In this paper, we propose a QoS-Oriented Distributed routing protocol (QOD). Usually, a hybrid network has widespread base stations. The data transmission in hybrid networks has two features. First, an AP can be a source or a destination to any mobile node. Second, the number of transmission hops between a mobile node and an AP […]
PRIVACY IN DATA PUBLICATION OF SOCIAL NETWORKS
The first necessary anonymization technique in both the contexts of micro- and network data consists in removing identification. This nave technique has quickly been recognized as failing to protect privacy. For microdata, Sweeney et al. propose k-anonymity to circumvent possible identity disclosure in naively anonymized microdata. `-diversity is proposed in order to further prevent attribute […]
THE L SENSITIVE LABEL DIVERSITY REQUIREMENT
The publication of social network data entails a privacy threat for their users. Sensitive information about users of the social networks should be protected. The challenge is to devise methods to publish social network data in a form that affords utility without compromising privacy. Previous research has pro- posed various privacy models with the corresponding […]
A secure multiparty protocol for computing the OR of private binary vectors
The problem of secure mining of association rules in horizontally partitioned databases. In that setting, there are several sites (or players) that hold homogeneous databases, i.e., databases that share the same schema but hold information on different entities. The goal is to find all association rules with support at least s and confidence at least […]
A SCALABLE SENTENCE SCORING METHOD
Ranking has abundant applications in information retrieval (IR), data mining, and natural language processing. In many real scenarios, the ranking problem is defined as follows. Given a group of data objects, a ranking model (function) sorts the objects in the group according to their degrees of relevance, importance, or preferences. For example, in IR, the […]
Privacy Preserving Mining of frequent patterns
In this paper, our goal is to devise an encryption scheme which enables formal privacy guarantees to be proved, and to validate this model over large-scale, real-life transaction databases. The client/owner encrypts its data using an encrypt/decrypt (E/D) module, which can be essentially treated as a “black box” from its perspective. While the details of […]
ENCRYPTION/DECRYPTION SCHEME
In this paper, we study the problem of outsourcing the association rule mining task within a corporate privacy-preserving framework. A substantial body of work has been done on privacy-preserving data mining in a variety of contexts. A common characteristic of most of the previously studied frameworks is that the patterns mined from the data (which […]
THE NON COOPERATIVE COMPUTATION (NCC) MODEL
Privacy and security, particularly maintaining confidentiality of data, have become a challenging issue with advances in information and communication technology. The ability to communicate and share data has many benefits, and the idea of an omniscient data source carries great value to research and building accurate data analysis models. For credit card companies to build […]
A Database Aggregate Privacy Guarantee
It is often the case that the data published by an organization or company are too detailed to expect attackers to have accurate partial knowledge. Still, an attacker might have some aggregate or abstract knowledge of a record. Examples like this often arise in practice. For example IMIS is currently involved in anonymizing tax related […]
A TRADITIONAL NAIVE BAYES CLASSIFIER
In this paper, we touch on many areas of research that have been heavily studied. The area of privacy inside a social network encompasses a large breadth, based on how privacy is defined. In authors consider an attack against an anonymized network. In their model, the network consists of only nodes and edges. Trait details […]