With the fast development in Cloud storage technologies and ever increasing use of Cloud data centres, data privacy and confidentiality has become a must. Indeed, Cloud data centres store each time more sensitive data such as personal data, organizational and enterprise data, transactional data, etc. However, achieving confidentiality with flexible searchable capability is a challenging issue. In this article, we show how to construct an efficient predicate encryption with fine-grained searchable capability. Predicate Encryption (PEPE) can achieve more sophisticated and flexible functionality compared with traditional public key encryption. We propose an efficient predicate encryption scheme by utilizing the dual system encryption technique, which can also be proved to be IND-AH-CPA (indistinguishable under chosen plain-text attack for attribute-hiding) secure without random oracle. We also carefully analyse the relationship between predicate encryption and searchable encryption. To that end, we introduce a new notion of Public-Key Encryption with Fine-grained Keyword Search (PEFKSPEFKS). Our results show that an IND-AH-CPA secure PE scheme can be used to construct an IND-PEFKS-CPA (indistinguishable under chosen plain-text attack for public-key encryption with fine-grained keyword search) secure PEFKSPEFKS scheme. A new transformation of PE-to-PEFKS is also proposed and used to construct an efficient PEFKSPEFKS scheme based on the transformation from the proposed PEPE scheme. Finally, we design a new framework for supporting privacy preserving predicate encryption with fine-grained searchable capability for Cloud storage. Compared to most prominent frameworks, our framework satisfies more features altogether and can serve as a basis for developing such frameworks for Cloud data centres.
Abadal, S.; Martinez, R.; Solé-Pareta, J.; Alarcon, E.; Albert Cabellos-Aparicio Computers and electrical engineering Vol. 51, p. 168-183 DOI: 10.1016/j.compeleceng.2015.12.018 Data de publicació: 2016-01-21 Article en revista
The scalability of Network-on-Chip (NoC) designs has become a rising concern as we enter the manycore era. Multicast support represents a particular yet relevant case within this context, mainly due to the poor performance of NoCs in the presence of this type of traffic. Multicast techniques are typically evaluated using synthetic traffic or within a full system, which is either simplistic or costly, given the lack of realistic traffic models that distinguish between unicast and multicast flows. To bridge this gap, this paper presents a trace-based multicast traffic characterization, which explores the scaling trends of aspects such as the multicast intensity or the spatiotemporal injection distribution for different coherence schemes. This analysis is the basis upon which the concept of multicast source prediction is proposed, and upon which a multicast traffic model is built. Both aspects pave the way for the development and accurate evaluation of advanced NoCs in the context of manycore computing.
This paper introduces a new approach for the implementation of randomly interconnected neural networks on hardware taking into account the length of the synapses. We divide the synapses into Long and Short according to the distance between the source and target neurons in a 2D mesh, and we demonstrate that it is possible to guarantee the latency of the Long synapses when they are routed through an additional layer which is based on hierarchical structures of Networks on Chip (NoC). The connection scheme consists in grouping neurons into four regions and communicating their sets of synapses between a pair of them, using circuit switching. In order to validate the interconnection scheme, we simulated the operation of this additional layer for two regions in a neuronal network with grid structure arrangement comprising 1.03 x 10(6) neurons, with a firing rate of 100 Hz and an average of 10(4) synapses per neuron. This pair of regions can support an average of 562 Long synapses per neuron, which is equivalent to managing 5% of the traffic generated by the grouped neurons, with the advantage of having the latency of the synapses guaranteed. A node of the one region has 30,528 neurons and operates with a throughput of 2.95 Millions of spikes per second (Mspk/s) approximately. In a complete operation, the additional layer has four regions and it would support 58 Mspk/s and 520,672 neurons of the network. (C) 2015 Elsevier Ltd. All rights reserved.
Manycore CMP systems are expected to grow to tens or even hundreds of cores. In this paper we show that the effective co-design of both, the network-on-chip and the coherence protocol, improves performance and power meanwhile total area resources remain bounded. We propose a snoopy-aware network-on-chip topology made of two mesh-of-tree topologies. Reducing the complexity of the coherence protocol - and hence its resources - and moving this complexity to the network, leads to a global decrease in power consumption meanwhile area is barely affected. Benefits of our proposal are due to the high-throughput and low delay of the network, but also due to the simplicity of the coherence protocol. The proposed network and protocol minimizes communication amongst cores when compared to traditional solutions based either on 2D-mesh topologies or in directory-based protocols.
The use of WiMAX cellular networks has arisen as a promising solution in order to provide broadband access over large, often shadowed, areas. As in other cellular networks, localization of users is extremely useful for many services and even essential for some civilian and/or military logistic operations. In a cellular WiMAX network, a node can obtain its position from beacons received by several cell base stations. Therefore, securing the localization method against potential false or erroneous feedback is of paramount importance in order to allow the nodes to get reliable position estimations. This fact implies not only making the localization method robust against erroneous or forged measurements, but also identifying which WiMAX base stations are providing such measurements. In this paper, we propose a robust localization method that can identify up to k malicious or misbehaving base stations and provide with an accurate estimation of the node position even in their presence. Simulation results prove that this proposal outperforms other existing detection techniques.
This paper introduces a wavelet denoising architecture with adaptive thresholding for real-time 1D-systems and without the use of external memories for storing input data or wavelet coefficients. The Discrete Wavelet Transform (DWT) is executed sample-by-sample by a polyphase scheme of the biorthogonal base 5/3. Since the weights of the filters are represented by integer terms and the quantization error is quasi-zero, the principle of Perfect Reconstruction is satisfied. The adaptive threshold is based on a real-time sorting process which calculates the median of the detail coefficients. Simulations are presented to measure the delay, latency, quantization error and hardware cost. A comparison with related works is also provided in order to show the strengths of the current proposal. The good trade-off among reconstruction error, latency, delay and hardware cost permits to use the proposed architecture in a wide variety of signals that require good fidelity and prompt response.
Real-time, embedded speech-in-speech hiding has not been widely researched. Nevertheless, it could be useful, among other cases, in secure mobile telephony. In this paper, we propose a new scheme of data hiding which takes advantage of the masking property of the Human Auditory System (HAS) to hide a secret (speech) signal into a host (speech) signal. The embedding process is carried out into the wavelet coefficients of the speech signals. The main point of the proposed scheme is that the embedding process is suitable for real-time processing, and the secret’s coefficients are relocated by an adaptive key, instead of a pseudo-noise sequence of some approaches. The latency of the embedding module makes this approach useful for real-time speech communication because the total delay added by the proposed system is low compared to the highest delay allowed for a high quality speech transmission
Real-time, embedded speech-in-speech hiding has not been widely researched. Nevertheless, it could be useful, among other cases, in secure mobile telephony. In this paper, we propose a new scheme of data hiding which takes advantage of the masking property of the Human Auditory System (HAS) to hide a secret (speech) signal into a host (speech) signal. The embedding process is carried out into the wavelet coefficients of the speech signals. The main point of the proposed scheme is that the embedding process is suitable for real-time processing, and the secret’s coefficients are relocated by an adaptive key, instead of a pseudo-noise sequence of some approaches. The latency of the embedding module makes this approach useful for real-time speech communication because the total delay added by the proposed system is low compared to the highest delay allowed for a high quality speech transmission.