Boris Köpf

An information-theoretic model for adaptive side-channel attacks

We present a model of adaptive side-channel attacks which we combine with information-theoretic metrics to quantify the information revealed to an attacker. This allows us to express an attackers remaining uncertainty about a secret as a function of the number of side-channel measurements made. We present algorithms and approximation techniques for computing this measure. We also give examples of how they can be used to analyze the resistance of hardware implementations of cryptographic functions to both timing and power attacks.

Automatic Discovery and Quantification of Information Leaks

Information-flow analysis is a powerful technique for reasoning about the sensitive information exposed by a program during its execution. We present the first automatic method for information-flow analysis that discovers what information is leaked and computes its comprehensive quantitative interpretation. The leaked information is characterized by an equivalence relation on secret artifacts, and is represented by a logical assertion over the corresponding program variables. Our measurement procedure computes the number of discovered equivalence classes and their sizes. This provides a basis for computing a set of quantitative properties, which includes all established information-theoretic measures in quantitative information-flow. Our method exploits an inherent connection between formal models of qualitative information-flow and program verification techniques. We provide an implementation of our method that builds upon existing tools for program verification and information-theoretic analysis. Our experimental evaluation indicates the practical applicability of the presented method.

Probabilistic relational reasoning for differential privacy

Differential privacy is a notion of confidentiality that protects the privacy of individuals while allowing useful computations on their private data. Deriving differential privacy guarantees for real programs is a difficult and error-prone task that calls for principled approaches and tool support. Approaches based on linear types and static analysis have recently emerged; however, an increasing number of programs achieve privacy using techniques that cannot be analyzed by these approaches. Examples include programs that aim for weaker, approximate differential privacy guarantees, programs that use the Exponential mechanism, and randomized programs that achieve differential privacy without using any standard mechanism. Providing support for reasoning about the privacy of such programs has been an open problem. We report on CertiPriv, a machine-checked framework for reasoning about differential privacy built on top of the Coq proof assistant. The central component of CertiPriv is a quantitative extension of a probabilistic relational Hoare logic that enables one to derive differential privacy guarantees for programs from first principles. We demonstrate the expressiveness of CertiPriv using a number of examples whose formal analysis is out of the reach of previous techniques. In particular, we provide the first machine-checked proofs of correctness of the Laplacian and Exponential mechanisms and of the privacy of randomized and streaming algorithms from the recent literature.

Vulnerability Bounds and Leakage Resilience of Blinded Cryptography under Timing Attacks

We establish formal bounds for the number of min-entropy bits that can be extracted in a timing attack against a cryptosystem that is protected by blinding, the state-of-the art countermeasure against timing attacks. Compared with existing bounds, our bounds are both tighter and of greater operational significance, in that they directly address the key’s one-guess vulnerability. Moreover, we show that any semantically secure public-key cryptosystem remains semantically secure in the presence of timing attacks, if the implementation is protected by blinding and bucketing. This result shows that, by considering (and justifying) more optimistic models of leakage than recent proposals for leakage-resilient cryptosystems, one can achieve provable resistance against side-channel attacks for standard cryptographic primitives.

A Provably Secure and Efficient Countermeasure against Timing Attacks

We show that the amount of information about the key that an unknown-message attacker can extract from a deterministic side-channel is bounded from above by |O| log (n+1) bits, where n is the number of side-channel measurements and O is the set of possible observations. We use this bound to derive a novel countermeasure against timing attacks, where the strength of the security guarantee can be freely traded for the resulting performance penalty. We give algorithms that efficiently and optimally adjust this trade-off for given constraints on the side-channel leakage or on the efficiency of the cryptosystem. Finally, we perform a case-study that shows that applying our countermeasure leads to implementations with minor performance overhead and formal security guarantees.

Approximation and Randomization for Quantitative Information-Flow Analysis

Quantitative information-flow analysis (QIF) is an emerging technique for establishing information-theoretic confidentiality properties. Automation of QIF is an important step towards ensuring its practical applicability, since manual reasoning about program security has been shown to be a tedious and expensive task. Existing automated techniques for QIF fall short of providing full coverage of all program executions, especially in the presence of unbounded loops and data structures, which are notoriously difficult to analyze automatically. In this paper we propose a blend of approximation and randomization techniques to bear on the challenge of sufficiently precise, yet efficient computation of quantitative information flow properties. Our approach relies on a sampling method to enumerate large or unbounded secret spaces, and applies both static and dynamic program analysis techniques to deliver necessary over- and under-approximations of information-theoretic characteristics.

Fast and Simple Horizontal Coordinate Assignment

We present a simple, linear-time algorithm to determine horizontal coordinates in layered layouts subject to a given ordering within each layer. The algorithm is easy to implement and compares well with existing approaches in terms of assignment quality.

Automatic quantification of cache side-channels

The latency gap between caches and main memory has been successfully exploited for recovering sensitive input to programs, such as cryptographic keys from implementation of AES and RSA. So far, there are no practical general-purpose countermeasures against this threat. In this paper we propose a novel method for automatically deriving upper bounds on the amount of information about the input that an adversary can extract from a program by observing the CPUs cache behavior. At the heart of our approach is a novel technique for efficient counting of concretizations of abstract cache states that enables us to connect state-of-the-art techniques for static cache analysis and quantitative information-flow. We implement our counting procedure on top of the AbsInt TimingExplorer, one of the most advanced engines for static cache analysis. We use our tool to perform a case study where we derive upper bounds on the cache leakage of a 128-bit AES executable on an ARM processor. We also analyze this implementation with a commonly suggested (but until now heuristic) countermeasure applied, obtaining a formal account of the corresponding increase in security.

Information-Theoretic Bounds for Differentially Private Mechanisms

There are two active and independent lines of research that aim at quantifying the amount of information that is disclosed by computing on confidential data. Each line of research has developed its own notion of confidentiality: on the one hand, differential privacy is the emerging consensus guarantee used for privacy-preserving data analysis. On the other hand, information-theoretic notions of leakage are used for characterizing the confidentiality properties of programs in language-based settings. The purpose of this article is to establish formal connections between both notions of confidentiality, and to compare them in terms of the security guarantees they deliver. We obtain the following results. First, we establish upper bounds for the leakage of every eps-differentially private mechanism in terms of eps and the size of the mechanisms input domain. We achieve this by identifying and leveraging a connection to coding theory. Second, we construct a class of eps-differentially private channels whose leakage grows with the size of their input domains. Using these channels, we show that there cannot be domain-size-independent bounds for the leakage of all eps-differentially private mechanisms. Moreover, we perform an empirical evaluation that shows that the leakage of these channels almost matches our theoretical upper bounds, demonstrating the accuracy of these bounds. Finally, we show that the question of providing optimal upper bounds for the leakage of eps-differentially private mechanisms in terms of rational functions of eps is in fact decidable.

Visone Software for Visual Social Network Analysis

We are developing a social network tool that is powerful, comprehensive, and yet easy to use. The unique feature of our tool is the integration of network analysis and visualization. In a long-term interdisciplinary research collaboration, members of our group had implemented several prototypes to explore and demonstrate the feasibility of novel methods. These prototypes have been revised and combined into a stand-alone tool which will be extended regularly.