Description
Smartphones are pervasive nowadays. They are supported by mobile platforms that allow users to download and run feature-rich mobile applications (apps). While mobile apps help users conveniently process personal data on mobile devices, they also pose security and privacy threats

Smartphones are pervasive nowadays. They are supported by mobile platforms that allow users to download and run feature-rich mobile applications (apps). While mobile apps help users conveniently process personal data on mobile devices, they also pose security and privacy threats and put user's data at risk. Even though modern mobile platforms such as Android have integrated security mechanisms to protect users, most mechanisms do not easily adapt to user's security requirements and rapidly evolving threats. They either fail to provide sufficient intelligence for a user to make informed security decisions, or require great sophistication to configure the mechanisms for enforcing security decisions. These limitations lead to a situation where users are disadvantageous against emerging malware on modern mobile platforms. To remedy this situation, I propose automated and systematic approaches to address three security management tasks: monitoring, assessment, and confinement of mobile apps. In particular, monitoring apps helps a user observe and record apps' runtime behaviors as controlled under security mechanisms. Automated assessment distills intelligence from the observed behaviors and the security configurations of security mechanisms. The distilled intelligence further fuels enhanced confinement mechanisms that flexibly and accurately shape apps' behaviors. To demonstrate the feasibility of my approaches, I design and implement a suite of proof-of-concept prototypes that support the three tasks respectively.
Reuse Permissions
  • Downloads
    pdf (2 MB)

    Details

    Title
    • Toward monitoring, assessing, and confining mobile applications in modern mobile platforms
    Contributors
    Date Created
    2015
    Resource Type
  • Text
  • Collections this item is in
    Note
    • Partial requirement for: Ph.D., Arizona State University, 2015
      Note type
      thesis
    • Includes bibliographical references (pages 138-148)
      Note type
      bibliography
    • Field of study: Computer science

    Citation and reuse

    Statement of Responsibility

    by Yiming Jing

    Machine-readable links