RanDroid: Structural Similarity Approach for Detecting Ransomware Applications in Android Platform

  • Abdulrahman Alzahrani
  • , Ali Alshehri
  • , Hani Alshahrani
  • , Raed Alharthi
  • , Huirong Fu
  • , Anyi Liu
  • , Ye Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

36 Scopus citations

Abstract

The worldwide epidemic of ransomware monetary gains has grown astonishingly. This crimeware form is emerged to extort innocent users under the threat of locking their devices and/or encrypting their files. To mitigate the growth of ransomware attacks, cybersecurity researchers have proposed various solutions based on the functionalities of those attacks. However, this polymorphic type is kept refined to increase the appearance of new families and survive against mitigation approaches. This paper introduces RanDroid, a new automated lightweight approach for detecting ransomware variants in Android platform by measuring the structural similarity between a set of collected information from an inspected application and a set of predefined threatening information collected from known ransomware variants. Furthermore, RanDroid performs a linguistic analysis on the app's code as well as image textural strings to enhance further revelation. RanDroid was evaluated using 950 ransomware samples. In addition, this approach is capable of extracting threatening messages from samples that use evasion techniques such as sophisticated codes or dynamic payloads.
Original languageEnglish
Title of host publicationIEEE International Conference on Electro Information Technology
Place of Publicationusa
PublisherIEEE Computer [email protected]
Pages892-897
Number of pages6
Volume2018-May
ISBN (Electronic)9781538653982
DOIs
StatePublished - Oct 18 2018
Event2018 IEEE International Conference on Electro/Information Technology, EIT 2018 - Rochester, United States
Duration: May 3 2018May 5 2018

Conference

Conference2018 IEEE International Conference on Electro/Information Technology, EIT 2018
Country/TerritoryUnited States
CityRochester
Period05/3/1805/5/18

Keywords

  • Extorting texts
  • Ransomware
  • Similarity measurement
  • Threatening images

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