Today’s smartphone operating systems frequently fail to provide users with visibility into how third-party applications collect and share their private data. We address these shortcomings with TaintDroid, an efficient, system-wide dynamic taint tracking and analysis system capable of simultaneously tracking multiple sources of sensitive data. TaintDroid enables realtime analysis by leveraging Android’s virtualized execution environment. TaintDroid incurs only 32p performance overhead on a CPU-bound microbenchmark and imposes negligible overhead on interactive third-party applications. Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, in our 2010 study we found 20 applications potentially misused users’ private information; so did a similar fraction of the tested applications in our 2012 study. Monitoring the flow of privacy-sensitive data with TaintDroid provides valuable input for smartphone users and security service firms seeking to identify misbehaving applications.

/pdf/taintdroid-an-information-flow-tracking-system-for-realtime-5d8smsr0iy.pdf

TaintDroid: An Information-Flow Tracking System for Realtime Privacy Monitoring on Smartphones

Today's smartphone operating systems frequently fail to provide users with adequate control over and visibility into how third-party applications use their private data. We address these shortcomings with TaintDroid, an efficient, system-wide dynamic taint tracking and analysis system capable of simultaneously tracking multiple sources of sensitive data. TaintDroid provides realtime analysis by leveraging Android's virtualized execution environment. TaintDroid incurs only 14% performance overhead on a CPU-bound micro-benchmark and imposes negligible overhead on interactive third-party applications. Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, we found 68 instances of potential misuse of users' private information across 20 applications. Monitoring sensitive data with TaintDroid provides informed use of third-party applications for phone users and valuable input for smartphone security service firms seeking to identify misbehaving applications.

/pdf/taintdroid-an-information-flow-tracking-system-for-realtime-3fnz9lwdso.pdf

TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones

Edge Computing provides mobile and Internet-of-Things (IoT) app vendors with a new distributed computing paradigm which allows an app vendor to deploy its app at hired edge servers distributed near app users at the edge of the cloud. This way, app users can be allocated to hired edge servers nearby to minimize network latency and energy consumption. A cost-effective edge user allocation (EUA) requires maximum app users to be served with minimum overall system cost. Finding a centralized optimal solution to this EUA problem is NP-hard. Thus, we propose EUAGame, a game-theoretic approach that formulates the EUA problem as a potential game. We analyze the game and show that it admits a Nash equilibrium. Then, we design a novel decentralized algorithm for finding a Nash equilibrium in the game as a solution to the EUA problem. The performance of this algorithm is theoretically analyzed and experimentally evaluated. The results show that the EUA problem can be solved effectively and efficiently.

A Game-Theoretical Approach for User Allocation in Edge Computing Environment

In this paper, we perform a systematic design study of the "elephant in the room" facing the VR industry -- is it feasible to enable high-quality VR apps on untethered mobile devices such as smartphones? Our quantitative, performance-driven design study makes two contributions. First, we show that the QoE achievable for high-quality VR applications on today's mobile hardware and wireless networks via local rendering or offloading is about 10X away from the acceptable QoE, yet waiting for future mobile hardware or next-generation wireless networks (e.g. 5G) is unlikely to help, because of power limitation and the higher CPU utilization needed for processing packets under higher data rate. Second, we present Furion, a VR framework that enables high-quality, immersive mobile VR on today's mobile devices and wireless networks. Furion exploits a key insight about the VR workload that foreground interactions and background environment have contrasting predictability and rendering workload, and employs a split renderer architecture running on both the phone and the server. Supplemented with video compression, use of panoramic frames, and parallel decoding on multiple cores on the phone, we demonstrate Furion can support high-quality VR apps on today's smartphones over WiFi, with under 14ms latency and 60 FPS (the phone display refresh rate).

https://dl.acm.org/doi/pdf/10.1145/3117811.3117815

Furion: Engineering High-Quality Immersive Virtual Reality on Today's Mobile Devices

Big data, with their promise to discover valuable insights for better decision making, have recently attracted significant interest from both academia and industry. Voluminous data are generated from a variety of users and devices, and are to be stored and processed in powerful data centers. As such, there is a strong demand for building an unimpeded network infrastructure to gather geologically distributed and rapidly generated data, and move them to data centers for effective knowledge discovery. The express network should also be seamlessly extended to interconnect multiple data centers as well as interconnect the server nodes within a data center. In this article, we take a close look at the unique challenges in building such a network infrastructure for big data. Our study covers each and every segment in this network highway: the access networks that connect data sources, the Internet backbone that bridges them to remote data centers, as well as the dedicated network among data centers and within a data center. We also present two case studies of real-world big data applications that are empowered by networking, highlighting interesting and promising future research directions.

Building a network highway for big data: architecture and challenges

This paper presents Kahawai1, a system that provides high-quality gaming on mobile devices, such as tablets and smartphones, by offloading a portion of the GPU computation to server-side infrastructure In contrast with previous thin-client approaches that require a server-side GPU to render the entire content, Kahawai uses collaborative rendering to combine the output of a mobile GPU and a server-side GPU into the displayed output Compared to a thin client, collaborative rendering requires significantly less network bandwidth between the mobile device and the server to achieve the same visual quality and, unlike a thin client, collaborative rendering supports disconnected operation, allowing a user to play offline - albeit with reduced visual quality Kahawai implements two separate techniques for collaborative rendering: (1) a mobile device can render each frame with reduced detail while a server sends a stream of per-frame differences to transform each frame into a high detail version, or (2) a mobile device can render a subset of the frames while a server provides the missing frames Both techniques are compatible with the hardware-accelerated H264 video decoders found on most modern mobile devices We implemented a Kahawai prototype and integrated it with the idTech 4 open-source game engine, an advanced engine used by many commercial games In our evaluation, we show that Kahawai can deliver gameplay at an acceptable frame rate, and achieve high visual quality using as little as one-sixth of the bandwidth of the conventional thin-client approach Furthermore, a 50-person user study with our prototype shows that Kahawai can deliver the same gaming experience as a thin client under excellent network conditions

https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/mobi093f-cuervoA.pdf

Demo: Kahawai: high-quality mobile gaming using GPU offload

Users are increasingly vulnerable to inadvertently leaking sensitive information through cameras. In this paper, we investigate an approach to mitigating the risk of such inadvertent leaks called privacy markers. Privacy markers give users fine-grained control of what visual information an app can access through a device's camera. We present two examples of this approach: PrivateEye, which allows a user to mark regions of a two-dimensional surface as safe to release to an app, and WaveOff, which does the same for three-dimensional objects. We have integrated both systems with Android's camera subsystem. Experiments with our prototype show that a Nexus 5 smartphone can deliver near realtime frame rates while protecting secret information, and a 26-person user study elicited positive feedback on our prototype's speed and ease-of-use.

https://dl.acm.org/doi/pdf/10.1145/2906388.2906405

What You Mark is What Apps See

This paper presents SpanDex, a set of extensions to Android's Dalvik virtual machine that ensures apps do not leak users' passwords. The primary technical challenge addressed by SpanDex is precise, sound, and efficient handling of implicit information flows (e.g., information transferred by a program's control flow). SpanDex handles implicit flows by borrowing techniques from symbolic execution to precisely quantify the amount of information a process' control flow reveals about a secret. To apply these techniques at runtime without sacrificing performance, SpanDex runs untrusted code in a data-flow sensitive sandbox, which limits the mix of operations that an app can perform on sensitive data. Experiments with a SpanDex prototype using 50 popular Android apps and an analysis of a large list of leaked passwords predicts that for 90% of users, an attacker would need over 80 login attempts to guess their password. Today the same attacker would need only one attempt for all users.

/pdf/spandex-secure-password-tracking-for-android-53n27vrpwp.pdf

SpanDex: secure password tracking for android

We show that the performance of downloads in a 3G/HSPA mobile network can be significantly degraded by a concurrent upload that saturates the uplink buffer on the mobile device. In particular, we found in some instances that download speeds can be reduced by over an order of magnitude from 2,000 kbps to 100 kbps. To mitigate this problem, we propose a new algorithm called Receiver-side Flow Control (RSFC) that regulates the uplink buffer on 3G/HSPA data senders. It uses a feedback loop to monitor the available upload capacity and dynamically adjusts the TCP receiver window (rwnd) accordingly. We evaluated RSFC on the 3G/HSPA networks of three different mobile ISPs and show that for one of them, RSFC can improve the download throughput from less than 400 kbps to up to 1,400 kbps. In the presence of a concurrent upload, RSFC can also reduce website load times from more than 2 minutes to less than 1 minute 90% of the time. Our technique is compatible with existing TCP implementations and can easily be deployed at 3G web proxies without requiring any modification to existing mobile devices.

/pdf/dynamic-regulation-of-mobile-3g-hspa-uplink-buffer-with-4bu2olfgmq.pdf

Dynamic regulation of mobile 3G/HSPA uplink buffer with Receiver-side Flow Control

The permissions framework for Android is frustratingly inflexible. Once granted a permission, Android will always allow an app to access the resource until the user manually revokes the app's permission. Prior work has proposed extensible plugin frameworks, but they have struggled to support flexible authorization and isolate apps and plugins from each other. In this paper, we propose DALF, a framework for extensible permissions plugins that provides both flexibility and isolation. The insight underlying DALF is that permissions plugins should be treated as apps themselves. This approach allows plugins to maintain state and access system resources such as a device's location while being restricted by Android's process-isolation mechanisms. Experiments with microbenchmarks and case studies with real third-party apps show promising results: plugins are easy to develop and impose acceptable overhead for most resources.

https://dl.acm.org/doi/pdf/10.1145/3307334.3326095

Ali Razeen

Papers

Demo: Kahawai: high-quality mobile gaming using GPU offload

What You Mark is What Apps See

SpanDex: secure password tracking for android

Dynamic regulation of mobile 3G/HSPA uplink buffer with Receiver-side Flow Control

Permissions Plugins as Android Apps