41737256
On the noninvertibility of adaptive digital watermarking
This paper is intended to demonstrate that the widely researched adaptive watermarking is noninvertible in nature if it can induce and exploit the perturbation in an attacker's reverse engineering properly. The intrinsic noninvertibility of some adaptive watermarking is disclosed and evaluated. Under the technologies that exploit it, attackers have great difficulty dividing a released version into their claimed original and scaled watermark, and in the meantime making the latter be the particular adaptive result based on the former. Their reversed solutions are drastically perturbed and perceptually unacceptable. Compared with the existing noninvertible method based on cryptography, the proposed method is more efficient because it disposes of the cryptographic processing. Furthermore, it also shows a promising way of making a public watermarking scheme, which is considered intrinsically invertible, noninvertible.
875545
Multiplex Encryption: A Practical Approach to Encrypting Multi-recipient Emails
Efficiently protecting the privacy of multi-recipient emails is not as trivial as it seems. The approach proposed by S/MIME is to concatenate all ciphertexts. However, it suffers from poor scalability due to its linear computation and communication cost. In this paper, we propose a new practical and secure scheme, called multiplex encryption. By combining the ideas of identity-based mediated RSA and re-encryption mix network, our framework only requires constant computation and communication cost to encrypt a multi-recipient email.
39321946
Attacks on the (enhanced) Yang-Shieh authentication
The Yang-Shieh authentication is a time-stamp based password authentication scheme that uses smart cards [1]. In [2,3], various attacks on this scheme are described. However, an enhancement of the scheme is proposed in [3] and enables the scheme to resist these existing attacks. In this paper, we show two new attack that can break the enhanced scheme. We further point out that the fundamental computational assumption of the Yang-Shieh authentication scheme is incorrect.
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.
41230139
Comments on an access control model in semantic grid
In this note, we show that there are some significant design weaknesses in the access control model that proposed to address the convergence and consistence problems in semantic grid by Bu and Xu in a recent paper.
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.
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.
465165
Text-dependent speaker identification based on input/output HMMs: An empirical study
In this paper, we explore theInput/Output HMM (IOHMM) architecture for a substantial problem, that of text-dependent speaker identification. For subnetworks modeled with generalized linear models, we extend the IRLS algorithm to the M-step of the corresponding EM algorithm. Experimental results show that the improved EM algorithm yields significantly faster training than the original one. In comparison with the multilayer perceptron, the dynamic programming technique and hidden Markov models, we empirically demonstrate that the IOHMM architecture is a promising way to text-dependent speaker identification.
11647155
Methods of Combining Multiple Classifiers with Different Features and Their Applications to Text-Independent Speaker Identification
In practical applications of pattern recognition, there are often different features extracted from raw data which needs recognizing. Methods of combining multiple classifiers with different features are viewed as a general problem in various application areas of pattern recognition. In this paper, a systematic investigation has been made and possible solutions are classified into three frameworks, i.e. linear opinion pools, winner-take-all and evidential reasoning. For combining multiple classifiers with different features, a novel method is presented in the framework of linear opinion pools and a modified training algorithm for associative switch is also proposed in the framework of winner-take-all. In the framework of evidential reasoning, several typical methods are briefly reviewed for use. All aforementioned methods have already been applied to text-independent speaker identification. The simulations show that results yielded by the methods described in this paper are better than not only the individual classifiers' but also ones obtained by combining multiple classifiers with the same feature. It indicates that the use of combining multiple classifiers with different features is an effective way to attack the problem of text-independent speaker identification.
15814103
Fast and scalable multi-TCAM classification engine for wide policy table lookup
With the explosive growth of Internet traffic, the next generation switches are designed to provide forwarding speed up to 10 Gbps or above. To meet the challenges of delivering wire-speed deep packet inspection for various QoS requirements that making classification becomes the bottleneck of next generation high-speed switches. Ternary content addressable memory (TCAM) provides high-speed parallel comparison operations and is one of the best candidates to implement next-generation hardware-based packet classifiers. Single-TCAM-based solution with ultra-high density has the advantage of simple architecture, but may not be feasible due to the scalability issue; also it may not be fast enough to fulfill the wide-policy-rule classifications, especial for the IPv6-based packets. To provide scalable and deep packet inspection, this paper proposes the pipeline architecture with multiple TCAMs to obtain wire-speed classification for IPv6 and multimedia applications. An algorithm to solve ambiguous cases among the rules is also proposed. Based on the proposed mechanisms, the packet classification engine capable of handling multiple QoS requirements at ultra-high speed is presented.
10353520
Finding Self-Similarities in Opportunistic People Networks
Opportunistic network is a type of delay tolerant networks (DTN) where network communication opportunities appear opportunistic. In this study, we investigate opportunistic network scenarios based on public network traces, and our contributions are the following: First, we identify the censorship issue in network traces that usually leads to strongly skewed distribution of the measurements. Based on this knowledge, we then apply the Kaplan-Meier Estimator to calculate the survivorship of network measurements, which is used in designing our proposed censorship removal algorithm (CRA) that is used to recover censored data. Second, we perform a rich set of analysis illustrating that UCSD and Dartmouth network traces show strong self-similarity, and can be modeled as such. Third, we pointed out the importance of these newly revealed characteristics in future development and evaluation of opportunistic networks.