44251234
Efficient and Proactive Threshold Signcryption
To make the system more secure and robust, threshold schemes are proposed to avoid single point failure. At the same time, there are more and more applications which utilize the two basic blocks encryption and digital signature to secure message delivery (such as SSL, SSH). Combining the three tools organically leads to an interesting security tool termed as threshold signcryption which can be used in distributed systems especially the mobile networks. In this paper, we present an efficient threshold signcryption scheme. The scheme is designed for an asynchronous network model which may better present practical distributed systems, especially Internet or mobile ad hoc networks. In order to resist mobile attacks, we add proactive property to our scheme. To the best of our knowledge, the proposed scheme is the first threshold signcryption scheme which is noninteractive, proactive and provably secure and works on asynchronous network models.
28980752
Exploiting the Intrinsic Irreversibility of Adaptive Technologies to Enhance the Security of Digital Watermarking
To overcome the reversibility of the widely researched adaptive watermarking, the existing method based on cryptography is first directly revised for adaptive systems. The intrinsic irreversibility of some adaptive technologies is then disclosed and evaluated. Under these technologies, attackers have great difficulty dividing a released version into their claimed original data and scaled watermarks, and in the meantime making the latter be the particular adaptive results based on the former. Their reversed solutions are violently perturbed and perceptually unacceptable. The condition number of the coefficient matrix of the reverse equations can be employed to assess the degree of the perturbation. The proposed method is more efficient because it disposes of any cryptographic processing, such as hashing and stream generation. The experiments on images support the theoretic conclusion well.
18013503
An Efficient Asynchronous Proactive RSA Scheme
In this paper, we present an efficient asynchronous proactive RSA scheme. This paper has three contributions. Firstly, we present an asynchronous verifiable secret sharing protocol. Secondly, we propose an efficient asynchronous threshold RSA signature generation protocol. Thirdly, we propose an efficient asynchronous share refreshing protocol
195349585
Identity Based Conference Key Distribution Scheme from Parings
A conference key distribution system can provide a session key of a conference with more than three participants via network. In this paper,we propose an ID-based conference key distribution scheme from pairings. The proposed scheme provides user anonymity. At the same time, we also show that the proposed scheme is secure against replaying attacks and conspiratorial impersonation attacks.
12064638
SDD: Secure Distributed Diffusion Protocol for Sensor Networks
A sensor network is a collection of tiny sensor nodes, which consists of sensing, data processing and communicating components. Directed Diffusion is an important data-centric routing protocol of sensor networks. In this paper we present the design of a new secure Directed Diffusion protocol (SDD), which provides a secure extension for the Directed Diffusion protocol. We mainly focus on secure routing and give a simple scheme to securely diffuse data. We have not considered with the in-network aggregation as a goal. In order to support the use of SDD for sensor nodes with extremely limited CPU processing capability, we use an efficient one-way chain and do not use asymmetric cryptographic operations in this protocol. Our security analyses show that SDD is robust against any active attackers or compromised nodes in the network.
666073
A Feasible Baseline Architecture for Building and Evaluating Distributed Systems
Although distributed networks and systems are widely deployed, an effective overall benchmark architecture is still lacking. Recently we defined and studied the fat-stack network architecture and found that it is both efficient and scalable to distributed systems of various scales. In precedent work, we theoretically proved that the fat-stack is universal by measure of routing efficiency with a low 1.5-powered logarithmic overhead. Universality implies that the fat-stack of a given size is nearly the best routing network of that size. The fat-stack is also the minimal universal network in terms of number of links and nodes used. In this paper, we add more analytical proof and report our simulation results. Simulations show that the fat-stack outperforms a mesh-based distributed network of comparable hardware usage. We show how the fat-stack can be an effective benchmark architecture and how to scale the network from a VLSI graph layout to a large-scale distributed topology. Our work helps explain why some deployed networks function in the way they do in terms of routing. It also provides an exemplary network of proven efficiency and scalability for building new distributed systems.
35381627
Finding frequent items in data streams
We present a 1-pass algorithm for estimating the most frequent items in a data stream using limited storage space. Our method relies on a data structure called a COUNT SKETCH, which allows us to reliably estimate the frequencies of frequent items in the stream. Our algorithm achieves better space bounds than the previously known best algorithms for this problem for several natural distributions on the item frequencies. In addition, our algorithm leads directly to a 2-pass algorithm for the problem of estimating the items with the largest (absolute) change in frequency between two data streams. To our knowledge, this latter problem has not been previously studied in the literature.
34883067
Personalized News Reading via Hybrid Learning
In this paper, we present a personalized news reading prototype where latest news articles published by various on-line news providers are automatically collected, categorized and ranked in light of a user’s habits or interests. Moreover, our system can adapt itself towards a better performance. In order to develop such an adaptive system, we proposed a hybrid learning strategy; supervised learning is used to create an initial system configuration based on user’s feedbacks during registration, while an unsupervised learning scheme gradually updates the configuration by tracing the user’s behaviors as the system is being used. Simulation results demonstrate satisfactory performance.
18568401
Capture inter-speaker information with a neural network for speaker identification
Many speaker identification systems are created by model-based approaches, where a statistical model is used to characterize a speaker's voice and no inter-speaker information is used in parameter estimation. It is well known that inter-speaker information is very helpful in discrimination of different speakers. We propose a method for the use of inter-speaker information to improve performance of a model-based speaker identification system. A neural network is employed to capture inter-speaker information from output space of those statistical models. In order to sufficiently utilize inter-speaker information, a rival penalized encoding rule is proposed to design supervised learning pairs for training the neural network. Comparative results in the KING speech corpus show that our method leads to a considerable improvement for a model-based speaker identification system.
32262987
Speaker Modeling with Various Speech Representations
Although numerous speech representations have been reported to be useful in speaker recognition, there is much less agreement on which speech representation provides a perfect representation of speaker-specific information. In this paper, we charaterize a speaker’s identity through the simultaneous use of various speech representations of his/her voice. We present a parametric statistical model, generalized Gaussian mixture model, and develop an EM algorithm for parameter estimation. Our approach has been applied to speaker recognition and comparative results on KING corpus demonstrate its effectiveness.