, obfuscation through garbage code insertion, code transformation and registry modification which makes detection very challenging. The main objective of this study is to contribute an evidence-based narrative demonstrating the effectiveness of recent proposals. 16 primary studies were included in this analysis based on a pre-defined protocol. The majority of the reviewed detection methods used Opcode, control flow graph (CFG) and API call graph. Key challenges facing the detection of metamorphic malware include code obfuscation, lack of dynamic capabilities to analyse code and application difficulty. Methods were further analysed on the basis of their approach, limitation, empirical evidence and key parameters such as dataset, detection rate (DR) and false positive rate (FPR).
    Citation
    Irshad M, Al-Khateeb H, Mansour A, Ashawa M, Hamisu M (2018) 'Effective methods to detect metamorphic malware: a systematic review', International Journal of Electronic Security and Digital Forensics, 10 (2), pp.138-154.
    Publisher
    Inderscience
    Journal
    International Journal of Electronic Security and Digital Forensics
    URI
    http://hdl.handle.net/10547/623829
    DOI
    10.1504/IJESDF.2018.090948
    Additional Links
    https://www.inderscienceonline.com/doi/abs/10.1504/IJESDF.2018.090948
    Type
    Article
    Language
    en
    ISSN
    1751-911X
    EISSN
    1751-9128
    ae974a485f413a2113503eed53cd6c53
    10.1504/IJESDF.2018.090948
    Scopus Count
    Collections
    Computing

    entitlement

     
    DSpace software (copyright © 2002 - 2021)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.