16049143
Two-Pass ID-Based Authenticated Key Agreement Protocol with Key Confirmation Using Pairings
In the area of secure communications, key agreement is one of the most important issues. In this paper, a practical two-party ID-based authenticated key agreement protocol is proposed, which uses pairings on certain elliptic curves. An important advantage of our protocol is that it provides unilateral key confirmation to the protocol initiator only in two passes. We first put forward a variant of the ID-based signature scheme due to Sakai et al., then we describe our protocol, which uses the variant as a building block. We show that the newly proposed key agreement protocol is fit for real-world applications, and at the same time, it satisfies every desired security requirements of key agreement protocols
11681399
Security of an Efficient ID-Based Authenticated Key Agreement Protocol from Pairings
Authenticated key agreement protocols are essential for secure communications in open and distributed environments. In 2004, Ryu et al. proposed an efficient two-party identity-based authenticated key agreement protocol based on pairings. However, in this paper, we demonstrate that their protocol is vulnerable to a key-compromise impersonation attack. The attacking scenario is described in details. Furthermore,we point out that their protocol provides the property of deniability and at the same time it is the mechanism used to achieve deniability that allows the key-compromise impersonation attack.
15462956
Generalized Histogram Equalization Based on Local Characteristics
Histogram equalization (HE) and its variations have been widely used in image enhancement. Even though these approaches may enhance image contrast in an effective and efficient way, they usually face some undesired drawbacks, like loss of image details, noise amplification and over-enhancement. In this paper, we propose a generalized histogram equalization technique based on localized image analysis. Starting from designing two measures f1 and f2 to measure local characteristics around each pixel, the global statistics of these two local measures are then recorded into an extended histogram. Based on this extended histogram, we develop a procedure to generate suitable intensity transfer functions for various applications, like contrast enhancement and shadow enhancement. Experimental results show that the proposed algorithm provides a flexible and efficient way for image enhancement.
18781726
Watermarking scheme capable of resisting attacks based on availability of inserter
Attacks based on the presence ofwatermark inserter are easy to perf orm since they make use ofsimilarity between an original watermark and additionally added ones by using the same inserter and key. In this paper, a novel watermarking scheme capable ofresisting inserter attacks is proposed. Watermark signals corresponding to the same key are mutually independent ifthey are randomly selected using the described technique. Thus the inserter attack is invalidated. Performance ofthe proposed method is studied, and simulation experiments presented. ? 2002 Elsevier Science B.V. All rights reserved.
14774181
Nondifferentiable multiobjective programming under generalized d
Abstract In this paper, we are concerned with a nondifferentiable multiobjective programming problem with inequality constraints. We introduce four new classes of generalized convex functions by combining the concepts of weak strictly pseudoinvex, strong pseudoinvex, weak quasi invex, weak pseudoinvex and strong quasi invex functions in Aghezzaf and Hachimi [Numer. Funct. Anal. Optim. 22 (2001) 775], d -invex functions in Antczak [Europ. J. Oper. Res. 137 (2002) 28] and univex functions in Bector et al. [Univex functions and univex nonlinear programming, Proc. Admin. Sci. Assoc. Canada, 1992, p. 115]. By utilizing the new concepts, we derive a Karush–Kuhn–Tucker sufficient optimality condition and establish Mond–Weir type and general Mond–Weir type duality results for the nondifferentiable multiobjective programming problem.
15396849
Convex grouping combining boundary and region information
Convexity is an important geometric property of many natural and man-made structures. Prior research has shown that it is imperative to many perceptual-organization and image-understanding tasks. This paper presents a new grouping method for detecting convex structures from noisy images in a globally optimal fashion. Particularly, this method combines both region and boundary information: the detected structural boundary is closed and well aligned with detected edges while the enclosed region has good intensity homogeneity. We introduce a ratio-form cost function for measuring the structural desirability, which avoids a possible bias to detect small structures. A new fragment-pruning algorithm is developed to achieve the structural convexity. The proposed method can also be extended to detect open boundaries, which correspond to the structures that are partially cropped by the image perimeter and incorporate a human-computer interaction for detecting a convex boundary around a specified point. We test the proposed method on a set of real images and compare it with the Jacobs'convex-grouping method
1160887
An objective approach to cluster validation
Cluster validation is a major issue in cluster analysis. Many existing validity indices do not perform well when clusters overlap or there is significant variation in their covariance structure. The contribution of this paper is twofold. First, we propose a new validity index for fuzzy clustering. Second, we present a new approach for the objective evaluation of validity indices and clustering algorithms. Our validity index makes use of the covariance structure of clusters, while the evaluation approach utilizes a new concept of overlap rate that gives a formal measure of the difficulty of distinguishing between overlapping clusters. We have carried out experimental studies using data sets containing clusters of different shapes and densities and various overlap rates, in order to show how validity indices behave when clusters become less and less separable. Finally, the effectiveness of the new validity index is also demonstrated on a number of real-life data sets.