Systemization of Pluggable Transports for Censorship Resistance

An increasing number of countries implement Internet censorship at different scales and for a variety of reasons. In particular, the link between the censored client and entry point to the uncensored network is a frequent target of censorship due to the ease with which a nation-state censor can control it. A number of censorship resistance systems have been developed thus far to help circumvent blocking on this link, which we refer to as link circumvention systems (LCs). The variety and profusion of attack vectors available to a censor has led to an arms race, leading to a dramatic speed of evolution of LCs. Despite their inherent complexity and the breadth of work in this area, there is no systematic way to evaluate link circumvention systems and compare them against each other. In this paper, we (i) sketch an attack model to comprehensively explore a censor's capabilities, (ii) present an abstract model of a LC, a system that helps a censored client communicate with a server over the Internet while resisting censorship, (iii) describe an evaluation stack that underscores a layered approach to evaluate LCs, and (iv) systemize and evaluate existing censorship resistance systems that provide link circumvention. We highlight open challenges in the evaluation and development of LCs and discuss possible mitigations.Comment: Content from this paper was published in Proceedings on Privacy Enhancing Technologies (PoPETS), Volume 2016, Issue 4 (July 2016) as "SoK: Making Sense of Censorship Resistance Systems" by Sheharbano Khattak, Tariq Elahi, Laurent Simon, Colleen M. Swanson, Steven J. Murdoch and Ian Goldberg (DOI 10.1515/popets-2016-0028

Thwarting Web Censorship with Untrusted Messenger Discovery

All existing anti-censorship systems for the Web rely on proxies to grant clients access to censored information. Therefore, they face the proxy discovery problem: how can clients discover the proxies without having the censor discover and block these proxies? To avoid widespread discovery and blocking, proxies must not be widely published and should be discovered in-band. In this paper, we present a proxy discovery mechanism called keyspace hopping that meets this goal. Similar in spirit to frequency hopping in wireless networks, keyspace hopping ensures that each client discovers only a small fraction of the total number of proxies

Circumvention of censorship of internet access and publication

Internet censorship of one form or another affects on the order of half of all internet users. Previous work has studied this censorship, and proposed techniques for circumventing it, ranging from making proxy servers available to censored users, to tunneling internet connections through services such as voice or video chat, to embedding censorship circumvention in cloud platforms' front-end servers or even in ISP's routers. This dissertation describes a set of techniques for circumventing internet censorship building on and surpassing prior efforts. As is always the case, there are tradeoffs to be made: some of this work emphasizes deployability, and some aims for unstoppable circumvention with the assumption of significant resources. However, the latter techniques are not merely academic thought experiments: this dissertation also describes the experience of successfully deploying such a technique, which served tens of thousands of users. While the solid majority of previous work, as well as much of the work presented here, is focused on governments blocking access to sites and services hosted outside of their country, the rise of social media has created a new form of internet censorship. A country may block a social media platform, but have its own domestic version, on which it tightly controls what can be said. This dissertation describes a system for enabling users of such a platform to monitor for post deletions, and distribute the contents to other users

Security Hazards when Law is Code.

As software continues to eat the world, there is an increasing pressure to automate every aspect of society, from self-driving cars, to algorithmic trading on the stock market. As this pressure manifests into software implementations of everything, there are security concerns to be addressed across many areas. But are there some domains and fields that are distinctly susceptible to attacks, making them difficult to secure? My dissertation argues that one domain in particular—public policy and law— is inherently difficult to automate securely using computers. This is in large part because law and policy are written in a manner that expects them to be flexibly interpreted to be fair or just. Traditionally, this interpreting is done by judges and regulators who are capable of understanding the intent of the laws they are enforcing. However, when these laws are instead written in code, and interpreted by a machine, this capability to understand goes away. Because they blindly fol- low written rules, computers can be tricked to perform actions counter to their intended behavior. This dissertation covers three case studies of law and policy being implemented in code and security vulnerabilities that they introduce in practice. The first study analyzes the security of a previously deployed Internet voting system, showing how attackers could change the outcome of elections carried out online. The second study looks at airport security, investigating how full-body scanners can be defeated in practice, allowing attackers to conceal contraband such as weapons or high explosives past airport checkpoints. Finally, this dissertation also studies how an Internet censorship system such as China’s Great Firewall can be circumvented by techniques that exploit the methods employed by the censors themselves. To address these concerns of securing software implementations of law, a hybrid human-computer approach can be used. In addition, systems should be designed to allow for attacks or mistakes to be retroactively undone or inspected by human auditors. By combining the strengths of computers (speed and cost) and humans (ability to interpret and understand), systems can be made more secure and more efficient than a method employing either alone.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120795/1/ewust_1.pd

Scalable and Robust Distributed Algorithms for Privacy-Preserving Applications

We live in an era when political and commercial entities are increasingly engaging in sophisticated cyber attacks to damage, disrupt, or censor information content and to conduct mass surveillance. By compiling various patterns from user data over time, untrusted parties could create an intimate picture of sensitive personal information such as political and religious beliefs, health status, and so forth. In this dissertation, we study scalable and robust distributed algorithms that guarantee user privacy when communicating with other parties to either solely exchange information or participate in multi-party computations. We consider scalability and robustness requirements in three privacy-preserving areas: secure multi-party computation (MPC), anonymous broadcast, and blocking-resistant Tor bridge distribution. We propose decentralized algorithms for MPC that, unlike most previous work, scale well with the number of parties and tolerate malicious faults from a large fraction of the parties. Our algorithms do not require any trusted party and are fully load-balanced. Anonymity is an essential tool for achieving privacy; it enables individuals to communicate with each other without being identified as the sender or the receiver of the information being exchanged. We show that our MPC algorithms can be effectively used to design a scalable anonymous broadcast protocol. We do this by developing a multi-party shuffling protocol that can efficiently anonymize a sequence of messages in the presence of many faulty nodes. Our final approach for preserving user privacy in cyberspace is to improve Tor; the most popular anonymity network in the Internet. A current challenge with Tor is that colluding corrupt users inside a censorship territory can completely block user\u27s access to Tor by obtaining information about a large fraction of Tor bridges; a type of relay nodes used as the Tor\u27s primary mechanism for blocking-resistance. We describe a randomized bridge distribution algorithm, where all honest users are guaranteed to connect to Tor in the presence of an adversary corrupting an unknown number of users. Our simulations suggest that, with minimal resource costs, our algorithm can guarantee Tor access for all honest users after a small (logarithmic) number of rounds

Empowering bystanders to facilitate Internet censorship measurement and circumvention

Free and open exchange of information on the Internet is at risk: more than 60 countries practice some form of Internet censorship, and both the number of countries practicing censorship and the proportion of Internet users who are subject to it are on the rise. Understanding and mitigating these threats to Internet freedom is a continuous technological arms race with many of the most influential governments and corporations. By its very nature, Internet censorship varies drastically from region to region, which has impeded nearly all efforts to observe and fight it on a global scale. Researchers and developers in one country may find it very difficult to study censorship in another; this is particularly true for those in North America and Europe attempting to study notoriously pervasive censorship in Asia and the Middle East. This dissertation develops techniques and systems that empower users in one country, or bystanders, to assist in the measurement and circumvention of Internet censorship in another. Our work builds from the observation that there are people everywhere who are willing to help us if only they knew how. First, we develop Encore, which allows webmasters to help study Web censorship by collecting measurements from their sites' visitors. Encore leverages weaknesses in cross-origin security policy to collect measurements from a far more diverse set of vantage points than previously possible. Second, we build Collage, a technique that uses the pervasiveness and scalability of user-generated content to disseminate censored content. Collage's novel communication model is robust against censorship that is significantly more powerful than governments use today. Together, Encore and Collage help people everywhere study and circumvent Internet censorship.Ph.D

EFFICIENT DATA PROTECTION BY NOISING, MASKING, AND METERING

Protecting data secrecy is an important design goal of computing systems. Conventional techniques like access control mechanisms and cryptography are widely deployed, and yet security breaches and data leakages still occur. There are several challenges. First, sensitivity of the system data is not always easy to decide. Second, trustworthiness is not a constant property of the system components and users. Third, a system’s functional requirements can be at odds with its data protection requirements. In this dissertation, we show that efficient data protection can be achieved by noising, masking, or metering sensitive data. Specifically, three practical problems are addressed in the dissertation—storage side-channel attacks in Linux, server anonymity violations in web sessions, and data theft by malicious insiders. To mitigate storage side-channel attacks, we introduce a differentially private system, dpprocfs, which injects noise into side-channel vectors and also reestablishes invariants on the noised outputs. Our evaluations show that dpprocfs mitigates known storage side channels while preserving the utility of the proc filesystem for monitoring and diagnosis. To enforce server anonymity, we introduce a cloud service, PoPSiCl, which masks server identifiers, including DNS names and IP addresses, with personalized pseudonyms. PoPSiCl can defend against both passive and active network attackers with minimal impact to web-browsing performance. To prevent data theft from insiders, we introduce a system, Snowman, which restricts the user to access data only remotely and accurately meters the sensitive data output to the user by conducting taint analysis in a replica of the application execution without slowing the interactive user session.Doctor of Philosoph