Efficient oblivious transfer with membership verification

tru

Revisiting Related-Key Boomerang attacks on AES using computer-aided tool

In recent years, several MILP models were introduced to search automatically for boomerang distinguishers and boomerang attacks on block ciphers. However, they can only be used when the key schedule is linear. Here, a new model is introduced to deal with nonlinear key schedules as it is the case for AES. This model is more complex and actually it is too slow for exhaustive search. However, when some hints are added to the solver, it found the current best related-key boomerang attack on AES-192 with $2^{124}$ time, $2^{124}$ data, and $2^{79.8}$ memory complexities, which is better than the one presented by Biryukov and Khovratovich at ASIACRYPT 2009 with complexities $2^{176}/2^{123}/2^{152}$ respectively. This represents a huge improvement for the time and memory complexity, illustrating the power of MILP in cryptanalysis

Conditional Proxy Broadcast Re-Encryption

A*STA

Improving Key-Recovery in Linear Attacks: Application to 28-Round PRESENT

International audienceLinear cryptanalysis is one of the most important tools in usefor the security evaluation of symmetric primitives. Many improvementsand refinements have been published since its introduction, and manyapplications on different ciphers have been found. Among these upgrades,Collard et al. proposed in 2007 an acceleration of the key-recovery partof Algorithm 2 for last-round attacks based on the FFT.In this paper we present a generalized, matrix-based version of the pre-vious algorithm which easily allows us to take into consideration an ar-bitrary number of key-recovery rounds. We also provide efficient variantsthat exploit the key-schedule relations and that can be combined withmultiple linear attacks.Using our algorithms we provide some new cryptanalysis on PRESENT,including, to the best of our knowledge, the first attack on 28 rounds

An Automated and Scalable Formal Process for Detecting Fault Injection Vulnerabilities in Binaries

Fault injection has increasingly been used both to attack software applications, and to test system robustness. Detecting fault injection vulnerabilities has been approached with a variety of different but limited methods. This paper proposes an extension of a recently published general model checking based process to detect fault injection vulnerabilities in binaries. This new extension makes the general process scalable to real-world implementions which is demonstrated by detecting vulnerabilities in different cryptographic implementations

Securing Abe\u27s Mix-net Against Malicious Verifiers via Witness Indistinguishability

We show that the simple and appealing unconditionally sound mix-net due to Abe (Asiacrypt\u2799) can be augmented to further guarantee anonymity against malicious verifiers. This additional guarantee implies, in particular, that when applying the Fiat-Shamir transform to the mix-net\u27s underlying sub-protocols, anonymity is provably guaranteed for {\em any} hash function. As our main contribution, we demonstrate how anonymity can be attained, even if most sub-protocols of a mix-net are merely witness indistinguishable (WI). We instantiate our framework with two variants of Abe\u27s mix-net. In the first variant, ElGamal ciphertexts are replaced by an alternative, yet equally efficient, lossy encryption scheme. In the second variant, new dummy vote ciphertexts are injected prior to the mixing process, and then removed. Our techniques center on new methods to introduce additional witnesses to the sub-protocols within the proof of security. This, in turn, enables us to leverage the WI guarantees against malicious verifiers. In our first instantiation, these witnesses follow somewhat naturally from the lossiness of the encryption scheme, whereas in our second instantiation they follow from leveraging combinatorial properties of the Benes-network. These approaches may be of independent interest. Finally, we demonstrate cases in Abe\u27s original mix-net (without modification) where only one witness exists, such that if the WI proof leaks information on the (single) witness in these cases, then the system will not be anonymous against malicious verifiers

Web attack risk awareness with lessons learned from high interaction honeypots

Tese de mestrado, Segurança Informática, Universidade de Lisboa, Faculdade de Ciências, 2009Com a evolução da web 2.0, a maioria das empresas elabora negócios através da Internet usando aplicações web. Estas aplicações detêm dados importantes com requisitos cruciais como confidencialidade, integridade e disponibilidade. A perda destas propriedades influencia directamente o negócio colocando-o em risco. A percepção de risco providencia o necessário conhecimento de modo a agir para a sua mitigação. Nesta tese foi concretizada uma colecção de honeypots web de alta interacção utilizando diversas aplicações e sistemas operativos para analisar o comportamento do atacante. A utilização de ambientes de virtualização assim como ferramentas de monitorização de honeypots amplamente utilizadas providencia a informação forense necessária para ajudar a comunidade de investigação no estudo do modus operandi do atacante, armazenando os últimos exploits e ferramentas maliciosas, e a desenvolver as necessárias medidas de protecção que lidam com a maioria das técnicas de ataque. Utilizando a informação detalhada de ataque obtida com os honeypots web, o comportamento do atacante é classificado entre diferentes perfis de ataque para poderem ser analisadas as medidas de mitigação de risco que lidam com as perdas de negócio. Diferentes frameworks de segurança são analisadas para avaliar os benefícios que os conceitos básicos de segurança dos honeypots podem trazer na resposta aos requisitos de cada uma e a consequente mitigação de risco.With the evolution of web 2.0, the majority of enterprises deploy their business over the Internet using web applications. These applications carry important data with crucial requirements such as confidentiality, integrity and availability. The loss of those properties influences directly the business putting it at risk. Risk awareness provides the necessary know-how on how to act to achieve its mitigation. In this thesis a collection of high interaction web honeypots is deployed using multiple applications and diverse operating systems in order to analyse the attacker behaviour. The use of virtualization environments along with widely used honeypot monitoring tools provide the necessary forensic information that helps the research community to study the modus operandi of the attacker gathering the latest exploits and malicious tools and to develop adequate safeguards that deal with the majority of attacking techniques. Using the detailed attacking information gathered with the web honeypots, the attacking behaviour will be classified across different attacking profiles to analyse the necessary risk mitigation safeguards to deal with business losses. Different security frameworks commonly used by enterprises are analysed to evaluate the benefits of the honeypots security concepts in responding to each framework’s requirements and consequently mitigating the risk