A Survey on Routing in Anonymous Communication Protocols

The Internet has undergone dramatic changes in the past 15 years, and now forms a global communication platform that billions of users rely on for their daily activities. While this transformation has brought tremendous benefits to society, it has also created new threats to online privacy, ranging from profiling of users for monetizing personal information to nearly omnipotent governmental surveillance. As a result, public interest in systems for anonymous communication has drastically increased. Several such systems have been proposed in the literature, each of which offers anonymity guarantees in different scenarios and under different assumptions, reflecting the plurality of approaches for how messages can be anonymously routed to their destination. Understanding this space of competing approaches with their different guarantees and assumptions is vital for users to understand the consequences of different design options. In this work, we survey previous research on designing, developing, and deploying systems for anonymous communication. To this end, we provide a taxonomy for clustering all prevalently considered approaches (including Mixnets, DC-nets, onion routing, and DHT-based protocols) with respect to their unique routing characteristics, deployability, and performance. This, in particular, encompasses the topological structure of the underlying network; the routing information that has to be made available to the initiator of the conversation; the underlying communication model; and performance-related indicators such as latency and communication layer. Our taxonomy and comparative assessment provide important insights about the differences between the existing classes of anonymous communication protocols, and it also helps to clarify the relationship between the routing characteristics of these protocols, and their performance and scalability

Human-data interaction

We have moved from a world where computing is siloed and specialised, to a world where computing is ubiquitous and everyday. In many, if not most, parts of the world, networked computing is now mundane as both foreground (e.g., smartphones, tablets) and background (e.g., road tra c management, financial systems) technologies. This has permitted, and continues to permit, new gloss on existing interactions (e.g., online banking) as well as distinctively new interactions (e.g., massively scalable distributed real-time mobile gaming). An e ect of this increasing pervasiveness of networked computation in our environments and our lives is that data are also now ubiquitous: in many places, much of society is rapidly becoming “data driven”

Technical Privacy Metrics: a Systematic Survey

The file attached to this record is the author's final peer reviewed versionThe goal of privacy metrics is to measure the degree of privacy enjoyed by users in a system and the amount of protection offered by privacy-enhancing technologies. In this way, privacy metrics contribute to improving user privacy in the digital world. The diversity and complexity of privacy metrics in the literature makes an informed choice of metrics challenging. As a result, instead of using existing metrics, new metrics are proposed frequently, and privacy studies are often incomparable. In this survey we alleviate these problems by structuring the landscape of privacy metrics. To this end, we explain and discuss a selection of over eighty privacy metrics and introduce categorizations based on the aspect of privacy they measure, their required inputs, and the type of data that needs protection. In addition, we present a method on how to choose privacy metrics based on nine questions that help identify the right privacy metrics for a given scenario, and highlight topics where additional work on privacy metrics is needed. Our survey spans multiple privacy domains and can be understood as a general framework for privacy measurement

Privacy Analysis of Online and Offline Systems

How to protect people's privacy when our life are banded together with smart devices online and offline? For offline systems like smartphones, we often have a passcode to prevent others accessing to our personal data. Shoulder-surfing attacks to predict the passcode by humans are shown to not be accurate. We thus propose an automated algorithm to accurately predict the passcode entered by a victim on her smartphone by recording the video. Our proposed algorithm is able to predict over 92% of numbers entered in fewer than 75 seconds with training performed once.For online systems like surfing on Internet, anonymous communications networks like Tor can help encrypting the traffic data to reduce the possibility of losing our privacy. Each Tor client telescopically builds a circuit by choosing three Tor relays and then uses that circuit to connect to a server. The Tor relay selection algorithm makes sure that no two relays with the same /16 IP address or Autonomous System (AS) are chosen. Our objective is to determine the popularity of Tor relays when building circuits. With over 44 vantage points and over 145,000 circuits built, we found that some Tor relays are chosen more often than others. Although a completely balanced selection algorithm is not possible, analysis of our dataset shows that some Tor relays are over 3 times more likely to be chosen than others. An adversary could potentially eavesdrop or correlate more Tor traffic.Further more, the effectiveness of website fingerprinting (WF) has been shown to have an accuracy of over 90% when using Tor as the anonymity network. The common assumption in previous work is that a victim is visiting one website at a time and has access to the complete network trace of that website. Our main concern about website fingerprinting is its practicality. Victims could visit another website in the middle of visiting one website (overlapping visits). Or an adversary may only get an incomplete network traffic trace. When two website visits are overlapping, the website fingerprinting accuracy falls dramatically. Using our proposed "sectioning" algorithm, the accuracy for predicting the website in overlapping visits improves from 22.80% to 70%. When part of the network trace is missing (either the beginning or the end), the accuracy when using our sectioning algorithm increases from 20% to over 60%

Privacy and Security Concerns Associated with mHealth Technologies: A Computational Social Science Approach

mHealth technologies seek to improve personal wellness; however, there are still significant privacy and security challenges. The purpose of this study is to analyze tweets through social media mining to understand user-reported concerns associated with mHealth devices. Triangulation was conducted on a representative sample to confirm the results of the topic modeling using manual coding. The results of the emotion analysis showed 67% of the posts were largely associated with anger and fear, while 71% revealed an overall negative sentiment. The findings demonstrate the viability of leveraging computational techniques to understand the social phenomenon in question and confirm concerns such as accessibility of data, lack of data protection, surveillance, misuse of data, and unclear policies. Further, the results extend existing findings by highlighting critical concerns such as users’ distrust of these mHealth hosting companies and the inherent lack of data control

Mitigating Intersection Attacks in Anonymous Microblogging

Anonymous microblogging systems are known to be vulnerable to intersection attacks due to network churn. An adversary that monitors all communications can leverage the churn to learn who is publishing what with increasing confidence over time. In this paper, we propose a protocol for mitigating intersection attacks in anonymous microblogging systems by grouping users into anonymity sets based on similarities in their publishing behavior. The protocol provides a configurable communication schedule for users in each set to manage the inevitable trade-off between latency and bandwidth overhead. In our evaluation, we use real-world datasets from two popular microblogging platforms, Twitter and Reddit, to simulate user publishing behavior. The results demonstrate that the protocol can protect users against intersection attacks at low bandwidth overhead when the users adhere to communication schedules. In addition, the protocol can sustain a slow degradation in the size of the anonymity set over time under various churn rates

Web Password Recovery:A Necessary Evil?

Web password recovery, enabling a user who forgets their password to re-establish a shared secret with a website, is very widely implemented. However, use of such a fall-back system brings with it additional vulnerabilities to user authentication. This paper provides a framework within which such systems can be analysed systematically, and uses this to help gain a better understanding of how such systems are best implemented. To this end, a model for web password recovery is given, and existing techniques are documented and analysed within the context of this model. This leads naturally to a set of recommendations governing how such systems should be implemented to maximise security. A range of issues for further research are also highlighted.Comment: v2. Revised versio