Sea of Lights: Practical Device-to-Device Security Bootstrapping in the Dark

Practical solutions to bootstrap security in today's information and communication systems critically depend on centralized services for authentication as well as key and trust management. This is particularly true for mobile users. Identity providers such as Google or Facebook have active user bases of two billion each, and the subscriber number of mobile operators exceeds five billion unique users as of early 2018. If these centralized services go completely `dark' due to natural or man made disasters, large scale blackouts, or country-wide censorship, the users are left without practical solutions to bootstrap security on their mobile devices. Existing distributed solutions, for instance, the so-called web-of-trust are not sufficiently lightweight. Furthermore, they support neither cross-application on mobile devices nor strong protection of key material using hardware security modules. We propose Sea of Lights(SoL), a practical lightweight scheme for bootstrapping device-to-device security wirelessly, thus, enabling secure distributed self-organized networks. It is tailored to operate `in the dark' and provides strong protection of key material as well as an intuitive means to build a lightweight web-of-trust. SoL is particularly well suited for local or urban operation in scenarios such as the coordination of emergency response, where it helps containing/limiting the spreading of misinformation. As a proof of concept, we implement SoL in the Android platform and hence test its feasibility on real mobile devices. We further evaluate its key performance aspects using simulation

DroidSearch: A tool for scaling Android app triage to real-world app stores

The Android platform now features more than a million apps from thousands of developers. This abundance is convenient, as it caters to almost every need. But users and researchers also worry about the security and trustworthiness of these apps. While precise program-analysis tools are helpful in this context, unfortunately they do not scale to the large number of apps present in current app stores. In this work we thus present DroidSearch, a search engine that aids a multi-staged analysis in which fast pre-filtering techniques allow security experts to quickly retrieve candidate applications that should be subjected to further automated and/or manual analysis. DroidSearch is supported by DroidBase, a middleware and back-end database which associates apps with metadata and the results of lightweight analyses on bytecode and configuration files that DroidBase automatically manages and executes. Experiments on more than 235,000 applications from six different application stores including Google Play reveal many interesting findings. For instance, DroidSearch identifies 40 known malware applications in Google Play and detects over 35,000 applications that use both http and https connections for accessing the same resources, effectively rendering the https protection ineffective. It also reveals 11,995 applications providing access to potentially sensitive data through unprotected content providers