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Differential privacy (DP) is a promising scheme for releasing the results of statistical queries on sensitive data. This paper focuses on top-k frequent columns publication on sensitive data, with high result utility under differential privacy. Existing works directly select frequent columns from all columns (called one-phase scheme), which is far from ideal due to the large privacy consumption or misjudgments for columns with frequencies close to the frequency of the k th frequent column (called near-k-fluctuation-column). This paper presents a new solution Two Phase Selection (TPS) to carefully choose frequent columns in two phases. The main idea is to classify columns into two distinct categories based on whether it is one near-k-fluctuation-column or not. Frequent columns are chosen from the two categories using different techniques, which is totally different from existing solutions without classifying. Furthermore, by analyzing the distribution of near-k-fluctuation-columns, we introduce a block-centric column-choosing method privacy-free-mechanism (PFM). By partitioning columns into blocks, PFM makes the privacy consumption proportional to the number of blocks, instead of frequent columns. Extensive experiments on real datasets show that our proposals outperform the state-of-the-art techniques for top-k column publication.

Due to the availability of several social media platforms and their use in sending text messages, it is necessary to provide an easy and safe way to protect messages from being hacked especially in the presence of intruders and data thieves, and taking into consideration that most of messages are confidential and personal, it is necessary to provide an easy and safe way to protect messages from being hacked. In this research paper, a simple and easy method of message cryptography will be proposed. The method divides a message into blocks with fixed sizes. The block size ranges from 2 to 60. The method uses a secret color image to generate an array with a size equal to the number of resulted blocks. The array will then be used as a private key. Each element of the private key will be used to calculate the number of rotation digits for the associated block in order to apply block rotation left operation. The proposed method will be examined using the parameters: Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Correlation Coefficient (CC), and throughput. The proposed method will be compared with other standard methods of message cryptography, such as Data Encryption Standard (DES), Triple-DES (3DES), Advanced Encryption Standard (AES), and Blow Fish (BF). Experimental results show that the proposed method is enough secured based on using secret image, block size, and calculated Rotation Left Digits (RLD) for each block.

A parameter is a numerical or other measurable factor whose values characterize a system. Connectivity parameters have indispensable role in the analysis of connectivity of networks. Strength of a cycle in an unweighted graph is always one. But, in a fuzzy graph, strengths of cycles may vary even for a given pair of vertices. Cyclic reachability is a property that determines the overall connectedness of a network. This article introduces two connectivity parameters namely, cyclic connectivity index (CCI) and average CCI (ACCI) of fuzzy graphs, which can be used to represent the cyclic reachability. CCI of fuzzy graph theoretic structures, such as trees, blocks, θ-fuzzy graphs, and complete fuzzy graphs, are discussed. Vertices of a fuzzy graph are classified into three categories in terms of ACCI and their characterizations are obtained. Three algorithms are proposed. One of them is to help find CCI and ACCI of a given fuzzy graph. Another helps to identify the nature of vertices and the third to enhance the existing ACCI of a fuzzy graph. Also, future directions in the study of CCI and ACCI are proposed. [ABSTRACT FROM AUTHOR]

Abstract-The role of slow potassium current in nerve conduction block induced by high-frequency biphasic electrical current was analyzed using a lumped circuit model of a myelinated axon based on the Schwarz-Reid-Bostock model. The results indicate that nerve conduction block at stimulation frequencies above 4 kllz is due to constant activation of both fast and slow potassium channels, but the block at stimulation frequencies below 4 kHz could be due to either anodal or cathodal dc block depending on the time of the action potiential arriving at the block electrode. When stimulation frequency was above 4 kHz, the slow potassium current was about 3.5 to 6.5 times greater than the fast potassium current at blocking threshold, indicating that the slow potassium current played a more dominant role than the fast potassium current. The blocking location moved from the node under the blocking electrode to a nearby node as the stimulation intensity increased. This simulation study reveals that in mammalian myelinated axons, the slow potassium current probably plays a critical role in the nerve conduction block induced by high-frequency biphasic electrical current. [ABSTRACT FROM AUTHOR]