9581791
A genetic clustering method for intrusion detection
Traditional intrusion detection methods lack extensibility in face of changing network configurations as well as adaptability in face of unknown attack types. Meanwhile, current machine-learning algorithms need labeled data for training first, so they are computational expensive and sometimes misled by artificial data. In this paper, a new detection algorithm, the Intrusion Detection Based on Genetic Clustering (IDBGC) algorithm, is proposed. It can automatically establish clusters and detect intruders by labeling normal and abnormal groups. Computer simulations show that this algorithm is effective for intrusion detection.
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.
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.
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.
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.
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.
4274853
Lifting based discrete wavelet transform architecture for JPEG2000
A lifting based 1-D discrete wavelet transform (DWT) core is proposed. It is re-configurable for 5/3 and 9/7 filters in JPEG2000. Folded architecture is adopted to reduce the hardware cost and achieve the higher hardware utilization. Multiplication is realized in hardwired multiplier with coefficients represented in canonic signed-digit (CSD) form. It is a compact and efficient DWT core for the hardware implementation of JPEG2000 encoder.
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.
378309
Type-directed weaving of aspects for higher-order functional languages
Aspect-oriented programming (AOP) has been shown to be a useful model for software development. Special care must be taken when we try to adapt AOP to strongly typed functional languages which come with features like a type inference mechanism, polymorphic types, higher-order functions and type-scoped pointcuts. Our main contribution lies in a seamless integration of these two paradigms through a static weaving process which deals with around advices with type-scoped pointcuts in the presence of higher-order functions. We give a source-level type inference system for a higher-order, polymorphic language coupled with type-scoped pointcuts. The type system ensures that base programs are oblivious to the type of around advices. We present a type-directed translation scheme which resolves all advice applications at static time. The translation removes advice declarations from source programs and produces translated code which is typable in the Hindley-Milner system.
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.
9353133
Using information scent to model user information needs and actions and the Web
On the Web, users typically forage for information by navigating from page to page along Web links. Their surfing patterns or actions are guided by their information needs. Researchers need tools to explore the complex interactions between user needs, user actions, and the structures and contents of the Web. In this paper, we describe two computational methods for understanding the relationship between user needs and user actions. First, for a particular pattern of surfing, we seek to infer the associated information need. Second, given an information need, and some pages as starting pints, we attempt to predict the expected surfing patterns. The algorithms use a concept called “information scent”, which is the subjective sense of value and cost of accessing a page based on perceptual cues. We present an empirical evaluation of these two algorithms, and show their effectiveness.