The Computer Journal, J. González Eds., Oxford Academic, 2012.
Information, vol. 12, issue 9, no. 357, MDPI, 08/2021.
Mobile Networks and Applications, Springer, In Press.
Requirements Engineering, vol. 18, issue 4, Springer London, pp. 321-341, Nov 2013. DOI (I.F.: 1.147)
Cloud applications entail the provision of a huge amount of heterogeneous, geographically-distributed resources managed and shared by many different stakeholders who often do not know each other beforehand. This raises numerous security concerns that, if not addressed carefully, might hinder the adoption of this promising computational model. Appropriately dealing with these threats gains special relevance in the social cloud context, where computational resources are provided by the users themselves. We argue that taking trust and reputation requirements into account can leverage security in these scenarios by incorporating the notions of trust relationships and reputation into them. For this reason, we propose a development framework onto which developers can implement trust-aware social cloud applications. Developers can also adapt the framework in order to accommodate their application-specific needs.
Journal of Network and Computer Applications, vol. 69, Elsevier, pp. 134-151, 04/2016. (I.F.: 3.500)
Computers & Security, vol. 45, Elsevier, pp. 186-198, 09/2014. DOI (I.F.: 1.031)
This paper introduces a sealed bid and multi-currency auction using secure multiparty computation (SMC).
Two boolean functions, a comparison and multiplication function, have been designed as required to apply SMC. These functions are applied without revealing any information, not even to trusted third parties such as the auctioneer. A type of Zero Knowledge proof, discreet proof, has been implemented with three variants, interactive, regular and reduced non interactive proofs. These proofs make it possible to verify the correctness of the functions whilst preserving the privacy of the bid values. Moreover, a system performance evaluation of the proposal has been realized on heterogeneous platforms, including a mobile platform. The evaluation concludes that our proposal is practical even on mobile platforms.
Mathematical and Computer Modelling, vol. 57, Elsevier, pp. 2583–2595, Jun 2013. DOI (I.F.: 2.02)
This work describes the design and implementation of an auction system using secure multiparty computation techniques. Our aim is to produce a system that is practical under actual field constraints on computation, memory, and communication. The underlying protocol is privacy-preserving, that is, the winning bid is determined without information about the losing bids leaking to either the auctioneer or other bidders. Practical implementation of the protocol is feasible using circuit-based cryptographic proofs along with additively homomorphic bit commitment. Moreover, we propose the development of a Proof Certificatestandard. These certificates convey sufficient information to recreate the cryptographic proofs and verify them offline.
IEEE Access , IEEE, 2022. DOI (I.F.: 3.367)
Neural networks based cryptography has seen a significant growth since the introduction of adversarial cryptography which makes use of Generative Adversarial Networks (GANs) to build neural networks that can learn encryption. The encryption has been proven weak at first but many follow up works have shown that the neural networks can be made to learn the One Time Pad (OTP) and produce perfectly secure ciphertexts. To the best of our knowledge, existing works only considered communications between two or three parties. In this paper, we show how multiple neural networks in an adversarial setup can remotely synchronize and establish a perfectly secure communication in the presence of different attackers eavesdropping their communication. As an application, we show how to build Secret Sharing Scheme based on this perfectly secure multi-party communication. The results show that it takes around 45,000 training steps for 4 neural networks to synchronize and reach equilibria. When reaching equilibria, all the neural networks are able to communicate between each other and the attackers are not able to break the ciphertexts exchanged between them.
International Journal of Information Security (IJIS), vol. 3, no. 2, Springer, pp. 99-112, 2004.
The protection of software applications is one of the most important problems to solve in information security because it has a crucial effect on other security issues.We can find in the literature many research initiatives that have tried to solve this problem, many of them based on the use of tamperproof hardware tokens. This type of solutions depends on two basic premises: (i) to increase the physical security by using tamperproof devices, and (ii) to increase the complexity of the analysis of the software. The first premise is reasonable. The second one is certainly related to the first one. In fact, its main goal is that the pirate user can not modify the software to bypass an operation that is crucial: checking the presence of the token. However, the experience shows that the second premise is not realistic because the analysis of the executable code is always possible. Moreover, the techniques used to obstruct the analysis process are not enough to discourage an attacker with average resources. In this paper, we review the most relevant works related to software protection, present a taxonomy of those works and, most important, we introduce a new and robust software protection scheme. This solution, called SmartProt, is based on the use of smart cards and cryptographic techniques, and its security relies only on the first of previous premises; that is, Smartprot has been designed to avoid attacks based on code analysis and software modification. The entire system is described following a lifecycle approach, explaining in detail the card setup, production, authorization, and execution phases. We also present some interesting applications of Smart- Prot as well as the protocols developed to manage licenses. Finally, we provide an analysis of its implementation details.