In a world where the industry of mobile applications is continuously expanding and new health care apps and devices are created every day, it is important to take special care of the collection and treatment of users' personal health information. However, the appropriate methods to do this are not usually taken into account by apps designers and insecure applications are released. This paper presents a study of security and privacy in mHealth, focusing on three parts: a study of the existing laws regulating these aspects in the European Union and the United States, a review of the academic literature related to this topic, and a proposal of some recommendations for designers in order to create mobile health applications that satisfy the current security and privacy legislation. This paper will complement other standards and certifications about security and privacy and will suppose a quick guide for apps designers, developers and researchers.

Privacy and Security in Mobile Health Apps: A Review and Recommendations

The healthcare data is an important asset and rich source of healthcare intellect. Medical databases, if created properly, will be large, complex, heterogeneous and time varying. The main challenge nowadays is to store and process this data efficiently so that it can benefit humans. Heterogeneity in the healthcare sector in the form of medical data is also considered to be one of the biggest challenges for researchers. Sometimes, this data is referred to as large-scale data or big data. Blockchain technology and the Cloud environment have proved their usability separately. Though these two technologies can be combined to enhance the exciting applications in healthcare industry. Blockchain is a highly secure and decentralized networking platform of multiple computers called nodes. It is changing the way medical information is being stored and shared. It makes the work easier, keeps an eye on the security and accuracy of the data and also reduces the cost of maintenance. A Blockchain-based platform is proposed that can be used for storing and managing electronic medical records in a Cloud environment.

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A Proposed Solution and Future Direction for Blockchain-Based Heterogeneous Medicare Data in Cloud Environment

Public safety networks are based on wireless communication technologies, and are particularly important in field operations to support the mobility of first responders. With enhanced functionalities and capabilities, unmanned aerial vehicles, commonly referred to as drones, can be equipped with communication hardware and sent to suitable positions in the field to augment the operation of public safety networks. Security is of primary importance in such drone-assisted public safety networks because sensitive or critical information could be transmitted among these network entities. This article examines the cyber security issues of such networks.

Drone-Assisted Public Safety Networks: The Security Aspect

Energy efficient communication is a plenary issue in Wireless Sensor Networks (WSNs) Contemporary energy efficient optimization schemes are focused on reducing power consumption in various aspects of hardware design, data processing, network protocols and operating system In this paper, optimization of network is formulated by Cuckoo Based Particle Approach (CBPA) Nodes are deployed randomly and organized as static clusters by Cuckoo Search (CS) After the cluster heads are selected, the information is collected, aggregated and forwarded to the base station using generalized particle approach algorithm The Generalized Particle Model Algorithm (GPMA) transforms the network energy consumption problem into dynamics and kinematics of numerous particles in a force-field The proposed approach can significantly lengthen the network lifetime when compared to traditional methods

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Energy Efficient Computation of Data Fusion in Wireless Sensor Networks Using Cuckoo Based Particle Approach (CBPA)

Clustering in wireless sensor networks (WSNs) is one of the techniques that can expand the lifetime of the whole network through data aggregation at the cluster head. This paper presents performance comparison between particle swarm optimization (PSO) and genetic algorithms (GA) with a new cost function that has the objective of simultaneously minimizing the intra-cluster distance and optimizing the energy consumption of the network. Furthermore, a comparison is made with the well known cluster-based protocols developed for WSNs, LEACH (low-energy adaptive clustering hierarchy) and LEACH-C, the later being an improved version of LEACH, as well as the traditional K-means clustering algorithm. Simulation results demonstrate that the proposed protocol using PSO algorithm has higher efficiency and can achieve better network lifetime and data delivery at the base station over its comparatives.

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Performance Comparison of Optimization Algorithms for Clustering in Wireless Sensor Networks

With the rapid development of the information technology, the health care technologies already became matured. Such as electronic medical records that can be easily stored. However, how to get medical resources more convenient is currently concerning issue. In spite of many literatures discussed about medical systems, these literatures should face many security challenges. The most important issue is patients' privacy. Therefore, we propose a privacy authentication scheme based on cloud environment. In our scheme, we use mobile device's characteristics, allowing peoples to use medical resources on the cloud environment to find medical advice conveniently. The digital signature is used to ensure the security of the medical information that is certified by the medical department in our proposed scheme.

A Privacy Authentication Scheme Based on Cloud for Medical Environment

One possibility direction to assist routing in Mobile Ad Hoc Network (MANET) is to use geographical location information provided by positioning devices such as global positioning systems (GPS). Instead of searching the route in the entire network blindly, position-based routing protocol uses the location information of mobile nodes to confine the route searching space into a smaller estimated range. The smaller route searching space to be searched, the less routing overhead and broadcast storm problem will occur.

In this paper, we proposed a location-based routing protocol called LARDAR. There are three important characteristics be used in our protocol to improve the performance. Firstly, we use the location information of destination node to predict a smaller triangle or rectangle request zone that covers the position of destination in the past. The smaller route discovery space reduces the traffic of route request and the probability of collision. Secondly, in order to adapt the precision of the estimated request zone, and reduce the searching range, we applied a dynamic adaptation of request zone technique to trigger intermediate nodes using the location information of destination node to redefine a more precise request zone. Finally, an increasing-exclusive search approach is used to redo route discovery by a progressive increasing search angle basis when route discovery failed. This progressive increased request zone and exclusive search method is helpful to reduce routing overhead. It guarantees that the areas of route rediscovery will never exceed twice the entire network. Simulation results show that LARDAR has lower routing cost and collision than other protocols.

Location-aware routing protocol with dynamic adaptation of request zone for mobile ad hoc networks

In recent years, health care technologies already became matured such as electronic medical records that can be easily stored. However, how to get medical resources more convenient is currently concern issue. In spite of many literatures discussed about medical systems, but these literatures should face many security challenges. The most important issue is patients' privacy. Therefore, we propose a secure medical data exchange protocol based on cloud environment. In our scheme, we use mobile device's characteristics, allowing peoples use medical resources on the cloud environment to seek medical advice conveniently.

A Secure Medical Data Exchange Protocol Based on Cloud Environment

In order to reduce the traffic load and improve the system's lifetime, a cluster-based routing protocol has attracted more attention. In cluster-based sensor networks, energy can be conserved by combining redundant data from nearby sensors into cluster head nodes before forwarding the data to the destination. The lifespan of the whole network can also be expanded by the clustering of sensor nodes and through data aggregation. In this paper, we propose a cluster-based routing protocol which uses the location information of sensors to assist in network clustering. Our protocol partitions the entire network into several clusters by a particle swarm optimization (PSO) clustering algorithm. In each cluster, a cluster head is selected to deal with data aggregation or compression of nearby sensor nodes. For this clustering technique, the correct selection of the number of clusters is challenging and important. To cope with this issue, an energy dissipation model is used in our protocol to automatically estimate the optimal number of clusters. Several variations of PSO-clustering algorithm are proposed to improve the performance of our protocol. Simulation results show that the performance of our protocol is better than other protocols.

Particle Swarm Optimization Algorithm for Energy-Efficient Cluster-Based Sensor Networks

Instead of blindly searching for a route in the entire network, the location-based routing protocol uses the location information of mobile nodes to confine routing space into a smaller range that reduces routing overhead and broadcast storm. In this paper, we propose a location-aided cluster-based routing protocol called Core Location-Aided Cluster-based Routing protocol (CLACR). CLACR partitions the entire network into square clusters. In each cluster, a cluster head is selected for routing. Instead of flooding route request packets in the entire network blindly, CLACR computes the desired route by using Dijkstra algorithm in a cluster-by-cluster basis. Only cluster heads, source, and destination nodes are needed to participate in routing procedure that reduce routing overhead tremendously. In order to maintain a shorter path, a route optimization is used to adjust the constructed path dynamically. A local route repair is applied to fix path, while the source or destination nodes roam off a cluster. It is helpful to lengthen the lifetime of route effectively. CLACR can easily be extended to provide geocasting service. Simulation results show that the performance of our routing protocol is better than other protocol.

http://www.wseas.us/e-library/conferences/2006cscc/papers/534-724.pdf

Tzay-Farn Shih

Papers

A Privacy Authentication Scheme Based on Cloud for Medical Environment

Location-aware routing protocol with dynamic adaptation of request zone for mobile ad hoc networks

A Secure Medical Data Exchange Protocol Based on Cloud Environment

Particle Swarm Optimization Algorithm for Energy-Efficient Cluster-Based Sensor Networks

Core location-aided cluster-based routing protocol for mobile ad hoc networks