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E-Mail Tracking

Interesting survey paper: on the privacy implications of e-mail tracking:

Abstract: We show that the simple act of viewing emails contains privacy pitfalls for the unwary. We assembled a corpus of commercial mailing-list emails, and find a network of hundreds of third parties that track email recipients via methods such as embedded pixels. About 30% of emails leak the recipient’s email address to one or more of these third parties when they are viewed. In the majority of cases, these leaks are intentional on the part of email senders, and further leaks occur if the recipient clicks links in emails. Mail servers and clients may employ a variety of defenses, but we analyze 16 servers and clients and find that they are far from comprehensive. We propose, prototype, and evaluate a new defense, namely stripping tracking tags from emails based on enhanced versions of existing web tracking protection lists.

Blog post on the research.

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Using Ultrasonic Beacons to Track Users

I’ve previously written about ad networks using ultrasonic communications to jump from one device to another. The idea is for devices like televisions to play ultrasonic codes in advertisements and for nearby smartphones to detect them. This way the two devices can be linked.

Creepy, yes. And also increasingly common, as this research demonstrates:

Privacy Threats through Ultrasonic Side Channels on Mobile Devices

by Daniel Arp, Erwin Quiring, Christian Wressnegger and Konrad Rieck

Abstract: Device tracking is a serious threat to the privacy of users, as it enables spying on their habits and activities. A recent practice embeds ultrasonic beacons in audio and tracks them using the microphone of mobile devices. This side channel allows an adversary to identify a user’s current location, spy on her TV viewing habits or link together her different mobile devices. In this paper, we explore the capabilities, the current prevalence and technical limitations of this new tracking technique based on three commercial tracking solutions. To this end, we develop detection approaches for ultrasonic beacons and Android applications capable of processing these. Our findings confirm our privacy concerns: We spot ultrasonic beacons in various web media content and detect signals in 4 of 35 stores in two European cities that are used for location tracking. While we do not find ultrasonic beacons in TV streams from 7 countries, we spot 234 Android applications that are constantly listening for ultrasonic beacons in the background without the user’s knowledge.

News article. BoingBoing post.

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Reading Analytics and Privacy

Interesting paper: “The rise of reading analytics and the emerging calculus of reading privacy in the digital world,” by Clifford Lynch:

Abstract: This paper studies emerging technologies for tracking reading behaviors (“reading analytics”) and their implications for reader privacy, attempting to place them in a historical context. It discusses what data is being collected, to whom it is available, and how it might be used by various interested parties (including authors). I explore means of tracking what’s being read, who is doing the reading, and how readers discover what they read. The paper includes two case studies: mass-market e-books (both directly acquired by readers and mediated by libraries) and scholarly journals (usually mediated by academic libraries); in the latter case I also provide examples of the implications of various authentication, authorization and access management practices on reader privacy. While legal issues are touched upon, the focus is generally pragmatic, emphasizing technology and marketplace practices. The article illustrates the way reader privacy concerns are shifting from government to commercial surveillance, and the interactions between government and the private sector in this area. The paper emphasizes U.S.-based developments.

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De-Anonymizing Browser History Using Social-Network Data

Interesting research: “De-anonymizing Web Browsing Data with Social Networks“:

Abstract: Can online trackers and network adversaries de-anonymize web browsing data readily available to them? We show — theoretically, via simulation, and through experiments on real user data — that de-identified web browsing histories can be linked to social media profiles using only publicly available data. Our approach is based on a simple observation: each person has a distinctive social network, and thus the set of links appearing in one’s feed is unique. Assuming users visit links in their feed with higher probability than a random user, browsing histories contain tell-tale marks of identity. We formalize this intuition by specifying a model of web browsing behavior and then deriving the maximum likelihood estimate of a user’s social profile. We evaluate this strategy on simulated browsing histories, and show that given a history with 30 links originating from Twitter, we can deduce the corresponding Twitter profile more than 50% of the time. To gauge the real-world effectiveness of this approach, we recruited nearly 400 people to donate their web browsing histories, and we were able to correctly identify more than 70% of them. We further show that several online trackers are embedded on sufficiently many websites to carry out this attack with high accuracy. Our theoretical contribution applies to any type of transactional data and is robust to noisy observations, generalizing a wide range of previous de-anonymization attacks. Finally, since our attack attempts to find the correct Twitter profile out of over 300 million candidates, it is — to our knowledge — the largest scale demonstrated de-anonymization to date.

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Firefox Removing Battery Status API

Firefox is removing the battery status API, citing privacy concerns. Here’s the paper that described those concerns:

Abstract. We highlight privacy risks associated with the HTML5 Battery Status API. We put special focus on its implementation in the Firefox browser. Our study shows that websites can discover the capacity of users’ batteries by exploiting the high precision readouts provided by Firefox on Linux. The capacity of the battery, as well as its level, expose a fingerprintable surface that can be used to track web users in short time intervals. Our analysis shows that the risk is much higher for old or used batteries with reduced capacities, as the battery capacity may potentially serve as a tracking identifier. The fingerprintable surface of the API could be drastically reduced without any loss in the API’s functionality by reducing the precision of the readings. We propose minor modifications to Battery Status API and its implementation in the Firefox browser to address the privacy issues presented in the study. Our bug report for Firefox was accepted and a fix is deployed.

W3C is updating the spec. Here’s a battery tracker found in the wild.

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Detecting When a Smartphone Has Been Compromised

Andrew “bunnie” Huang and Edward Snowden have designed a smartphone case that detects unauthorized transmissions by the phone. Paper. Three news articles.

Looks like a clever design. Of course, it has to be outside the device; otherwise, it could be compromised along with the device. Note that this is still in the research design stage; there are no public prototypes.

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