FlowFence: Practical Data Protection for Emerging IoT Application Frameworks

By Earlence Fernandes, Justin Paupore, Amir Rahmati, Daniel Simionato, Mauro Conti, Atul Prakash. USENIX Security Symposium, 2016

298 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

ContexloT: Towards Providing Contextual Integrity to Appified IoT Platforms (2017, background): “In addition, drive-by download can also be easily adopted by attacker to entice users to download the malware app.”
Demystifying IoT Security: An Exhaustive Survey on IoT Vulnerabilities and a First Empirical Look on Internet-Scale IoT Exploitations (2019, methodology): “[119] introduced a method of restricting access to sensitive IoT data.”
Edge Computing Security: State of the Art and Challenges (2019, background): “[188] developed a systemlevel sandbox to place the codes that are in charge of requesting sensitive permissions.”
Protecting Visual Information in Augmented Reality from Malicious Application Developers (2019, background): “introduced FlowFence to guarantee that sensitive data is only processed within designated functions that run in FlowFence-provided sandboxes [10].”
Understanding the Mirai Botnet (2017, background): “proposed Flowfence, which enables data flow protection for emerging IoT frameworks [27].”
SoK: Security Evaluation of Home-Based IoT Deployments (2019, background): “FlowFence [28] is a framework that splits application codes into sensitive and non-sensitive modules and orchestrates the execution through opaque handlers.”