Personal health record (PHR) is an emerging patient-centric model of health information exchange, which is often outsourced to be stored at a third party, such as cloud providers. However, there have been wide privacy concerns as personal health information could be exposed to those third party servers and to unauthorized parties. To assure the patients’ […]
Towards Privacy-Preserving Location proof Updating System
Today’s location-sensitive service relies on user’s mobile device to determine the current location. This allows malicioususers to access a restricted resource or provide bogus alibis by cheating on their locations. To address this issue, we propose A Privacy -Preserving Location proof Updating System (APPLAUS) in which colocated Bluetooth enabled mobile devices mutually generate location proofs […]
A new Distributed Cooperation and Diversity Combining framework in hybrid wireless networks
Our focus is on heterogeneous networks with devices equipped with two types of radio frequency (RF) interfaces: short-range high-rate interface (e.g., IEEE802.11), and a long-range low-rate interface (e.g., cellular) communicating over urban Rayleigh fading channels. Within this framework, we propose and evaluate a set of distributed cooperation techniques operating at different hierarchical levels with resource […]
Improving Probabilistic Route Discovery in Mobile Ad Hoc Networks
Due to high mobility of nodes in mobile ad hoc networks (MANETs), there exist frequent link breakages which lead to nfrequent path failures and route discoveries. The overhead of a route discovery cannot be neglected. In a route discovery, broadcasting is a fundamental and effective data propagation mechanism, where a mobile node blindly rebroadcasts the […]
Semi-random backoff: Towards resource reservation for channel access in 802.11e wireless LANs
This paper proposes a semi-random backoff (SRB) method that enables resource reservation in contention-based wireless LANs. The proposed SRB is fundamentally different from traditional random backoff methods because it provides an easy migration path from random backoffs to deterministic slot assignments. The central idea of the SRB is for the wireless station to set its […]
Distributed management for load balancing in content delivery networks
In this paper, we face the challenging issue of defining and implementing an effective law for load balancing in Content Delivery Networks (CDNs). We base our proposal on a formal study of a CDN system, carried out through the exploitation of a fluid flow model characterization of the network of servers. Starting from such characterization, […]
Mining Association Rules between Sets of Items in Large Databases
Frequent itemset mining is a widely exploratory technique that focuses on discovering recurrent correlations among data. The steadfast evolution of markets and business environments prompts the need of data mining algorithms to discover significant correlation changes in order to reactively suit product and service provision to customer needs. Change mining, in the context of frequent itemsets, […]
Query Recommendation Using Query Logs in Search Engines
For a broad-topic and ambiguous query, different users may have different search goals when they submit it to a search engine. The inference and analysis of user search goals can be very useful in improving search engine relevance and user experience. In this paper, we propose a novel approach to infer user search goals by […]
Privacy Preserving Network Publication against Structural Attacks
Privacy is one of the major concerns when publishing or sharing social network data for social science research and business analysis. Recently, researchers have developed privacy models similar to k-anonymity to prevent node re-identification through structure information. However, even when these privacy models are enforced, an attacker may still be able to infer one’s private […]
Mining Distance-Based Outliers from Categorical Data
Outlier detection can usually be considered as a pre-processing step for locating, in a data set, those objects that do not conform to well-defined notions of expected behavior. It is very important in data mining for discovering novel or rare events, anomalies, vicious actions, exceptional phenomena, etc. We are investigating outlier detection for categorical data […]
- « Previous Page
- 1
- …
- 3
- 4
- 5
- 6
- 7
- Next Page »