8321087
Improvements on the WTLS protocol to avoid denial of service attacks
The current WTLS protocol is closely modeled after the well-studied SSL protocol. However, since some differences exist between these two protocols, even if the SSL protocol is secure, the WTLS protocol may not. We propose three kinds of possible Denial of Service (DoS) attacks on the existing WTLS protocol, which can be categorized into two types: memory exhaustion attacks and CPU exhaustion attacks. The first and the second kinds of attacks belong to memory exhaustion attacks, and the third kind of attack is a CPU exhaustion attack. Not only wireless network clients but also Internet clients can launch these three kinds of attacks, which are very simple and effective. Since Internet clients are more powerful in network bandwidth and CPU resources, damages made by these attackers are more serious, which can even make the WTLS server stop providing services for legitimate clients. Client cookies, client puzzles and an application timer is used to improve the current protocol, and our improvements are secure against such attacks.
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.
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.
3049349
Authenticating tripartite key agreement protocol with pairings
In this paper, an authenticated tripartite key agreement protocol is proposed, which is an ID-based one with pairings. This protocol involves only one round. The authenticity of the protocol is assured by a special signature scheme, so that messages carrying the information of two ephemeral keys can be broadcasted authentically by an entity. Consequently, one instance of the protocol results in eight session keys for three entities. In other word, one instance of the protocol generates a session key, which is eight times longer than those obtained from traditional key agreement protocols. Security attributes of the protocol are presented, and the computational overhead and bandwidth of the broadcast messages are analyzed as well.
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.
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.
206038276
Molecular Mechanics Calculations (MM2 and MM3) on Enamines and Aniline Derivatives
The MM2 and MM3 force fields have been extended to cover this class of compounds. Structures, vibrational spectra, and other data for 13 compounds were examined and can be reproduced satisfactorily by MM3. Except for the spectra, the other data can be reproduced somewhat less well by MM2. © 1994 by John Wiley & Sons, Inc.
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.
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.
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.