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Mapa mental

ContexIoT

David Liu Inglês

Conteúdo do mapa

ContexIoT

  • 1. Appified IoT: 3rd-party develoepers 2. Permission model are flawed--> in need of a new access control model 3. ContexIoT: context-based permission system:     (1). fine-grained context identification for sensitive actions     (2). runtime prompts for users. 4. Context definition in ContexIoT is at inter-procedure level, and data flow level. 5. Prototyped on Samsung SmartThings.
  1. Security Analysis of Emerging Smart Home Applications (IEEE S&P 2016)

    • Security design flaws in the permission model of IoT platforms.
    • Therefore, a new access control model is needed in these appified IoT platforms
    • Access control mechanism of Recent appified platform (such as smartphone) are coarse-grained, insufficient and undemanding
      • [19] SoK: Lessons Learned From Android Security Research For Appified Software Platforms (IEEE S&P 2016)
        • User-driven access control: Rethinking permission granting in modern operating systems (IEEE S&P 2012)
          • [64] Android permissions remystified: A field study on contextual integrity (USENIX Security 2015)
            • Aurasium: Practical Policy Enforcement for Android Applications (USENIX Security 2012)
          • From numerous studies on Android and iOS permission systems, a key design flaw is that they either require users to make uninformed decision at install time [1] or prompt users at runtime when an app requests any of a handful of resources, without providing essential contextual information [2], [8]. These studies conclude that it is highly desirable to put the user in context when making permission granting decisions at runtime. This helps ensure a property known as “contextual integrity” defined by Nissenbaum [52] with which “information flows according to contextual norms,” and it is advocated as the desired norm for future permission system design of the smartphone platform [64], [68], [19].
            • [52] Privacy as contextual integrity (2004)
              • [68] Appcontext: Differentiating malicious and benign mobile app behaviors using context. (IEEE/ACM 2015)
                • [19] SoK: Lessons Learned From Android Security Research For Appified Software Platforms (IEEE S&P 2016)
                • As discussed in previous attempts to support contextual integrity in smartphone, providing contextual integrity in appified system is challenging because
                  • Availability of context: sensitive permission requests occur when the user is not interacting with the requesting app [64]
                  • Frequency of prompt: too frequent is annoying
                  • A permission is granted by the user to a functionality only under a particular usage context
                    • Usage Context of an app functionality=execution flow at runtime (trigger + callgraph) + data flowing through that path
                      • Practical trigger-action programming in the smart home (SIGCHI 2014)
                      • 33.21.50.67.19.64..56.54///usability34.64.44
  2. How do they patch Samsung SmartThings

    • To support existing SmartApps without changing the close-source SmartThings cloud backend, we developed an app patching machanism that convert unmodified SmartApps to ContexIoT-compatible SmartApps. The patching process separates the execution flow of a sensitive action in the original SmartApp into 2 steps: (1). collect the context info before the action is executed.
  3. Extensive study of possible attacks on appifiede IoT platforms

  4. Taxonomized IoT attack app dataset (based on lifecycle and adversary techniques

Informações

Descrição
Mapa Mental sobre ContexIoT, criado por David Liu em 31-03-2017.
Criado por
David Liu · mar 2017
Atualizado
1 abr 2017
Visualizações
3
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