Abstract

Protocols for Generalized Oblivious Transfer(GOT) were introduced by Ishai and Kushilevitz [10]. They built it by reducing GOT protocols to standard 1-out-of-2 oblivious transfer protocols based on private protocols. In our protocols, we provide alternative reduction by using secret sharing schemes instead of private protocols. We therefore show that there exist a natural correspondence between GOT and general secret sharing schemes and thus the techniques and tools developed for the latter can be applied equally well to the former.

Abstract

(URMT) problem, two non-faulty players, the sender S and the receiver R are part of a synchronous network modeled as a directed graph. S has a message that he wishes to send to R; the challenge is to design a protocol such that after exchanging messages as per the protocol, the receiver R should correctly obtain S’s message with arbitrarily small error probability δ, in spite of the influence of a Byzantine adversary that may actively corrupt up to t nodes in the network (we denote such a URMT protocol as (t,(1− δ))-reliable). While it is known that (2t+ 1) vertex disjoint directed paths from S to R are necessary and sufficient for (t, 1)-reliable URMT (that is with zero error probability), we prove that a strictly weaker condition, which we define and denote as (2t, t)-special-connectivity, together with just (t+ 1) vertex disjoint directed paths from S to R, is necessary and sufficient for (t,(1− δ))-reliable URMT with arbitrarily small (but non-zero) error probability, δ. Thus, we demonstrate the power of randomization in the context of reliable message transmission. In fact, for any positive integer k> 0, we show that there always exists a digraph Gk such that (k, 1)-reliable URMT is impossible over Gk whereas there exists a (2k,(1− δ))-reliable URMT protocol, δ> 0 in Gk. In a digraph G on which (t,(1− δ))-reliable URMT is possible, an edge is called critical if the deletion of that edge renders (t,(1− δ))-reliable URMT impossible. We give an example of a digraph G on n vertices such that G has Ω (n2) critical edges. This is quite baffling since no such graph exists for the case of perfect reliable message transmission (or equivalently (t, 1)-reliable URMT) or when the underlying graph is undirected. Such is the anomalous behavior of URMT protocols (when “randomness meet directedness”) that it makes it extremely hard to design efficient protocols over arbitrary digraphs. However, if URMT is possible between every pair of vertices in the network, then we present efficient protocols for the same.

Abstract

For content level access, very often database needs the query as a sample image. However, the image may contain private information and hence the user does not wish to reveal the image to the database. Private content based image retrieval (PCBIR) deals with retrieving similar images from an image database without revealing the content of the query image - not even to the database server. We propose algorithms for PCBIR, when the database is indexed using hierarchical index structure or hash based indexing scheme. Experiments are conducted on real datasets with popular features and state of the art data structures. It is observed that specialty and subjectivity of image retrieval (unlike SQL queries to a relational database) enables in computationally efficient yet private solutions.

Abstract

In this paper we present an automatic Keyphrase extraction technique for English documents of scientific domain. The devised algorithm uses n-gram filtration technique, which filters sophisticated n-grams {1dnd4} along with their weight from the words of input document. To develop n-gram filtration technique, we have used (1) LZ78 data compression based technique, (2) a simple refinement step, (3) A simple Pattern Filtration algorithm and, (4) a term weighting scheme. In term weighting scheme, we have introduced the importance of position of sentence (where given phrase occurs first) in document and position of phrase in sentence for documents of scientific domain (which is literally more organized than other domains). The entire system is based upon statistical observations, simple grammatical facts, heuristics, and lexical information of English language. We remark that the devised system does not require a learning phase. Our experimental results with publically available text dataset, shows that the devised system is comparable with other known algorithms.

Abstract

The rapid growth of Internet and digitized content has made video distribution easy. Hence the need for video data protection is on the rise. In this paper, we propose a secure and computationally feasible video encryption algorithm based on the method of Secret Sharing. In an MPEG video, the strength of the DC is distributed among the AC values based on Shamir's Secret Sharing (SSS) scheme. The proposed algorithm guarantees security, speed and error tolerance with a small increase in video size.

Abstract

Most of the video encryptions algorithms considered in the literature significantly increase the video size independent of encryption algorithm employed. This is because these algorithms encrypt DCTs without considering their characteristics or relationship to the visual content. This adversely affects the transmission throughput. We propose a fast video encryption algorithm that exploits the statistics of the DCTs in the video data sets. Our algorithm reduces the video size significantly without any compromise in security. The proposed algorithm performs encryption followed by permutation of the DCTs. On an average, increase in video size is restricted to 23.41% of the original.

Abstract

Advances in digital content transmission have increased in the past few years. Security and privacy issues of the transmitted data have become an important concern in multimedia technology. In this paper, we propose a computationally efficient and secure video encryption algorithm. This makes secure video encryption feasible for real-time applications without any extra dedicated hardware. We achieve computational efficiency by exploiting the frequently occurring patterns in the DCT coefficients of the video data. Computational complexity of the encryption is made proportional to the influence of the DCT coefficients on the visual content. On an average, our algorithm takes only 8.32 ms of encryption time per frame.

Abstract

Current denoising techniques use the classical orthonormal wavelets for decomposition of an image corrupted with additive white Gaussian noise, upon which various thresholding strategies are built. The use of available biorthogonal wavelets in image denoising is less common because of their poor performance. In this paper, we present a method to design image-matched biorthogonal wavelet bases and report on their potential for denoising. We have conducted experiments on various image datasets namely Natural, Satellite and Medical with the designed wavelets using two existing thresholding strategies. Test results from comparing the performance of matched and fixed biorthogonal wavelets show an average improvement of 35% in MSE for low SNR values (0 to 18db) in every dataset. This improvement was also seen in the PSNR and visual comparisons. This points to the importance of matching when using wavelet-based denoising

Abstract

Retinal images are widely used to manually or automatically detect and diagnose many diseases. Due to the complex imaging setup, there is a large luminosity and contrast variability within and across images. Here, we use the knowledge of the imaging geometry and propose an enhancement method for colour retinal images, with a focus on contrast improvement with no introduction of artifacts. The method uses non-uniform sampling to estimate the degradation and derive a correction factor from a single plane. We also propose a scheme for applying the derived correction factor to enhance all the colour planes of a given image. The proposed enhancement method has been tested on a publicly available dataset [8]. Results show marked improvement over existing methods.

Abstract

Extraction of anatomical structures (landmarks), such as optic disk (OD), fovea and blood vessels, from fundus images is useful in automatic diagnosis. Current approaches largely use spatial relationship among the landmarks’ position for detection. In this paper, we present an appearance-based method for detecting fovea and OD from colour images. The strategy used for detection is based on improving the local contrast which is achieved by combining information from two spectral channels of the given image. The proposed method has been successfully tested on different datasets and the results show 96% detection for fovea and 91% detection for OD (a total of 502 and 531 images for fovea and OD are taken respectively).