arXiv subjects

Dan Boneh

Publications and source records attributed to Dan Boneh.

48 records · Page 3Linked to original sources

arXiv2017

Certificate Transparency with Privacy

Certificate transparency (CT) is an elegant mechanism designed to detect when a certificate authority (CA) has issued a certificate incorrectly. Many CAs now support CT and it is being actively deployed in browsers. However, a number of privacy-related challenges remain. In this paper we propose practical solutions to two issues. First, we develop a mechanism that enables web browsers to audit a CT log without violating user privacy. Second, we extend CT to support non-public subdomains.

cs.CR↗

arXiv2017

The Space of Transferable Adversarial Examples

Adversarial examples are maliciously perturbed inputs designed to mislead machine learning (ML) models at test-time. They often transfer: the same adversarial example fools more than one model. In this work, we propose novel methods for estimating the previously unknown dimensionality of the space of adversarial inputs. We find that adversarial examples span a contiguous subspace of large (~25) dimensionality. Adversarial subspaces with higher dimensionality are more likely to intersect. We find that for two different models, a significant fraction of their subspaces is shared, thus enabling transferability. In the first quantitative analysis of the similarity of different models' decision boundaries, we show that these boundaries are actually close in arbitrary directions, whether adversarial or benign. We conclude by formally studying the limits of transferability. We derive (1) sufficient conditions on the data distribution that imply transferability for simple model classes and (2) examples of scenarios in which transfer does not occur. These findings indicate that it may be possible to design defenses against transfer-based attacks, even for models that are vulnerable to direct attacks.

stat.ML↗

arXiv2017

Prio: Private, Robust, and Scalable Computation of Aggregate Statistics

This paper presents Prio, a privacy-preserving system for the collection of aggregate statistics. Each Prio client holds a private data value (e.g., its current location), and a small set of servers compute statistical functions over the values of all clients (e.g., the most popular location). As long as at least one server is honest, the Prio servers learn nearly nothing about the clients' private data, except what they can infer from the aggregate statistics that the system computes. To protect functionality in the face of faulty or malicious clients, Prio uses secret-shared non-interactive proofs (SNIPs), a new cryptographic technique that yields a hundred-fold performance improvement over conventional zero-knowledge approaches. Prio extends classic private aggregation techniques to enable the collection of a large class of useful statistics. For example, Prio can perform a least-squares regression on high-dimensional client-provided data without ever seeing the data in the clear.

cs.CR↗

arXiv2017

Privacy, Discovery, and Authentication for the Internet of Things

Automatic service discovery is essential to realizing the full potential of the Internet of Things (IoT). While discovery protocols like Multicast DNS, Apple AirDrop, and Bluetooth Low Energy have gained widespread adoption across both IoT and mobile devices, most of these protocols do not offer any form of privacy control for the service, and often leak sensitive information such as service type, device hostname, device owner's identity, and more in the clear. To address the need for better privacy in both the IoT and the mobile landscape, we develop two protocols for private service discovery and private mutual authentication. Our protocols provide private and authentic service advertisements, zero round-trip (0-RTT) mutual authentication, and are provably secure in the Canetti-Krawczyk key-exchange model. In contrast to alternatives, our protocols are lightweight and require minimal modification to existing key-exchange protocols. We integrate our protocols into an existing open-source distributed applications framework, and provide benchmarks on multiple hardware platforms: Intel Edisons, Raspberry Pis, smartphones, laptops, and desktops. Finally, we discuss some privacy limitations of the Apple AirDrop protocol (a peer-to-peer file sharing mechanism) and show how to improve the privacy of Apple AirDrop using our private mutual authentication protocol.

cs.CR↗

arXiv2015

Robust and Efficient Elimination of Cache and Timing Side Channels

Timing and cache side channels provide powerful attacks against many sensitive operations including cryptographic implementations. Existing defenses cannot protect against all classes of such attacks without incurring prohibitive performance overhead. A popular strategy for defending against all classes of these attacks is to modify the implementation so that the timing and cache access patterns of every hardware instruction is independent of the secret inputs. However, this solution is architecture-specific, brittle, and difficult to get right. In this paper, we propose and evaluate a robust low-overhead technique for mitigating timing and cache channels. Our solution requires only minimal source code changes and works across multiple languages/platforms. We report the experimental results of applying our solution to protect several C, C++, and Java programs. Our results demonstrate that our solution successfully eliminates the timing and cache side-channel leaks while incurring significantly lower performance overhead than existing approaches.

cs.CR↗

arXiv2015

PowerSpy: Location Tracking using Mobile Device Power Analysis

Modern mobile platforms like Android enable applications to read aggregate power usage on the phone. This information is considered harmless and reading it requires no user permission or notification. We show that by simply reading the phone's aggregate power consumption over a period of a few minutes an application can learn information about the user's location. Aggregate phone power consumption data is extremely noisy due to the multitude of components and applications that simultaneously consume power. Nevertheless, by using machine learning algorithms we are able to successfully infer the phone's location. We discuss several ways in which this privacy leak can be remedied.

cs.CR↗

arXiv2015

Stickler: Defending Against Malicious CDNs in an Unmodified Browser

Website publishers can derive enormous performance benefits and cost savings by directing traffic to their sites through content distribution networks (CDNs). However, publishers who use CDNs today must trust their CDN not to modify the site's JavaScript, CSS, images or other media en route to end users. A CDN that violates this trust could inject ads into websites, downsample media to save bandwidth or, worse, inject malicious JavaScript code to steal user secrets it could not otherwise access. We present Stickler, a system for website publishers that guarantees the end-to-end authenticity of content served to end users while simultaneously allowing publishers to reap the benefits of CDNs. Crucially, Stickler achieves these guarantees without requiring modifications to the browser.

cs.CR↗

arXiv2014

Cryptographically Enforced Control Flow Integrity

Recent Pwn2Own competitions have demonstrated the continued effectiveness of control hijacking attacks despite deployed countermeasures including stack canaries and ASLR. A powerful defense called Control flow Integrity (CFI) offers a principled approach to preventing such attacks. However, prior CFI implementations use static analysis and must limit protection to remain practical. These limitations have enabled attacks against all known CFI systems, as demonstrated in recent work. This paper presents a cryptographic approach to control flow integrity (CCFI) that is both fine-grain and practical: using message authentication codes (MAC) to protect control flow elements such as return addresses, function pointers, and vtable pointers. MACs on these elements prevent even powerful attackers with random read/write access to memory from tampering with program control flow. We implemented CCFI in Clang/LLVM, taking advantage of recently available cryptographic CPU instructions. We evaluate our system on several large software packages (including nginx, Apache and memcache) as well as all their dependencies. The cost of protection ranges from a 3-18% decrease in request rate.

cs.CR↗

arXiv2014

Mobile Device Identification via Sensor Fingerprinting

We demonstrate how the multitude of sensors on a smartphone can be used to construct a reliable hardware fingerprint of the phone. Such a fingerprint can be used to de-anonymize mobile devices as they connect to web sites, and as a second factor in identifying legitimate users to a remote server. We present two implementations: one based on analyzing the frequency response of the speakerphone-microphone system, and another based on analyzing device-specific accelerometer calibration errors. Our accelerometer-based fingerprint is especially interesting because the accelerometer is accessible via JavaScript running in a mobile web browser without requesting any permissions or notifying the user. We present the results of the most extensive sensor fingerprinting experiment done to date, which measured sensor properties from over 10,000 mobile devices. We show that the entropy from sensor fingerprinting is sufficient to uniquely identify a device among thousands of devices, with low probability of collision.

cs.CR↗

arXiv2014

Ensuring High-Quality Randomness in Cryptographic Key Generation

The security of any cryptosystem relies on the secrecy of the system's secret keys. Yet, recent experimental work demonstrates that tens of thousands of devices on the Internet use RSA and DSA secrets drawn from a small pool of candidate values. As a result, an adversary can derive the device's secret keys without breaking the underlying cryptosystem. We introduce a new threat model, under which there is a systemic solution to such randomness flaws. In our model, when a device generates a cryptographic key, it incorporates some random values from an entropy authority into its cryptographic secrets and then proves to the authority, using zero-knowledge-proof techniques, that it performed this operation correctly. By presenting an entropy-authority-signed public-key certificate to a third party (like a certificate authority or SSH client), the device can demonstrate that its public key incorporates randomness from the authority and is therefore drawn from a large pool of candidate values. Where possible, our protocol protects against eavesdroppers, entropy authority misbehavior, and devices attempting to discredit the entropy authority. To demonstrate the practicality of our protocol, we have implemented and evaluated its performance on a commodity wireless home router. When running on a home router, our protocol incurs a 2.1x slowdown over conventional RSA key generation and it incurs a 4.4x slowdown over conventional EC-DSA key generation.

cs.CR↗

arXiv2012

A Critical Look at Decentralized Personal Data Architectures

While the Internet was conceived as a decentralized network, the most widely used web applications today tend toward centralization. Control increasingly rests with centralized service providers who, as a consequence, have also amassed unprecedented amounts of data about the behaviors and personalities of individuals. Developers, regulators, and consumer advocates have looked to alternative decentralized architectures as the natural response to threats posed by these centralized services. The result has been a great variety of solutions that include personal data stores (PDS), infomediaries, Vendor Relationship Management (VRM) systems, and federated and distributed social networks. And yet, for all these efforts, decentralized personal data architectures have seen little adoption. This position paper attempts to account for these failures, challenging the accepted wisdom in the web community on the feasibility and desirability of these approaches. We start with a historical discussion of the development of various categories of decentralized personal data architectures. Then we survey the main ideas to illustrate the common themes among these efforts. We tease apart the design characteristics of these systems from the social values that they (are intended to) promote. We use this understanding to point out numerous drawbacks of the decentralization paradigm, some inherent and others incidental. We end with recommendations for designers of these systems for working towards goals that are achievable, but perhaps more limited in scope and ambition.

cs.CY↗

arXiv2012

Random Oracles in a Quantum World

The interest in post-quantum cryptography - classical systems that remain secure in the presence of a quantum adversary - has generated elegant proposals for new cryptosystems. Some of these systems are set in the random oracle model and are proven secure relative to adversaries that have classical access to the random oracle. We argue that to prove post-quantum security one needs to prove security in the quantum-accessible random oracle model where the adversary can query the random oracle with quantum states. We begin by separating the classical and quantum-accessible random oracle models by presenting a scheme that is secure when the adversary is given classical access to the random oracle, but is insecure when the adversary can make quantum oracle queries. We then set out to develop generic conditions under which a classical random oracle proof implies security in the quantum-accessible random oracle model. We introduce the concept of a history-free reduction which is a category of classical random oracle reductions that basically determine oracle answers independently of the history of previous queries, and we prove that such reductions imply security in the quantum model. We then show that certain post-quantum proposals, including ones based on lattices, can be proven secure using history-free reductions and are therefore post-quantum secure. We conclude with a rich set of open problems in this area.

quant-ph↗