Attacks and Countermeasures for White-box Designs

In traditional symmetric cryptography, the adversary has access only to the inputs and outputs of a cryptographic primitive. In the white-box model the adversary is given full access to the implementation. He can use both static and dynamic analysis as well as fault analysis in order to break the cryptosystem, e.g. to extract the embedded secret key. Implementations secure in such model have many applications in industry. However, creating such implementations turns out to be a very challenging if not an impossible task. Recently, Bos et al. proposed a generic attack on white-box primitives called differential computation analysis (DCA). This attack was applied to many white-box implementations both from academia and industry. The attack comes from the area of side-channel analysis and the most common method protecting against such attacks is masking, which in turn is a form of secret sharing. In this paper we present multiple generic attacks against masked white-box implementations. We use the term “masking” in a very broad sense. As a result, we deduce new constraints that any secure white-box implementation must satisfy. Based on the new constraints, we develop a general method for protecting white-box implementations. We split the protection into two independent components: value hiding and structure hiding. Value hiding must pro- vide protection against passive DCA-style attacks that rely on analysis of computation traces. Structure hiding must provide protection against circuit analysis attacks. In this paper we focus on developing the value hiding component. It includes protection against the DCA attack by Bos et al. and protection against a new attack called algebraic attack. We present a provably secure first-order protection against the new al- gebraic attack. The protection is based on small gadgets implementing secure masked XOR and AND operations. Furthermore, we give a proof of compositional security allowing to freely combine secure gadgets. We derive concrete security bounds for circuits built using our construction

Attacks and Countermeasures for White-box Designs

In traditional symmetric cryptography, the adversary has access only to the inputs and outputs of a cryptographic primitive. In the white-box model the adversary is given full access to the implementation. He can use both static and dynamic analysis as well as fault analysis in order to break the cryptosystem, e.g. to extract the embedded secret key. Implementations secure in such model have many applications in industry. However, creating such implementations turns out to be a very challenging if not an impossible task. Recently, Bos et al. proposed a generic attack on white-box primitives called differential computation analysis (DCA). This attack was applied to many white-box implementations both from academia and industry. The attack comes from the area of side-channel analysis and the most common method protecting against such attacks is masking, which in turn is a form of secret sharing. In this paper we present multiple generic attacks against masked white-box implementations. We use the term “masking” in a very broad sense. As a result, we deduce new constraints that any secure white-box implementation must satisfy. Based on the new constraints, we develop a general method for protecting white-box implementations. We split the protection into two independent components: value hiding and structure hiding. Value hiding must pro- vide protection against passive DCA-style attacks that rely on analysis of computation traces. Structure hiding must provide protection against circuit analysis attacks. In this paper we focus on developing the value hiding component. It includes protection against the DCA attack by Bos et al. and protection against a new attack called algebraic attack. We present a provably secure first-order protection against the new al- gebraic attack. The protection is based on small gadgets implementing secure masked XOR and AND operations. Furthermore, we give a proof of compositional security allowing to freely combine secure gadgets. We derive concrete security bounds for circuits built using our construction

Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning

Learning-based pattern classifiers, including deep networks, have shown impressive performance in several application domains, ranging from computer vision to cybersecurity. However, it has also been shown that adversarial input perturbations carefully crafted either at training or at test time can easily subvert their predictions. The vulnerability of machine learning to such wild patterns (also referred to as adversarial examples), along with the design of suitable countermeasures, have been investigated in the research field of adversarial machine learning. In this work, we provide a thorough overview of the evolution of this research area over the last ten years and beyond, starting from pioneering, earlier work on the security of non-deep learning algorithms up to more recent work aimed to understand the security properties of deep learning algorithms, in the context of computer vision and cybersecurity tasks. We report interesting connections between these apparently-different lines of work, highlighting common misconceptions related to the security evaluation of machine-learning algorithms. We review the main threat models and attacks defined to this end, and discuss the main limitations of current work, along with the corresponding future challenges towards the design of more secure learning algorithms.Comment: Accepted for publication on Pattern Recognition, 201

CAPTCHaStar! A novel CAPTCHA based on interactive shape discovery

Over the last years, most websites on which users can register (e.g., email providers and social networks) adopted CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart) as a countermeasure against automated attacks. The battle of wits between designers and attackers of CAPTCHAs led to current ones being annoying and hard to solve for users, while still being vulnerable to automated attacks. In this paper, we propose CAPTCHaStar, a new image-based CAPTCHA that relies on user interaction. This novel CAPTCHA leverages the innate human ability to recognize shapes in a confused environment. We assess the effectiveness of our proposal for the two key aspects for CAPTCHAs, i.e., usability, and resiliency to automated attacks. In particular, we evaluated the usability, carrying out a thorough user study, and we tested the resiliency of our proposal against several types of automated attacks: traditional ones; designed ad-hoc for our proposal; and based on machine learning. Compared to the state of the art, our proposal is more user friendly (e.g., only some 35% of the users prefer current solutions, such as text-based CAPTCHAs) and more resilient to automated attacks.Comment: 15 page

On the Duality of Probing and Fault Attacks

In this work we investigate the problem of simultaneous privacy and integrity protection in cryptographic circuits. We consider a white-box scenario with a powerful, yet limited attacker. A concise metric for the level of probing and fault security is introduced, which is directly related to the capabilities of a realistic attacker. In order to investigate the interrelation of probing and fault security we introduce a common mathematical framework based on the formalism of information and coding theory. The framework unifies the known linear masking schemes. We proof a central theorem about the properties of linear codes which leads to optimal secret sharing schemes. These schemes provide the lower bound for the number of masks needed to counteract an attacker with a given strength. The new formalism reveals an intriguing duality principle between the problems of probing and fault security, and provides a unified view on privacy and integrity protection using error detecting codes. Finally, we introduce a new class of linear tamper-resistant codes. These are eligible to preserve security against an attacker mounting simultaneous probing and fault attacks

Analysis and Mitigation of Remote Side-Channel and Fault Attacks on the Electrical Level

In der fortlaufenden Miniaturisierung von integrierten Schaltungen werden physikalische Grenzen erreicht, wobei beispielsweise Einzelatomtransistoren eine mögliche untere Grenze für Strukturgrößen darstellen. Zudem ist die Herstellung der neuesten Generationen von Mikrochips heutzutage finanziell nur noch von großen, multinationalen Unternehmen zu stemmen. Aufgrund dieser Entwicklung ist Miniaturisierung nicht länger die treibende Kraft um die Leistung von elektronischen Komponenten weiter zu erhöhen. Stattdessen werden klassische Computerarchitekturen mit generischen Prozessoren weiterentwickelt zu heterogenen Systemen mit hoher Parallelität und speziellen Beschleunigern. Allerdings wird in diesen heterogenen Systemen auch der Schutz von privaten Daten gegen Angreifer zunehmend schwieriger. Neue Arten von Hardware-Komponenten, neue Arten von Anwendungen und eine allgemein erhöhte Komplexität sind einige der Faktoren, die die Sicherheit in solchen Systemen zur Herausforderung machen. Kryptografische Algorithmen sind oftmals nur unter bestimmten Annahmen über den Angreifer wirklich sicher. Es wird zum Beispiel oft angenommen, dass der Angreifer nur auf Eingaben und Ausgaben eines Moduls zugreifen kann, während interne Signale und Zwischenwerte verborgen sind. In echten Implementierungen zeigen jedoch Angriffe über Seitenkanäle und Faults die Grenzen dieses sogenannten Black-Box-Modells auf. Während bei Seitenkanalangriffen der Angreifer datenabhängige Messgrößen wie Stromverbrauch oder elektromagnetische Strahlung ausnutzt, wird bei Fault Angriffen aktiv in die Berechnungen eingegriffen, und die falschen Ausgabewerte zum Finden der geheimen Daten verwendet. Diese Art von Angriffen auf Implementierungen wurde ursprünglich nur im Kontext eines lokalen Angreifers mit Zugriff auf das Zielgerät behandelt. Jedoch haben bereits Angriffe, die auf der Messung der Zeit für bestimmte Speicherzugriffe basieren, gezeigt, dass die Bedrohung auch durch Angreifer mit Fernzugriff besteht. In dieser Arbeit wird die Bedrohung durch Seitenkanal- und Fault-Angriffe über Fernzugriff behandelt, welche eng mit der Entwicklung zu mehr heterogenen Systemen verknüpft sind. Ein Beispiel für neuartige Hardware im heterogenen Rechnen sind Field-Programmable Gate Arrays (FPGAs), mit welchen sich fast beliebige Schaltungen in programmierbarer Logik realisieren lassen. Diese Logik-Chips werden bereits jetzt als Beschleuniger sowohl in der Cloud als auch in Endgeräten eingesetzt. Allerdings wurde gezeigt, wie die Flexibilität dieser Beschleuniger zur Implementierung von Sensoren zur Abschätzung der Versorgungsspannung ausgenutzt werden kann. Zudem können durch eine spezielle Art der Aktivierung von großen Mengen an Logik Berechnungen in anderen Schaltungen für Fault Angriffe gestört werden. Diese Bedrohung wird hier beispielsweise durch die Erweiterung bestehender Angriffe weiter analysiert und es werden Strategien zur Absicherung dagegen entwickelt