Articles producció científicaEnginyeria Informàtica i Matemàtiques

Analysis and Correlation of Visual Evidence in Campaigns of Malicious Office Documents

  • Identification data

    Identifier:  imarina:9368650
    Authors:  Casino F; Totosis N; Apostolopoulos T; Lykousas N; Patsakis C
    Abstract:
    Many malware campaigns use Microsoft (MS) Office documents as droppers to download and execute their malicious payload. Such campaigns often use these documents because MS Office is installed on billions of devices and that these files allow the execution of arbitrary VBA code. Recent versions of MS Office prevent the automatic execution of VBA macros, so malware authors try to convince users into enabling the content via images that, e.g., forge system or technical errors. In this article, we propose a mechanism to extract and analyse the different components of the files, including these visual elements, and construct lightweight signatures based on them. These visual elements are used as input for a text extraction pipeline which, in combination with the signatures, is able to capture the intent of MS Office files and the campaign they belong to. We test and validate our approach using an extensive database of malware samples, obtaining an accuracy above 99% in the task of distinguishing between benign and malicious files. Furthermore, our signature-based scheme allowed us to identify correlations between different campaigns, illustrating that some campaigns are either using the same tools or collaborating between them.
  • Others:

    Link to the original source: https://dl.acm.org/doi/10.1145/3513025
    APA: Casino F; Totosis N; Apostolopoulos T; Lykousas N; Patsakis C (2023). Analysis and Correlation of Visual Evidence in Campaigns of Malicious Office Documents. Digital Threats: Research And Practice, 4(2), -. DOI: 10.1145/3513025
    Paper original source: Digital Threats: Research And Practice. 4 (2):
    Article's DOI: 10.1145/3513025
    Journal publication year: 2023
    Entity: Universitat Rovira i Virgili
    Paper version: info:eu-repo/semantics/publishedVersion
    Record's date: 2025-02-24
    URV's Author/s: Casino Cembellín, Francisco José
    Department: Enginyeria Informàtica i Matemàtiques
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Publication Type: Journal Publications
    Author, as appears in the article.: Casino F; Totosis N; Apostolopoulos T; Lykousas N; Patsakis C
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Thematic Areas: Computer networks and communications, Computer science applications, Hardware and architecture, Information systems, Safety research, Software
    Author's mail: franciscojose.casino@urv.cat
  • Keywords:

    Machine learning
    Macro malware
    Malware
    Microsoft office
    Phishing
    Vba
    Computer Networks and Communications
    Computer Science Applications
    Hardware and Architecture
    Information Systems
    Safety Research
    Software
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