Lincoln, Yvonna, and Egon Guba, "Postpositivism and the Naturalist Paradigm," pp. 14-46 in Yvonna Lincoln and Egon Guba, Naturalistic Inquiry . Beverly Hills, CA: Sage, 1985.*

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

Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

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

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

Abstract Cell-site simulators, also known as IMSI-catchers and stingrays, are used around the world by governments and criminals to track and eavesdrop on cell phones. Despite extensive public debate surrounding their use, few hard facts about them are available. For example, the richest sources of information on U.S. government cell-site simulator usage are from anonymous leaks, public records requests, and court proceedings. This lack of concrete information and the difficulty of independently obtaining such information hampers the public discussion. To address this deficiency, we build, deploy, and evaluate SeaGlass, a city-wide cellsite simulator detection network. SeaGlass consists of sensors that measure and upload data on the cellular environment to find the signatures of portable cell-site simulators. SeaGlass sensors are designed to be robust, low-maintenance, and deployable in vehicles for long durations. The data they generate is used to learn a city’s network properties to find anomalies consistent with cell-site simulators. We installed SeaGlass sensors into 15 ridesharing vehicles across two cities, collecting two months of data in each city. Using this data, we evaluate the system and show how SeaGlass can be used to detect signatures of portable cell-site simulators. Finally, we evaluate our signature detection methods and discuss anomalies discovered in the data.

https://sciendo.com/pdf/10.1515/popets-2017-0027

SeaGlass: Enabling City-Wide IMSI-Catcher Detection

A configuration for encapsulating data that is unreadable after a predetermined timeout. To encapsulate data a random data key is generated and split into shares. A threshold number of shares are needed to reconstruct the key. The shares are stored at random locations within one or more networks. Each location is configured to delete the stored data after a predetermined time period. Encapsulated data is created by creating a vanishing data object (VDO) comprising the encrypted data, and data sufficient to locate at least a threshold number of key shares from their stored locations. The VDO becomes inaccessible after enough shares of the data are deleted such that the data key cannot be restored. However, if prior to timeout a sufficient number of data key shares are located and retrieved the data key can be reconstructed. The reconstructed data key is then used to decrypt the original data.

Encapsulation and decapsulation for data disintegration

Remote operating system fingerprinting relies on implementation differences between OSs to identify the specific variant executing on a remote host. Because these differences can be subtle and difficult to find, most fingerprinting tools require expert manual effort to construct discriminative fingerprints and classification models. In prior work, Caballero et al. proposed a promising technique to eliminate manual intervention: the automatic generation of fingerprints using an approach similar to fuzz testing [6]. Their work evaluated the technique in a small-scale, carefully controlled test environment. In this paper, we re-examine automatic OS fingerprinting in a more challenging large-scale scenario to better understand the viability of the technique. In contrast to the prior work, we find that automatic fingerprint generation suffers from several limitations and technical hurdles that can limit its effectiveness, particularly in more demanding, realistic environments.We use machine learning algorithms from the well-known Weka [11] data mining toolkit to automatically generate fingerprints over 329 different machine instances, and we compare the accuracy of our automatically generated fingerprints to Nmap. Our results suggest that overfitting to non-OS-specific behavioral differences, the indistinguishability of different OS variants, the biasing of an automatic tool to the makeup of the training data, and the lack of ability of an automatic tool to exploit protocol and software semantics significantly limit the usefulness of this technique in practice. Automatic techniques can help identify candidate signatures, but our results suggest that manual expertise will remain an integral part of fingerprint generation.

/pdf/the-limits-of-automatic-os-fingerprint-generation-4nfdcl3i6o.pdf

The limits of automatic OS fingerprint generation

The "cat-and-mouse" game of Internet censorship and circumvention cannot be won by capable technology alone. Instead, that technology must be available, comprehensible, and trustworthy to users. However, the field largely focuses only on censors and the technical means to circumvent them. Thailand, with its superlatives in Internet use and government information controls, offers a rich case study for exploring users' assessments of and interactions with censorship. We survey 229 and interview 13 Internet users in Thailand, and report on their current practices, experienced and perceived threats, and unresolved problems regarding censorship and digital security. Our findings indicate that existing circumvention tools were adequate for respondents to access blocked information, that respondents relied to some extent on risky tool selection and inaccurate assessment of blocked content, and that attempts to take action with sensitive content on social media led to the most concrete threats with the least available technical defenses. Based on these findings and in direct response to these problems, we make recommendations for shifting objectives in anti-censorship work, as well as for technical directions and future research to address users' on-the-ground needs.

Internet Censorship in Thailand: User Practices and Potential Threats

Computer security courses typically cover a breadth of technical topics, including threat modeling, applied cryptography, software security, and Web security. The technical artifacts of computer systems - and their associated computer security risks and defenses - do not exist in isolation, however; rather, these systems interact intimately with the needs, beliefs, and values of people. This is especially true as computers become more pervasive, embedding themselves not only into laptops, desktops, and the Web, but also into our cars, medical devices, and toys. Therefore, in addition to the standard technical material, we argue that students would benefit from developing a mindset focused on the broader societal and contextual issues surrounding computer security systems and risks. We used science fiction (SF) prototyping to facilitate such societal and contextual thinking in a recent undergraduate computer security course. We report on our approach and experiences here, as well as our recommendations for future computer security and other computer science courses.

/pdf/science-fiction-prototyping-and-security-education-2ybwwuc210.pdf

Tadayoshi Kohno

Papers

SeaGlass: Enabling City-Wide IMSI-Catcher Detection

Encapsulation and decapsulation for data disintegration

The limits of automatic OS fingerprint generation

Internet Censorship in Thailand: User Practices and Potential Threats

Science fiction prototyping and security education: cultivating contextual and societal thinking in computer security education and beyond