arXiv subjects

Benjamin Livshits

Publications and source records attributed to Benjamin Livshits.

60 records · Page 4Linked to original sources

arXiv2019

The Blind Men and the Internet: Multi-Vantage Point Web Measurements

In this paper, we design and deploy a synchronized multi-vantage point web measurement study to explore the comparability of web measurements across vantage points (VPs). We describe in reproducible detail the system with which we performed synchronized crawls on the Alexa top 5K domains from four distinct network VPs: research university, cloud datacenter, residential network, and Tor gateway proxy. Apart from the expected poor results from Tor, we observed no shocking disparities across VPs, but we did find significant impact from the residential VP's reliability and performance disadvantages. We also found subtle but distinct indicators that some third-party content consistently avoided crawls from our cloud VP. In summary, we infer that cloud VPs do fail to observe some content of interest to security and privacy researchers, who should consider augmenting cloud VPs with alternate VPs for cross-validation. Our results also imply that the added visibility provided by residential VPs over university VPs is marginal compared to the infrastructure complexity and network fragility they introduce.

cs.NI↗

arXiv2019

Static Analysis for Asynchronous JavaScript Programs

Asynchrony has become an inherent element of JavaScript, as an effort to improve the scalability and performance of modern web applications. To this end, JavaScript provides programmers with a wide range of constructs and features for developing code that performs asynchronous computations, including but not limited to timers, promises, and non-blocking I/O. However, the data flow imposed by asynchrony is implicit, and not always well-understood by the developers who introduce many asynchrony-related bugs to their programs. Worse, there are few tools and techniques available for analyzing and reasoning about such asynchronous applications. In this work, we address this issue by designing and implementing one of the first static analysis schemes capable of dealing with almost all the asynchronous primitives of JavaScript up to the 7th edition of the ECMAScript specification. Specifically, we introduce the callback graph, a representation for capturing data flow between asynchronous code. We exploit the callback graph for designing a more precise analysis that respects the execution order between different asynchronous functions. We parameterize our analysis with one novel context-sensitivity flavor, and we end up with multiple analysis variations for building callback graph. We performed a number of experiments on a set of hand-written and real-world JavaScript programs. Our results show that our analysis can be applied to medium-sized programs achieving 79% precision on average. The findings further suggest that analysis sensitivity is beneficial for the vast majority of the benchmarks. Specifically, it is able to improve precision by up to 28.5%, while it achieves an 88% precision on average without highly sacrificing performance.

cs.PL↗

arXiv2019

A Puff of Steem: Security Analysis of Decentralized Content Curation

Decentralized content curation is the process through which uploaded posts are ranked and filtered based exclusively on users' feedback. Platforms such as the blockchain-based Steemit employ this type of curation while providing monetary incentives to promote the visibility of high quality posts according to the perception of the participants. Despite the wide adoption of the platform very little is known regarding its performance and resilience characteristics. In this work, we provide a formal model for decentralized content curation that identifies salient complexity and game-theoretic measures of performance and resilience to selfish participants. Armed with our model, we provide a first analysis of Steemit identifying the conditions under which the system can be expected to correctly converge to curation while we demonstrate its susceptibility to selfish participant behaviour. We validate our theoretical results with system simulations in various scenarios.

cs.MA↗

arXiv2018

SpeedReader: Reader Mode Made Fast and Private

Most popular web browsers include "reader modes" that improve the user experience by removing un-useful page elements. Reader modes reformat the page to hide elements that are not related to the page's main content. Such page elements include site navigation, advertising related videos and images, and most JavaScript. The intended end result is that users can enjoy the content they are interested in, without distraction. In this work, we consider whether the "reader mode" can be widened to also provide performance and privacy improvements. Instead of its use as a post-render feature to clean up the clutter on a page we propose SpeedReader as an alternative multistep pipeline that is part of the rendering pipeline. Once the tool decides during the initial phase of a page load that a page is suitable for reader mode use, it directly applies document tree translation before the page is rendered. Based on our measurements, we believe that SpeedReader can be continuously enabled in order to drastically improve end-user experience, especially on slower mobile connections. Combined with our approach to predicting which pages should be rendered in reader mode with 91% accuracy, it achieves drastic speedups and bandwidth reductions of up to 27x and 84x respectively on average. We further find that our novel "reader mode" approach brings with it significant privacy improvements to users. Our approach effectively removes all commonly recognized trackers, issuing 115 fewer requests to third parties, and interacts with 64 fewer trackers on average, on transformed pages.

cs.IR↗

arXiv2018

Security: Doing Whatever is Needed... and Not a Thing More!

As malware, exploits, and cyber-attacks advance over time, so do the mitigation techniques available to the user. However, while attackers often abandon one form of exploitation in favor of a more lucrative one, mitigation techniques are rarely abandoned. Mitigations are rarely retired or disabled since proving they have outlived their usefulness is often impossible. As a result, performance overheads, maintenance costs, and false positive rates induced by the different mitigations accumulate, culminating in an outdated, inefficient, and costly security solution. We advocate for a new kind of tunable framework on which to base security mechanisms. This new framework enables a more reactive approach to security allowing us to optimize the deployment of security mechanisms based on the current state of attacks. Based on actual evidence of exploitation collected from the field, our framework can choose which mechanisms to enable/disable so that we can minimize the overall costs and false positive rates while maintaining a satisfactory level of security in the system. We use real-world Snort signatures to simulate the benefits of reactively disabling signatures when no evidence of exploitation is observed and compare them to the costs of the current state of deployment. Additionally, we evaluate the responsiveness of our framework and show that in case disabling a security mechanism triggers a reappearance of an attack we can respond in time to prevent mass exploitation. Through large-scale simulations that use integer linear and Bayesian solvers, we discover that our responsive strategy is both computationally affordable and results in significant reductions in false positives (~20% over traces that are about 9 years long), at the cost of introducing a moderate number of false negatives. Finding the optimal sampling strategy takes less than 2.5 minutes in the vast majority of cases.

cs.CR↗

arXiv2018

EthIR: A Framework for High-Level Analysis of Ethereum Bytecode

Analyzing Ethereum bytecode, rather than the source code from which it was generated, is a necessity when: (1) the source code is not available (e.g., the blockchain only stores the bytecode), (2) the information to be gathered in the analysis is only visible at the level of bytecode (e.g., gas consumption is specified at the level of EVM instructions), (3) the analysis results may be affected by optimizations performed by the compiler (thus the analysis should be done ideally after compilation). This paper presents EthIR, a framework for analyzing Ethereum bytecode, which relies on (an extension of) OYENTE, a tool that generates CFGs; EthIR produces from the CFGs, a rule-based representation (RBR) of the bytecode that enables the application of (existing) high-level analyses to infer properties of EVM code.

cs.PL↗