• Mobile phone forensics: an investigative framework based on user impulsivity and secure collaboration errors

      Petraityte, Milda; Dehghantanha, Ali; Epiphaniou, Gregory; University of Salford; University of Bedfordshire (Elsevier Inc., 2017-01-06)
      This paper uses a scenario-based, role-play experiment based on the usage of QR codes to detect how mobile users respond to social engineering attacks conducted via mobile devices. The results of this experiment outline a guided mobile phone forensics investigation method that could facilitate the work of digital forensics investigators while analyzing the data from mobile devices. The behavioral response of users could be impacted by several aspects, such as impulsivity, smartphone usage and security, or simply awareness that QR codes could contain malware. The findings indicate that the impulsivity of users is one of the key areas that determines the common mistakes of mobile device users. As a result, an investigative framework for mobile phone forensics is proposed based on the impulsivity and common mistakes of mobile device users. It could help the forensics investigators by potentially shortening the time spent on investigation of possible breach scenarios.
    • A model for android and iOS applications risk calculation: CVSS analysis and enhancement using case-control studies

      Petraityte, Milda; Dehghantanha, Ali; Epiphaniou, Gregory; University of Salford; University of Bedfordshire (Springer New York LLC, 2018-04-24)
      Various researchers have shown that the Common Vulnerability Scoring System (CVSS) has many drawbacks and may not provide a precise view of the risks related to software vulnerabilities. However, many threat intelligence platforms and industry-wide standards are relying on CVSS score to evaluate cyber security compliance. This paper suggests several improvements to the calculation of Impact and Exploitability sub-scores within the CVSS, improve its accuracy and help threat intelligence analysts to focus on the key risks associated with their assets. We will apply our suggested improvements against risks associated with several Android and iOS applications and discuss achieved improvements and advantages of our modelling, such as the importance and the impact of time on the overall CVSS score calculation.