46716117
Public-Key Encryption from ID-Based Encryption Without One-Time Signature
Design a secure public key encryption scheme and its security proof are one of the main interests in cryptography In 2004, Canetti, Halevi and Katz [8] constructed a public key encryption (PKE) from a selective identity-based encryption scheme with a strong one-time signature scheme In 2005, Boneh and Katz [6] improved Canetti-Halevi-Katz construction by replacing a strong one-time signature with a message authentication code, but it is not publicly verifiable Later, Boyen, Mei and Waters [7] constructed PKE scheme directly from Waters' IBE scheme [17] , which is only secure against direct chosen-ciphertext attack and is not secure against adaptive chosen-ciphertext attack In 2006, Tan [16] further improved the efficiency of Canetti-Halevi-Katz (CHK) construction by directly from Boneh-Boyen identity based encryption (IBE) scheme [4] with a weak one-time signature In this paper, we construct an efficient public key encryption scheme without one-time signature, which preserves a publicly verifiable property and secure against adaptive chosen-ciphertext attack The construction of the proposed scheme is based on Boneh-Boyen identity-based encryption (IBE) scheme [2] and a trapdoor function We also show that the proposed scheme is more efficient than CHK construction.
39519625
A CCA2 Secure Key Encapsulation Scheme Based on 3rd Order Shift Registers
In 1998, Cramer and Shoup proposed the first practical and provable cryptosystem against adaptive chosen ciphertext attack under the standard assumption in the standard model, that is, decisional Diffie-Hellman assumption. Recently, Lucks extended the Cramer-Shoup cryptosystem to a group of quadratic residues modulo a composite number and showed that the scheme is provably secure in the standard model. In this paper, we extend Lucks' key encapsulation scheme to a third order linear feedback shift register and is based on a new assunmption which is called shift register based decisional Diffie-Hellman assumptions (SR-DDH). The proposed scheme is provably secure against adaptive chosen ciphertext attack based on the hardness of shift register based decisional Diffie-Hellman assumption in the standard model and not in random oracle model. Furthermore, the size of public key and ciphertext are shorter than Cramer-Shoup cryptosystem and the computational complexity is also more efficient than Cramer-Shoup cryptosystem and Lucks scheme.
11495874
A new electronic cash model
Credit card is currently the most popular electronic payment method on the Internet, but it is not an ideal method from the security and privacy point of view. Electronic cash solves many inherent problems of credit card, such as anonymity and off-line payment, and is widely accepted as an ideal electronic payment method. However, there are issues that are yet to be satisfactorily solved, such as fair traceability and double-spending prevention of off-line schemes. In this paper, we present a customer generated electronic cash model that offers unique trade-off between credit card and traditional off-line electronic cash systems. This model provides anonymity for customers and is technically more secure than credit card systems. It eliminates the withdrawal phase of electronic cash systems, thus it is more convenient for customers to use. In addition, fair traceability is provided in case crimes take place.
17840852
A secure signature scheme
Digital signature is commonly used for authentication. So, it is important to design a signature with a security proof. In 1999, Gennaro et al. and Cramer et al. respectively proposed practical and provably secure signature schemes under the standard assumption without the random oracle model. Since then, some provably secure signature schemes in the standard model were constructed, for example, Camenisch-Lysyanskaya scheme in 2002; Fischlin scheme and Tan-Yi-Siew scheme in 2003. In this paper, we construct a new provably secure signature scheme based on the strong RSA assumption against existential forgery under adaptive chosen message attack in the standard model. The proposed scheme is also more efficient than other provable secure schemes in the standard model.
14690689
Analysis of improved signcryption scheme with key privacy
In this paper, we analyse the Yang-Wong-Deng signcryption scheme [G. Yang, D.S. Wong, X. Deng, Analysis and improvement of a signcryption scheme with key privacy, in: Information Security Conference--ISC'05, in: Lecture Notes in Comput. Sci., vol. 3650, Springer-Verlag, Berlin, 2005, pp. 218-232] proposed in ISC'05, which is the improvement and enhancement of the security of Libert-Quisquater signcryption scheme [B. Libert, J.J. Quisquater, Efficient signcryption with key privacy from gap Diffie-Hellman groups, in: Public Key Cryptography--PKC'04, in: Lecture Notes in Comput. Sci., vol. 2947, Springer-Verlag, Berlin, 2004, pp. 187-200]. Although Yang et al. [G. Yang, D.S. Wong, X. Deng, Analysis and improvement of a signcryption scheme with key privacy, in: Information Security Conference--ISC'05, in: Lecture Notes in Comput. Sci., vol. 3650, Springer-Verlag, Berlin, 2005, pp. 218-232] proved that their scheme is secure against adaptive chosen ciphertext attacks and achieves ciphertext anonymity (which is also called key privacy) in the random oracle model; we disprove all their claims and show that their scheme is not semantically secure and does not achieve ciphertext anonymity.
42190700
Key Substitution Attacks on Provably Secure Short Signature Schemes
Recently, Boneh et al. proposed provably secure short signature schemes in the standard model and in the random oracle model respectively. In this letter, we propose strong-key substitution attacks on these signature schemes. In one of the attacks, we show that an adversary can generate a new public key satisfying all legitimate signatures created by the legitimate signer.
15017700
A Comparative Study on Chinese Text Categorization Methods
This paper reports our comparative evaluation of three machine learning methods on Chinese text categorization. Whereas a wide range of methods have been applied to English text categorization, relatively few studies have been done on Chinese text categorization. Based on a People's Daily news corpus, a series of controlled experiments evaluate three machine learning methods, namely k Nearest Neighbor (kNN) algorithm, Support Vector Machines (SVM), and Adaptive Resonance Associative Map (ARAM), in terms of their capabilities in mining categorization knowledge from high dimensional, sparse, and relatively noisy document feature vectors. Experiments reveal that all three methods produce satisfactory performance on the test corpus while ARAM exhibits a marginally better generalization capability, especially from relatively small and noisy training sets.
6434843
Bangla/English Script Identification Based on Analysis of Connected Component Profiles
Script identification is required for a multilingual OCR system. In this paper, we present a novel and efficient technique for Bangla/English script identification with applications to the destination address block of Bangladesh envelope images. The proposed approach is based upon the analysis of connected component profiles extracted from the destination address block images, however, it does not place any emphasis on the information provided by individual characters themselves and does not require any character/line segmentation. Experimental results demonstrate that the proposed technique is capable of identifying Bangla/English scripts on the real Bangladesh postal images.
18402501
An Empirical Investigation of the Auction Buyer's Choice to Buy Out or Bid: Cry of Regret or Laugh of Satisfaction?
Online auction buyers often face the predicament of choosing between the buyout strategy and the bidding strategy to acquire an auctioned product. A buyer who chooses to buy out will obtain the item immediately at the posted price while the one who chooses to bid will have to monitor the bidding process in the hope of acquiring the product at a price lower than the posted one. Despite the wealth of auction literature, relatively few studies empirically assess the buyout option. This study seeks to bridge the gap by investigating how the buyout option (permanent or temporary) and price parameters (starting price and buyout price) affect the formation of two emotions, namely anticipated satisfaction of choice and anticipated regret of outcome, which in turn affect the buying strategy (i.e., buy out or bid). We employ laboratory experiments in our study and our results indicate two interesting findings. First, when the permanent buyout option is available, a buyer is more likely to exhibit loss aversion characteristics and prefer to adopt the buyout strategy. Second, when the temporary buyout option is present, the thought that one could avoid premature ending of auction by exercising the bidding option at the start decreases one’s preference for adopting the buyout strategy. Implications of these results for further research and practice are discussed.
10764222
Camera Text Recognition based on Perspective Invariants
As camera resolution increases, high-speed non-contact text capture through a digital camera is opening up a new channel for document capture and understanding. Unfortunately, perspective and geometric distortions in camera image of documents make it hard to recognize the document content properly. In this paper, we propose a character recognition technique, which is capable of recognizing camera text lying over a planar or smoothly curved surface in perspective views. In our proposed method, a few perspective invariants including character ascender and descender, centroid intersection numbers, and water reservior are first detected. Camera texts are then recognized using a classification and regression tree (CART) structure. Experimental results show our method is fast and improves recognition performance greatly
9012238
Improved nearest neighbor based approach to accurate document skew estimation
The nearest-neighbor based document skew detection methods do not require the presence of a predominant text area, and are not subject to skew angle limitation. However, the accuracy of these methods is not perfect in general. In this paper, we present an improved nearest-neighbor based approach to perform accurate document skew estimation. Size restriction is introduced to the detection of nearest-neighbor pairs. Then the chains with a largest possible number of nearest-neighbor pairs are selected, and their slopes are computed to give the skew angle of document image. Experimental results on various types of documents containing different linguistic scripts and diverse layouts show that the proposed approach has achieved an improved accuracy for estimating document image skew angle and has an advantage of being language independent.