ECC-based lightweight authentication protocol with untraceability for low-cost RFID

Due to the potential wide deployment of Radio Frequency Identification (RFID), the security of RFID systems has drawn extensive attention from both academia and industry, and the RFID authentication protocol is an important mechanism in the security of RFID systems. The desired security requirements of RFID authentication protocols include privacy, integrity, authentication, anonymity/untraceability, and even availability. To design an efficient protocol that satisfies all the requirements with limited resources is a challenge. This paper proposes a new RFID authentication protocol based on Error Correction Codes (ECC). The proposed scheme has excellent performance in terms of security, efficiency, server’s maintenance, robustness, and cost. The tag only performs simple operations, such as random number generation and simple bitwise computations. The lightweight feature makes it attractive to those low-cost RFIDs that support only simple operations.     

An effective biometric cryptosystem combining fingerprints with error correction codes

With the emergence and popularity of identity verification means by biometrics, the biometric system which can assure security and privacy has received more and more concentration from both the research and industry communities. In the field of secure biometric authentication, one branch is to combine the biometrics and cryptography. Among all the solutions in this branch, fuzzy commitment scheme is a pioneer and effective security primitive. In this paper, we propose a novel binary length-fixed feature generation method of fingerprint. The alignment procedure, which is thought as a difficult task in the encrypted domain, is avoided in the proposed method due to the employment of minutiae triplets. Using the generated binary feature as input and based on fuzzy commitment scheme, we construct the biometric cryptosystems by combining various of error correction codes, including BCH code, a concatenated code of BCH code and Reed-Solomon code, and LDPC code. Experiments conducted on three fingerprint databases, including one in-house and two public domain, demonstrate that the proposed binary feature generation method is effective and promising, and the biometric cryptosystem constructed by the feature outperforms most of the existing biometric cryptosystems in terms of ZeroFAR and security strength. For instance, in the whole FVC2002 DB2, a 4.58% ZeroFAR is achieved by the proposed biometric cryptosystem with the security strength 48 bits.     

A more efficient and secure ID-based remote mutual authentication with key agreement scheme for mobile devices on elliptic curve cryptosystem

Recently, Yang and Chang proposed an identity-based remote login scheme using elliptic curve cryptography for the users of mobile devices. We have analyzed the security aspects of the Yang and Chang's scheme and identified some security flaws. Also two improvements of the Yang and Chang's scheme have been proposed recently, however, it has been found that the schemes have similar security flaws as in the Yang and Chang's scheme. In order to remove the security pitfalls of the Yang and Chang and the subsequent schemes, we proposed an enhanced remote user mutual authentication scheme that uses elliptic curve cryptography and identity-based cryptosystem with three-way challenge-response handshake technique. It supports flawless mutual authentication of participants, agreement of session key and the leaked key revocation capability. In addition, the proposed scheme possesses low power consumption, low computation cost and better security attributes. As a result, the proposed scheme seems to be more practical and suitable for mobile users for secure Internet banking, online shopping, online voting, etc.     

Simple and effective boundary correction for kernel densities and regression with an application to the world income and Engel curve estimation

In both nonparametric density estimation and regression, the so-called boundary effects, i.e. the bias and variance increase due to one sided data information, can be quite serious. For estimation performed on transformed variables this problem can easily get boosted and may distort substantially the final estimates, and consequently the conclusions. After a brief review of some existing methods a new, straightforward and very simple boundary correction is proposed, applying local bandwidth variation at the boundaries. The statistical behavior is discussed and the performance for density and regression estimation is studied for small and moderate sample sizes. In a simulation study this method is shown to perform very well. Furthermore, it appears to be excellent for estimating the world income distribution, and Engel curves in economics.