International Conference on Computational Science and Its Applications 

About: International Conference on Computational Science and Its Applications is an academic conference. The conference publishes majorly in the area(s): Software & Computer science. Over the lifetime, 6716 publications have been published by the conference receiving 37861 citations.

Public Key Encryption with Keyword Search Revisited

Abstract: The public key encryption with keyword search (PEKS) scheme, proposed by Boneh, Di Crescenzo, Ostrovsky and Persiano, enables one to search for encrypted keywords without compromising the security of the original data. In this paper, we address two important issues of a PEKS scheme, "removing secure channel" and "refreshing keywords", which have not been considered in Boneh et al.'s paper. We point out the inefficiency of the original PEKS scheme due to the use of the secure channel. We resolve this problem by constructing an efficient PEKS scheme that removes a secure channel. We then argue that care must be taken when keywords are used frequently in the PEKS scheme as this situation might contradict the security of PEKS.

Computational Science and Its Applications – ICCSA 2004

Abstract: Human face detection plays an important role in applications such as video surveillance, human computer interface, face recognition, and face image database management. The face recognition by a CCD camera has the merit of being linked with other recognition systems such as an iris recognition to implement a multimodal recognition system. This paper is concerned with a new approach to face recognition that is automatically distinguished from moving pictures. Based on the research about recognition of color image by a CCD camera, we first find the proper value of color images in order to distinguish the tone of skin from other parts of face. Then, we look for the skin color among the regions of skin color converting RGB into Y , Cb, Cr to find skin parts of face. This new method can be applied to real-time biometric systems. We have developed the approach to face recognition with eigenface, focusing on the effects of eigenface to represent human face under several environment conditions. Finally an error rate is compared when face recognition is processed with facial features through the PCA (principal component analysis).

Automatic license plate recognition system based on color image processing

Abstract: A License plate recognition (LPR) system can be divided into the following steps: preprocessing, plate region extraction, plate region thresholding, character segmentation, character recognition and post-processing. For step 2, a combination of color and shape information of plate is used and a satisfactory extraction result is achieved. For step 3, first channel is selected, then threshold is computed and finally the region is thresholded. For step 4, the character is segmented along vertical, horizontal direction and some tentative optimizations are applied. For step 5, minimum Euclidean distance based template matching is used. And for those confusing characters such as '8' & 'B' and '0' & 'D', a special processing is necessary. And for the final step, validity is checked by machine and manual. The experiment performed by program based on aforementioned algorithms indicates that our LPR system based on color image processing is quite quick and accurate.

Big Data Clustering: A Review

Abstract: Clustering is an essential data mining and tool for analyzing big data. There are difficulties for applying clustering techniques to big data duo to new challenges that are raised with big data. As Big Data is referring to terabytes and petabytes of data and clustering algorithms are come with high computational costs, the question is how to cope with this problem and how to deploy clustering techniques to big data and get the results in a reasonable time. This study is aimed to review the trend and progress of clustering algorithms to cope with big data challenges from very first proposed algorithms until today’s novel solutions. The algorithms and the targeted challenges for producing improved clustering algorithms are introduced and analyzed, and afterward the possible future path for more advanced algorithms is illuminated based on today’s available technologies and frameworks.

Efficient authentication for low-cost RFID systems

Abstract: RFID (Radio Frequency Identification) technology is expected to play a critical role in identifying articles and serving the growing need to combat counterfeiting and fraud. However, the use of RFID tags may cause privacy violation of people holding an RFID tag. The main privacy concerns are information leakage of a tag, traceabiltiy of the person and impersonation of a tag. In this paper, we study authentication as a method to protect privacy, especially for low-cost RFID systems, which have much restrictions in limited computing power, low die-size, and low power requirements. Therefore, cost effective means of authentication is needed to deal with these problems effectively. We propose an authentication protocol, LCAP, which needs only two one-way hash function operations and hence is quite efficient. Leakage of information is prevented in the scheme since a tag emits its identifier only after authentication. By refreshing a identifier of a tag in each session, the scheme also provides a location privacy and can recover lost massages from many attacks such as spoofing attacks.