Quantifying Privacy: A Novel Entropy-Based Measure of Disclosure Risk

It is well recognised that data mining and statistical analysis pose a serious treat to privacy. This is true for financial, medical, criminal and marketing research. Numerous techniques have been proposed to protect privacy, including restriction and data modification. Recently proposed privacy models such as differential privacy and k-anonymity received a lot of attention and for the latter there are now several improvements of the original scheme, each removing some security shortcomings of the previous one. However, the challenge lies in evaluating and comparing privacy provided by various techniques. In this paper we propose a novel entropy based security measure that can be applied to any generalisation, restriction or data modification technique. We use our measure to empirically evaluate and compare a few popular methods, namely query restriction, sampling and noise addition.Comment: 20 pages, 4 figure

Securing Internet Protocol (IP) Storage: A Case Study

Storage networking technology has enjoyed strong growth in recent years, but security concerns and threats facing networked data have grown equally fast. Today, there are many potential threats that are targeted at storage networks, including data modification, destruction and theft, DoS attacks, malware, hardware theft and unauthorized access, among others. In order for a Storage Area Network (SAN) to be secure, each of these threats must be individually addressed. In this paper, we present a comparative study by implementing different security methods in IP Storage network.Comment: 10 Pages, IJNGN Journa

CORP: An algorithm to prevent unauthorized data modification using collaborative nodes

The COllaborative Redundant Processing (CORP) algorithm is an approach to prevent unauthorised modification of data in a decentralised and distributed computing environment. Built on Ki-Nga-Kopuku, a distributed and decentralised security model for Cloud Computing, where redundant nodes are functionally identical, the nodes collectively maintain consistency and integrity of processed data. If a single node is compromised and acts maliciously to modify data, other nodes detect the action. CORP extends the functionality of Ki-Nga-Kopuku and is developed mainly for a Cloud Computing context, but the concept can be used in any distributed and decentralised environment to provide consistency, integrity, and availability

User's manual for EZPLOT version 5.5: A FORTRAN program for 2-dimensional graphic display of data

EZPLOT is a computer applications program that converts data resident on a file into a plot displayed on the screen of a graphics terminal. This program generates either time history or x-y plots in response to commands entered interactively from a terminal keyboard. Plot parameters consist of a single independent parameter and from one to eight dependent parameters. Various line patterns, symbol shapes, axis scales, text labels, and data modification techniques are available. This user's manual describes EZPLOT as it is implemented on the Ames Research Center, Dryden Research Facility ELXSI computer using DI-3000 graphics software tools

Secure agent data integrity shield

In the rapidly expanding field of E-Commerce, mobile agent is the emerging technology that addresses the requirement of intelligent filtering/processing of information. This paper will address the area of mobile agent data integrity protection. We propose the use of Secure Agent Data Integrity Shield (SADIS) as a scheme that protects the integrity of data collected during agent roaming. With the use of a key seed negotiation protocol and integrity protection protocol, SADIS protects the secrecy as well as the integrity of agent data. Any illegal data modification, deletion, or insertion can be detected either by the subsequent host or the agent butler. Most important of all, the identity of each malicious host can be established. To evaluate the feasibility of our design, a prototype has been developed using Java. The result of benchmarking shows improvement both in terms of data and time efficiency