A k-anonymity privacy-preserving approach in wireless medical monitoring environments

With the proliferation of wireless sensor networks and mobile technologies in general, it is possible to provide improved medical services and also to reduce costs as well as to manage the shortage of specialized personnel. Monitoring a person’s health condition using sensors provides a lot of benefits but also exposes personal sensitive information to a number of privacy threats. By recording user-related data, it is often feasible for a malicious or negligent data provider to expose these data to an unauthorized user. One solution is to protect the patient’s privacy by making difficult a linkage between specific measurements with a patient’s identity. In this paper we present a privacy-preserving architecture which builds upon the concept of k-anonymity; we present a clustering-based anonymity scheme for effective network management and data aggregation, which also protects user’s privacy by making an entity indistinguishable from other k similar entities. The presented algorithm is resource aware, as it minimizes energy consumption with respect to other more costly, cryptography-based approaches. The system is evaluated from an energy-consuming and network performance perspective, under different simulation scenarios.     

Providing advanced remote medical treatment services through pervasive environments

Advances on sensor technology, wireless environments and data mining introduce new possibilities in the healthcare sector, realizing the anytime-anywhere access to medical information. Towards this direction, integration of packet-switched networks and sensor devices can be effective in deploying assistive environments, such as home monitoring for elderly or patients. In this paper we describe a policy-based architecture that utilizes wireless sensor devices, advanced network topologies and software agents to enable remote monitoring of patients and elderly people; through the aforementioned technologies we achieve continuous monitoring of a patient’s condition and we can proceed when necessary with proper actions. We also present a software framework and network architecture that realizes the provision of remote medical services, in compliance with the imposed security and privacy requirements. A proof of concept prototype is also deployed, along with an evaluation of the overall architecture’s performance.     

Competitive Call Control in Mobile Networks

Abstract. In this paper we deal with competitive local on-line algorithms for non-preemptive channel allocation in mobile networks. The signal interferences in a network are modeled using an interference graph G . We prove that the greedy on-line algorithm is Δ -competitive, where Δ is the maximum degree of G . We employ the ``classify and randomly select" paradigm [5], [17], and give a 5 -competitive randomized algorithm for the case of planar interference graphs, a 2 -competitive randomized algorithm for trees, and a (2c) -competitive randomized algorithm for graphs of arboricity c . We also show that the problem of call control in mobile networks with multiple available frequencies reduces to the problem of call control in mobile networks with a single frequency. Using this reduction, we present on-line algorithms for general networks with a single frequency. We give a local on-line algorithm which is (α (δ +1 + α )/(1/2+α ) ² )-competitive, where α is the independence number of G , and δ is the average degree of G . The above results hold in the case when the duration of each request is infinite, and the benefit the algorithm gains by accepting each request is equal to one. They are extended to handle requests of arbitrary durations, and arbitrary benefits.     

A survey on jamming attacks and countermeasures in WSNs

Jamming represents the most serious security threat in the field of Wireless Sensor Networks (WSNs), as it can easily put out of order even WSNs that utilize strong highlayer security mechanisms, simply because it is often ignored in the initial WSN design. The objective of this article is to provide a general overview of the critical issue of jamming in WSNs and cover all the relevant work, providing the interested researcher pointers for open research issues in this field. We provide a brief overview of the communication protocols typically used in WSN deployments and highlight the characteristics of contemporary WSNs, that make them susceptible to jamming attacks, along with the various types of jamming which can be exercised against WSNs. Common jamming techniques and an overview of various types of jammers are reviewed and typical countermeasures against jamming are also analyzed. The key ideas of existing security mechanisms against jamming attacks in WSNs are presented and open research issues, with respect to the defense against jamming attacks are highlighted.     

Efficient parallel Text Retrieval techniques on Bulk Synchronous Parallel (BSP)/Coarse Grained Multicomputers (CGM)

In this paper, we present efficient, scalable, and portable parallel algorithms for the off-line clustering, the on-line retrieval and the update phases of the Text Retrieval (TR) problem based on the vector space model and using clustering to organize and handle a dynamic document collection. The algorithms are running on the Coarse-Grained Multicomputer (CGM) and/or the Bulk Synchronous Parallel (BSP) model which are two models that capture within a few parameters the characteristics of the parallel machine. To the best of our knowledge, our parallel retrieval algorithms are the first ones analyzed under these specific parallel models. For all the phases of the proposed algorithms, we analytically determine the relevant communication and computation cost thereby formally proving the efficiency of the proposed solutions. In addition, we prove that our technique for the on-line retrieval phase performs very well in comparison to other possible alternatives in the typical case of a multiuser information retrieval (IR) system where a number of user queries are concurrently submitted to an IR system. Finally, we discuss external memory issues and show how our techniques can be adapted to the case when processors have limited main memory but sufficient disk capacity for holding their local data.

Approximation algorithms for the arc orienteering problem

In this article we present approximation algorithms for the Arc Orienteering Problem (AOP). We propose a polylogarithmic approximation algorithm in directed graphs, while in undirected graphs we give a (6+?+o(1))$(6+?+o(1))$ and a (4+?)$(4+?)$-approximation algorithm for arbitrary instances and instances of unit profit, respectively. Also, an inapproximability result for the AOP is obtained as well as approximation algorithms for the Mixed Orienteering Problem.     

Improved Algorithms for Dynamic Shortest Paths

We describe algorithms for finding shortest paths and distances in outerplanar and planar digraphs that exploit the particular topology of the input graph. An important feature of our algorithms is that they can work in a dynamic environment, where the cost of any edge can be changed or the edge can be deleted. In the case of outerplanar digraphs, our data structures can be updated after any such change in only logarithmic time. A distance query is also answered in logarithmic time. In the case of planar digraphs, we give an interesting tradeoff between preprocessing, query, and update times depending on the value of a certain topological parameter of the graph. Our results can be extended to n -vertex digraphs of genus O(n ^1-ε ) for any ε>0 . Received September 24, 1996; revised May 13, 1998, and January 20, 1999.