Identification with imperfect instruments

Dealing with endogenous regressors is a central challenge of applied research. The standard solution is to use instrumental variables that are assumed to be uncorrelated with unobservables. We instead assume (i) the correlation between the instrument and the error term has the same sign as the correlation between the endogenous regressor and the error term, and (ii) that the instrument is less correlated with the error term than is the endogenous regressor. Using these assumptions, we derive analytic bounds for the parameters. We demonstrate the method in two applications.

ObliviSync: Practical Oblivious File Backup and Synchronization

Oblivious RAM (ORAM) protocols are powerful techniques that hide a client's data as well as access patterns from untrusted service providers. We present an oblivious cloud storage system, ObliviSync, that specifically targets one of the most widely-used personal cloud storage paradigms: synchronization and backup services, popular examples of which are Dropbox, iCloud Drive, and Google Drive. This setting provides a unique opportunity because the above privacy properties can be achieved with a simpler form of ORAM called write-only ORAM, which allows for dramatically increased efficiency compared to related work. Our solution is asymptotically optimal and practically efficient, with a small constant overhead of approximately 4x compared with non-private file storage, depending only on the total data size and parameters chosen according to the usage rate, and not on the number or size of individual files. Our construction also offers protection against timing-channel attacks, which has not been previously considered in ORAM protocols. We built and evaluated a full implementation of ObliviSync that supports multiple simultaneous read-only clients and a single concurrent read/write client whose edits automatically and seamlessly propagate to the readers. We show that our system functions under high work loads, with realistic file size distributions, and with small additional latency (as compared to a baseline encrypted file system) when paired with Dropbox as the synchronization service.Comment: 15 pages. Accepted to NDSS 201

Identification with imperfect instruments

Dealing with endogenous regressors is a central challenge of applied research. The standard solution is to use instrumental variables that are assumed to be uncorrelated with unobservables. We instead assume (i) the correlation between the instrument and the error term has the same sign as the correlation between the endogenous regressor and the error term, and (ii) that the instrument is less correlated with the error term than is the endogenous regressor. Using these assumptions, we derive analytic bounds for the parameters. We demonstrate the method in two applications

Developing and evaluating a gestural and tactile mobile interface to support user authentication

As awareness grows surrounding the importance of protecting sensitive data, stored on or accessed through a mobile device, a need has been identified to develop authentication schemes which better match the needs of users, and are more resistant to observer attacks. This paper describes the design and evaluation of H4Plock (pronounced “Hap-lock”), a novel authentication mechanism to address the situation. In order to authenticate, the user enters up to four pre-selected on-screen gestures, informed by tactile prompts. The system has been designed in such a way that the sequence of gestures will vary on each authentication attempt, reducing the capability of a shoulder surfer to recreate entry. 94.1% of participants were able to properly authenticate using H4Plock, with 73.3% successfully accessing the system after a gap of five days without rehearsal. Only 23.5% of participants were able to successfully recreate passcodes in a video-based attack scenario, where gestures were unique in design and entered at different locations around the interface

Deterministic, Stash-Free Write-Only ORAM

Write-Only Oblivious RAM (WoORAM) protocols provide privacy by encrypting the contents of data and also hiding the pattern of write operations over that data. WoORAMs provide better privacy than plain encryption and better performance than more general ORAM schemes (which hide both writing and reading access patterns), and the write-oblivious setting has been applied to important applications of cloud storage synchronization and encrypted hidden volumes. In this paper, we introduce an entirely new technique for Write-Only ORAM, called DetWoORAM. Unlike previous solutions, DetWoORAM uses a deterministic, sequential writing pattern without the need for any "stashing" of blocks in local state when writes fail. Our protocol, while conceptually simple, provides substantial improvement over prior solutions, both asymptotically and experimentally. In particular, under typical settings the DetWoORAM writes only 2 blocks (sequentially) to backend memory for each block written to the device, which is optimal. We have implemented our solution using the BUSE (block device in user-space) module and tested DetWoORAM against both an encryption only baseline of dm-crypt and prior, randomized WoORAM solutions, measuring only a 3x-14x slowdown compared to an encryption-only baseline and around 6x-19x speedup compared to prior work

Towards Baselines for Shoulder Surfing on Mobile Authentication

Given the nature of mobile devices and unlock procedures, unlock authentication is a prime target for credential leaking via shoulder surfing, a form of an observation attack. While the research community has investigated solutions to minimize or prevent the threat of shoulder surfing, our understanding of how the attack performs on current systems is less well studied. In this paper, we describe a large online experiment (n=1173) that works towards establishing a baseline of shoulder surfing vulnerability for current unlock authentication systems. Using controlled video recordings of a victim entering in a set of 4- and 6-length PINs and Android unlock patterns on different phones from different angles, we asked participants to act as attackers, trying to determine the authentication input based on the observation. We find that 6-digit PINs are the most elusive attacking surface where a single observation leads to just 10.8% successful attacks, improving to 26.5\% with multiple observations. As a comparison, 6-length Android patterns, with one observation, suffered 64.2% attack rate and 79.9% with multiple observations. Removing feedback lines for patterns improves security from 35.3\% and 52.1\% for single and multiple observations, respectively. This evidence, as well as other results related to hand position, phone size, and observation angle, suggests the best and worst case scenarios related to shoulder surfing vulnerability which can both help inform users to improve their security choices, as well as establish baselines for researchers.Comment: Will appear in Annual Computer Security Applications Conference (ACSAC

RUST: A Retargetable Usability Testbed for Website Authentication Technologies

Website authentication technologies attempt to make the identity of a website clear to the user, by supplying information about the identity of the website. In practice however, usability issues can prevent users from correctly identifying the websites they are interacting with. To help identify usability issues we present RUST, a Retargetable USability Testbed for website authentication technologies. RUST is a testbed that consists of a test harness, which provides the ability to easily configure the environment for running usability study sessions, and a usability study design that evaluates usability based on spoofability, learnability, and acceptability. We present data collected by RUST and discuss preliminary results for two authentication technologies, Microsoft CardSpace and Verisign Secure Letterhead. Based on the data collected, we conclude that the testbed is useful for gathering data on a variety of technologies

DolphinAtack: Inaudible Voice Commands

Speech recognition (SR) systems such as Siri or Google Now have become an increasingly popular human-computer interaction method, and have turned various systems into voice controllable systems(VCS). Prior work on attacking VCS shows that the hidden voice commands that are incomprehensible to people can control the systems. Hidden voice commands, though hidden, are nonetheless audible. In this work, we design a completely inaudible attack, DolphinAttack, that modulates voice commands on ultrasonic carriers (e.g., f > 20 kHz) to achieve inaudibility. By leveraging the nonlinearity of the microphone circuits, the modulated low frequency audio commands can be successfully demodulated, recovered, and more importantly interpreted by the speech recognition systems. We validate DolphinAttack on popular speech recognition systems, including Siri, Google Now, Samsung S Voice, Huawei HiVoice, Cortana and Alexa. By injecting a sequence of inaudible voice commands, we show a few proof-of-concept attacks, which include activating Siri to initiate a FaceTime call on iPhone, activating Google Now to switch the phone to the airplane mode, and even manipulating the navigation system in an Audi automobile. We propose hardware and software defense solutions. We validate that it is feasible to detect DolphinAttack by classifying the audios using supported vector machine (SVM), and suggest to re-design voice controllable systems to be resilient to inaudible voice command attacks.Comment: 15 pages, 17 figure