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

National Institute of Standards and Technology における超伝導研究及び生活

https://beloglazov.info/papers/2011-energy-aware-fgcs.pdf

Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing

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

The popularity and adoption of smart phones has greatly stimulated the spread of mobile malware, especially on the popular platforms such as Android. In light of their rapid growth, there is a pressing need to develop effective solutions. However, our defense capability is largely constrained by the limited understanding of these emerging mobile malware and the lack of timely access to related samples. In this paper, we focus on the Android platform and aim to systematize or characterize existing Android malware. Particularly, with more than one year effort, we have managed to collect more than 1,200 malware samples that cover the majority of existing Android malware families, ranging from their debut in August 2010 to recent ones in October 2011. In addition, we systematically characterize them from various aspects, including their installation methods, activation mechanisms as well as the nature of carried malicious payloads. The characterization and a subsequent evolution-based study of representative families reveal that they are evolving rapidly to circumvent the detection from existing mobile anti-virus software. Based on the evaluation with four representative mobile security software, our experiments show that the best case detects 79.6% of them while the worst case detects only 20.2% in our dataset. These results clearly call for the need to better develop next-generation anti-mobile-malware solutions.

/pdf/dissecting-android-malware-characterization-and-evolution-2euhdmm33o.pdf

Dissecting Android Malware: Characterization and Evolution

In this paper, we discuss the problem of distributing streaming media content, both live and on-demand, to a large number of hosts in a scalable way Our work is set in the context of the traditional client-server framework Specifically, we consider the problem that arises when the server is overwhelmed by the volume of requests from its clients As a solution, we propose Cooperative Networking (CoopNet), where clients cooperate to distribute content, thereby alleviating the load on the server We discuss the proposed solution in some detail, pointing out the interesting research issues that arise, and present a preliminary evaluation using traces gathered at a busy news site during the flash crowd that occurred on September 11, 2001

/pdf/distributing-streaming-media-content-using-cooperative-euklifrp31.pdf

Distributing streaming media content using cooperative networking

In this paper, we propose virtual data center (VDC) as the unit of resource allocation for multiple tenants in the cloud. VDCs are more desirable than physical data centers because the resources allocated to VDCs can be rapidly adjusted as tenants' needs change. To enable the VDC abstraction, we design a data center network virtualization architecture called SecondNet. SecondNet achieves scalability by distributing all the virtual-to-physical mapping, routing, and bandwidth reservation state in server hypervisors. Its port-switching based source routing (PSSR) further makes SecondNet applicable to arbitrary network topologies using commodity servers and switches. SecondNet introduces a centralized VDC allocation algorithm for bandwidth guaranteed virtual to physical mapping. Simulations demonstrate that our VDC allocation achieves high network utilization and low time complexity. Our implementation and experiments show that we can build SecondNet on top of various network topologies, and SecondNet provides bandwidth guarantee and elasticity, as designed.

/pdf/secondnet-a-data-center-network-virtualization-architecture-49dghj04lh.pdf

SecondNet: a data center network virtualization architecture with bandwidth guarantees

Modern browsers and smartphone operating systems treat applications as mutually untrusting, potentially malicious principals. Applications are (1) isolated except for explicit IPC or inter-application communication channels and (2) unprivileged by default, requiring user permission for additional privileges. Although inter-application communication supports useful collaboration, it also introduces the risk of permission redelegation. Permission re-delegation occurs when an application with permissions performs a privileged task for an application without permissions. This undermines the requirement that the user approve each application's access to privileged devices and data. We discuss permission re-delegation and demonstrate its risk by launching real-world attacks on Android system applications; several of the vulnerabilities have been confirmed as bugs.

We discuss possible ways to address permission redelegation and present IPC Inspection, a new OS mechanism for defending against permission re-delegation. IPC Inspection prevents opportunities for permission redelegation by reducing an application's permissions after it receives communication from a less privileged application. We have implemented IPC Inspection for a browser and Android, and we show that it prevents the attacks we found in the Android system applications.

/pdf/permission-re-delegation-attacks-and-defenses-2xeg5bvage.pdf

Permission re-delegation: attacks and defenses

Software patching has not been effective as a first-line defense against large-scale worm attacks, even when patches have long been available for their corresponding vulnerabilities. Generally, people have been reluctant to patch their systems immediately, because patches are perceived to be unreliable and disruptive to apply. To address this problem, we propose a first-line worm defense in the network stack, using shields -- vulnerability-specific, exploit-generic network filters installed in end systems once a vulnerability is discovered, but before a patch is applied. These filters examine the incoming or outgoing traffic of vulnerable applications, and correct traffic that exploits vulnerabilities. Shields are less disruptive to install and uninstall, easier to test for bad side effects, and hence more reliable than traditional software patches. Further, shields are resilient to polymorphic or metamorphic variations of exploits [43].In this paper, we show that this concept is feasible by describing a prototype Shield framework implementation that filters traffic above the transport layer. We have designed a safe and restrictive language to describe vulnerabilities as partial state machines of the vulnerable application. The expressiveness of the language has been verified by encoding the signatures of several known vulnerabilites. Our evaluation provides evidence of Shield's low false positive rate and small impact on application throughput. An examination of a sample set of known vulnerabilities suggests that Shield could be used to prevent exploitation of a substantial fraction of the most dangerous ones.

/pdf/shield-vulnerability-driven-network-filters-for-preventing-4qf31vor6m.pdf

Shield: vulnerability-driven network filters for preventing known vulnerability exploits

Application-level protocol specifications are useful for many security applications, including intrusion prevention and detection that performs deep packet inspection and traffic normalization, and penetration testing that generates network inputs to an application to uncover potential vulnerabilities. However, current practice in deriving protocol specifications is mostly manual. In this paper, we present Discoverer, a tool for automatically reverse engineering the protocol message formats of an application from its network trace. A key property of Discoverer is that it operates in a protocol-independent fashion by inferring protocol idioms commonly seen in message formats of many application-level protocols. We evaluated the efficacy of Discoverer over one text protocol (HTTP) and two binary protocols (RPC and CIFS/SMB) by comparing our inferred formats with true formats obtained from Ethereal [5]. For all three protocols, more than 90% of our inferred formats correspond to exactly one true format; one true format is reflected in five inferred formats on average; our inferred formats cover over 95% of messages, which belong to 30-40% of true formats observed in the trace.

/pdf/discoverer-automatic-protocol-reverse-engineering-from-2y8j11b7o5.pdf

Helen J. Wang

Papers

Distributing streaming media content using cooperative networking

SecondNet: a data center network virtualization architecture with bandwidth guarantees

Permission re-delegation: attacks and defenses

Shield: vulnerability-driven network filters for preventing known vulnerability exploits

Discoverer: automatic protocol reverse engineering from network traces