The Internet of Things (IoT) makes smart objects the ultimate building blocks in the development of cyber-physical smart pervasive frameworks. The IoT has a variety of application domains, including health care. The IoT revolution is redesigning modern health care with promising technological, economic, and social prospects. This paper surveys advances in IoT-based health care technologies and reviews the state-of-the-art network architectures/platforms, applications, and industrial trends in IoT-based health care solutions. In addition, this paper analyzes distinct IoT security and privacy features, including security requirements, threat models, and attack taxonomies from the health care perspective. Further, this paper proposes an intelligent collaborative security model to minimize security risk; discusses how different innovations such as big data, ambient intelligence, and wearables can be leveraged in a health care context; addresses various IoT and eHealth policies and regulations across the world to determine how they can facilitate economies and societies in terms of sustainable development; and provides some avenues for future research on IoT-based health care based on a set of open issues and challenges.

The Internet of Things for Health Care: A Comprehensive Survey

They are susceptible to a variety of attacks, including node capture, physical tampering, and denial of service, while prompting a range of fundamental research challenges.

/pdf/security-in-wireless-sensor-networks-119x7nks5g.pdf

Security in wireless sensor networks

PROMETHEE: A comprehensive literature review on methodologies and applications

We propose a highly scalable cluster-based hierarchical trust management protocol for wireless sensor networks (WSNs) to effectively deal with selfish or malicious nodes. Unlike prior work, we consider multidimensional trust attributes derived from communication and social networks to evaluate the overall trust of a sensor node. By means of a novel probability model, we describe a heterogeneous WSN comprising a large number of sensor nodes with vastly different social and quality of service (QoS) behaviors with the objective to yield "ground truth" node status. This serves as a basis for validating our protocol design by comparing subjective trust generated as a result of protocol execution at runtime against objective trust obtained from actual node status. To demonstrate the utility of our hierarchical trust management protocol, we apply it to trust-based geographic routing and trust-based intrusion detection. For each application, we identify the best trust composition and formation to maximize application performance. Our results indicate that trust-based geographic routing approaches the ideal performance level achievable by flooding-based routing in message delivery ratio and message delay without incurring substantial message overhead. For trust-based intrusion detection, we discover that there exists an optimal trust threshold for minimizing false positives and false negatives. Furthermore, trust-based intrusion detection outperforms traditional anomaly-based intrusion detection approaches in both the detection probability and the false positive probability.

https://people.cs.vt.edu/~irchen/ps/Bao-TNSM12a.pdf

Hierarchical Trust Management for Wireless Sensor Networks and its Applications to Trust-Based Routing and Intrusion Detection

Recent advances in electronics and wireless communication technologies have enabled the development of large-scale wireless sensor networks that consist of many low-power, low-cost, and small-size sensor nodes. Sensor networks hold the promise of facilitating large-scale and real-time data processing in complex environments. Security is critical for many sensor network applications, such as military target tracking and security monitoring. To provide security and privacy to small sensor nodes is challenging, due to the limited capabilities of sensor nodes in terms of computation, communication, memory/storage, and energy supply. In this article we survey the state of the art in research on sensor network security.

Traditional trust management schemes developed for wired and wireless ad hoc networks are not well suited for sensor networks due to their higher consumption of resources such as memory and power. In this work, we propose a new lightweight group-based trust management scheme (GTMS) for wireless sensor networks, which employs clustering. Our approach reduces the cost of trust evaluation. Also, theoretical as well as simulation results show that our scheme demands less memory, energy, and communication overheads as compared to the current state-of-the-art trust management schemes and it is more suitable for large-scale sensor networks. Furthermore, GTMS also enables us to detect and prevent malicious, selfish, and faulty nodes.

Group-Based Trust Management Scheme for Clustered Wireless Sensor Networks

Sensor network security solutions that have been proposed so far are mostly built on the assumption of a trusted environment, which is not very realistic so we need trust management before deploying any other security solution Traditional trust management schemes that have been developed for wired and wireless ad-hoc networks are not suitable for wireless sensor networks because of higher consumption of resources such as memory and power In this paper, we propose a novel lightweight group based trust management scheme (GTMS) for distributed wireless sensor networks in which the whole group will get a single trust value Instead of using completely centralized or distributed trust management schemes, GTMS uses hybrid trust management approach that helps in keeping minimum resource utilization at the sensor nodes

Trust Management Problem in Distributed Wireless Sensor Networks

Constraint specific wireless sensor networks need energy efficient and secure communication mechanisms In this paper we propose Lightweight Security protocol (LSec) that fulfils both requirements LSec provides authentication and authorization of sensor nodes with simple secure key exchange scheme It also provides confidentiality of data and protection mechanism against intrusions and anomalies LSec is memory efficient that requires 72 bytes of memory storage for keys It only introduces 74125 bytes of transmission and reception cost per connection

/pdf/lsec-lightweight-security-protocol-for-distributed-wireless-18b8i06yam.pdf

LSec: lightweight security protocol for distributed wireless sensor network

Highlights? We design Personalized Learning Course Planner (PLCP) applied to E-learning systems. ? PLCP analyzes student's implicit requirements. ? Learning courses are organized according to characteristics and educational levels of students. ? English learning system consisting of PLCP is implemented. ? Learning effectiveness and student satisfaction is improved in experiment results. Various methods of E-learning systems, based on information and communications, and geared towards improving learning effectiveness and students' attention span, have been studied. However, most E-learning systems force students to follow the learning course or content established by a teacher. These methods are convenient, but they limit the effectiveness of E-learning.To overcome this limitation and increase effective learning, new techniques that reflect alternative learning styles, such as adaptive learning and personalized learning, have been studied. In this study, we proposed a Personalized Learning Course Planner (PLCP) that allows students to easily select the learning course they desire. User profile data was collected from the students' initial priorities about learning contents as well as the test scores after their study. E-Learning Decision Support System (EL-DSS) in PLCP suggests an appropriate learning course organization, according to calculated results based on the user profile data.To verify the effectiveness of the proposed system, we implemented an English learning system consisting of PLCP. We conducted an experiment with 30 university students and evaluated students' satisfaction by questionnaire analysis. The results indicate that the proposed system improved learning effectiveness and student satisfaction. Further investigation of the participants indicated that suggesting a learning course suitable for students' previous test scores and priorities encouraged students to concentrate on the lesson.

Personalized Learning Course Planner with E-learning DSS using user profile

Full network level privacy has often been categorized into four sub-categories: Identity, Route, Location and Data privacy. Achieving full network level privacy is a critical and challenging problem due to the constraints imposed by the sensor nodes (e.g., energy, memory and computation power), sensor networks (e.g., mobility and topology) and QoS issues (e.g., packet reach-ability and timeliness). In this paper, we proposed two new identity, route and location privacy algorithms and data privacy mechanism that addresses this problem. The proposed solutions provide additional trustworthiness and reliability at modest cost of memory and energy. Also, we proved that our proposed solutions provide protection against various privacy disclosure attacks, such as eavesdropping and hop-by-hop trace back attacks.

/pdf/achieving-network-level-privacy-in-wireless-sensor-networks-2bqeseoye7.pdf

Young-Jae Song

Papers

Group-Based Trust Management Scheme for Clustered Wireless Sensor Networks

Trust Management Problem in Distributed Wireless Sensor Networks

LSec: lightweight security protocol for distributed wireless sensor network

Personalized Learning Course Planner with E-learning DSS using user profile

Achieving network level privacy in wireless sensor networks