CTN Issue: November 2014

Introduction

The “Internet of Things” (IoT) refers to a (potentially) near-future Internet architecture where billions of everyday objects will each be assigned an IP address, enabling people to interact with these objects through the Internet, and for the objects to interact with each other.  Representative industry “positions” on the IoT include Microsoft [Microsoft IoT], Cisco [Cisco IoT], and Google [Google IoT], just to name a few.  Although the details of exactly how the future IoT will look remain unclear, it is clear that the IoT holds a potential to transform the way we interact with our world.  To be sure, there are a myriad of technical challenges, and the IEEE is playing a central role in coordinating and publishing cutting edge research in IoT.

In February 2014 the IEEE published the inaugural issue of the IEEE Internet of Things Journal [IEEE IoTJ], which is co-sponsored and published by the IEEE Sensors Council, the IEEE Communications Society, the IEEE Computer Society, and the IEEE Signal Processing Society.  As indicated by the presence of four sponsoring units within IEEE, the Internet of Things is truly an interdisciplinary research area.  In this month’s CTN we highlight three papers from the IEEE Internet of Things Journal -- one paper from each of the last three issues (June, August, and October 2014).  The three papers were selected to represent three broad topics within the IoT: social networking, wireless sensor networks for healthcare, and security concerns.

Three papers on IoT from the IEEE Internet of Things Journal

Our first focus paper is by Antonio Ortiz, Dina Hussein, Soochang Park, Son Han, and Noel Crespi (all from Telecom SudParis, France), entitled “The Cluster Between Internet of Things and Social Networks: Review and Research Challenges” (June, 2014).  This article discusses the Social Internet of Things (SIoT), which integrates the world-wide data availability of the IoT with human-centric social networking principles.  Twelve open research issues in realizing the SIoT are discussed.

Our second focus paper is byYuan Zhang (University of Jinan, China), Limin Sun (Chinese Academy of Sciences, Beijing, China), Houbing Song (West Virginia University, USA), and Xiaojun Cao (Georgia State University, USA), entitled “Ubiquitous WSN for Healthcare: Recent Advances and Future Prospects” (August, 2014).   This article discusses a three tiered architecture for a wireless sensor network (WSN) for healthcare applications, analyzes the suitability of six different members of the IEEE 802 series standards for healthcare monitoring, and finally identifies four principles of a future ubiquitous sensing for healthcare (USH) platform.

Our third and final focus paper is by Kuan Zhang (University of Waterloo, Canada), Xiaohui Liang (Dartmouth College, USA), Rongxing Lu (Nanyang Technological University, Singapore), and Xuemin Shen (University of Waterloo, Canada), entitled “Sybil Attacks and Their Defenses in the Internet of Things” (October, 2014).  Sybil attacks are security threats where malicious users in a social network form connections with honest users.  Detection of Sybil attacks is done through social network graph analysis, behavior analysis, or through techniques specific to mobile social networks, depending upon the context.  This paper surveys the various types of Sybil attacks as well as the wide variety of Sybil detection schemes, and outlines open research challenges in the field.

Additional resources on IoT

We briefly highlight several other sources of information about the IoT that may be of interest to IEEE Communications Society members.  First, the ComSoc Emerging Technologies Standing Committee [ComSoc ETS] has created a Subcommittee on Internet of Things [ComSoc IoT], chaired by Latif Ladid (University of Luxembourg).  The subcommittee helps organize and sponsor workshops, conferences, and special issues on IoT.

The IEEE GLOBECOM 2014 conference (December 8-12, 2014 in Austin, Texas, USA) will host four different Industry Forum Sessions [Globecom 2014 IF] on the IoT: “Low Power Solutions for IoT” (December 9, 4-6pm, IF-6), “IEEE 802.11ah: Wi‐Fi Technology Tuned for IoT” (December 10, 2-4pm, IF-15), “IPv6 and IoT Challenges” (December 10, 4-6pm, IF-16), and “Internet-of-Things – from Standardization to Deployment and Commercialization” (December 11, 2-3:30pm, 4-6pm, IF-25/26).

Looking forward, the IEEE ICC conference (June 8-12, 2015 in London, UK) will host an Internet of Things Symposium [ICC 2015 IoTS] chaired by Latif Ladid (University of Luxembourg), Antonio Jara (University of Applied Sciences Western Switzerland), Antonio Karmeta (University of Murcia, Spain), and Sebastien Ziegler (Mandat International, Switzerland).

The IEEE sponsored the IEEE World Forum on Internet of Things this past March, 2014 in Seoul, Korea [WF-IoT], including keynote presentations by Kyungwhoon Cheun (Samsung Electronics), Vida Ilderem (Intel Labs), and Chung-Sheng Li (IBM T.J. Watson Research Center), and tutorials on IoT as it relates to application architectures, social networks, and service platforms.

IEEE maintains a well-organized and frequently updated portal for all things related to IoT [IEEE IoT], including recent and upcoming conferences, articles, standards, and a newsletter.

In summary, the IEEE and the IEEE Communications Society are coordinating cutting-edge research that will enable transformative new ways for us to interact with our world through the Internet of Things.

1. The Cluster Between Internet of Things and Social Networks: Review and Research Challenges

Authors: Antonio Ortiz, Dina Hussein, Soochang Park, Son Han, and Noel Crespi (all from Telecom SudParis, France)
Title: “The Cluster Between Internet of Things and Social Networks: Review and Research Challenges”
Publication:  IEEE Internet of Things Journal, vol. 1, no. 3, June 2014

Whereas the current “Intranet of Things” consists of a local network (like a wireless sensor network) capable of exchanging local information, the envisioned “Internet of Things” would extend the scope and scale by interconnecting these networks.  Beyond the IoT lies the Social Internet of Things (SIoT), where the environmental information from the IoT is merged with social networking principles, to enable useful “social driven” human to device interaction.  Whereas the IoT is a “"a world-wide network of interconnected objects uniquely addressable, based on standard communication protocols", the SIoT paradigm facilitates interaction.  Interaction is facilitated in a variety of ways, e.g., enabling devices to play a “social role” (smart objects),facilitating easier service discovery, and facilitating service interoperability (“mash-ups”).

The paper summarizes challenges and open issues in realizing the SIoT vision (Section V).  First, the architectural components of SIoT include the actors (humans and things) who each produce and consume both data requests and responses, the “intelligent system” to orchestrate all these interactions, the interface design for humans and things to interact with the SIoT, and the Internet as the underlying communication medium.  Second, the enabling technologies to be developed include the addressing scheme (including identity administration and authentication),  the device hardware (sensors, actuators), and communication protocols and algorithms. 

Finally, the paper lists (Section V-C) twelve challenges to be addressed to make SIoT a reality:

1. Interoperability, data management, and signal processing.  How will heterogeneous devices interoperate? How will data be stored and managed?  How will information be analyzed?
2. Discovery and search engines.  How will data, services, and applications be made easily discoverable?
3. Energy management.  How will battery-powered hand-held mobile devices participate in the IoT?
4. Security, privacy and trust.  How will data be secured?  How will user privacy be maintained?  How can users be made to trust in the SIoT?
5. Self-operation, management, and organization.  How can the operation of the SIoT be made “automatic”? 
6. Heterogeneity.  How can a common interface be designed for devices as varied as “sensors, actuators, ID-tags, smartphones, tablets, computers”?
7. Interactions and interfaces.  How can the SIoT interface be made to be user-friendly?
8. Service management (discovery and composition).  How can available SIoT services be discovered?  How can they be composed (mashed-up)?
9. Application development.  What kind of application programming interface (API) will foster useful application development?
10. New business models and stakeholders.  What business models will be profitable by appealing to a broad customer base?
11. Fault tolerance.  How can the SIoT be made robust to the failure of individual components?
12. Semantics and context management.  How should a given device manage the variety of contexts in which it may be simultaneously participating? 

2. Ubiquitous WSN for Healthcare: Recent Advances and Future Prospects

Authors: Yuan Zhang (University of Jinan, China), Limin Sun (Chinese Academy of Sciences, Beijing, China), Houbing Song (West Virginia University, USA), and Xiaojun Cao (Georgia State University, USA)
Title: “Ubiquitous WSN for Healthcare: Recent Advances and Future Prospects”
Publication: IEEE Internet of Things Journal, vol. 1, no. 4, August 2014

Advances in health monitoring devices promise to usher in a new era in healthcare where health data is being constantly collected (through a wearable monitoring platform) and transmitted to and analyzed by the healthcare provider.  In contrast with current medical practices (episodic measurement and care), a ubiquitous health data stream promises to improve diagnosis accuracy, reduce treatment delay, and reduce obstacles for patients to receive treatment.

The authors propose a tiered architecture (access layer, convergence layer, and application layer) for wireless sensor network based healthcare systems.  Tier 1 (access layer) comprises the wireless medical sensors that form the wireless sensor network.  These sensors share data with remote healthcare providers over Tier 2 (convergence layer) using conventional wireless and wired communication and networking protocols.  This data is “synergized” to facilitate analysis of the patient’s health by health care providers at Tier 3 (application layer).

Six potential protocols within the IEEE 802 series standard are analyzed for suitability in health applications.  These include:

1. IEEE 802.11n (Wireless local area networks, WLAN): not suited to mobility and coverage needs.
2. IEEE 802.15.1 (Bluetooth low-energy, BT-LE): although conventional Bluetooth is a poor candidate due to high transmission power, the BT-LE variant is a viable candidate for healthcare monitoring.
3. IEEE 802.15.4 (Zigbee): low bandwidth of 250 kbps results in four times the latency of BT-LE and low market penetration make Zigbee inferior to BT-LE.
4. IEEE 802.15.6 (Body Area Networks): designed for short range communication and higher security/safety regulations.
5. IEEE 802.16e (Wireless Metropolitan Area Networks, MAN, commercialized as WiMAX): designed for high rate transmissions, high mobility, and high security; this protocol is well-suited to healthcare monitoring needs.
6. IEEE 802.22 (Cognitive radio): designed to make use of idle spectrum in TV broadcast bands, but its peaceful coexistence with TV is at this point still unclear.

Finally, four principles of a future ubiquitous sensing for healthcare (USH) are identified:

1. Proactiveness: transmission of healthcare data to healthcare providers should be done proactively so as to proactively enable necessary interventions.
2. Transparency: the design of the system should carefully tradeoff the value of a sensor’s data with the incurred discomfort on the wearer; the healthcare monitoring system should be made as transparent as possible.
3. Awareness: “blind” devices that are not context-aware could easily become a nuisance; devices and monitors should be tuned to the context and needs of the wearer.
4. Trustworthiness: the transmission of personal health data over a wireless medium requires controls in place to mitigate accidental errors, and secure data from unauthorized access or tampering.

3. Sybil Attacks and Their Defenses in the Internet of Things

Authors: Kuan Zhang (University of Waterloo, Canada), Xiaohui Liang (Dartmouth College, USA), Rongxing Lu (Nanyang Technological University, Singapore), and Xuemin Shen (University of Waterloo, Canada)
Title: “Sybil Attacks and Their Defenses in the Internet of Things”
Publication: IEEE Internet of Things Journal, vol. 1, no. 5, October 2014

A Sybil attack is a security threat where an attacker employs a false/forged identity to gain unauthorized access to a secure system.  A Sybil attack is of particular concern in the IoT because of the extensive personal data envisioned to be made available on the IoT.

The paper proceeds from an understanding that social network users may be classified as honest nodes or as dishonest (Sybil) nodes.  Viewing the social network as a graph with users as nodes and edges indicating an established relationship in a social network, an “attack edge” is one between a Sybil user and an honest user.  The authors distinguish three types of attacks:

1. SA-1: the Sybil users are themselves tightly interconnected, but are only able to establish a few attack edges.
2. SA-2: the Sybile users enjoy many attack edges to honest users
3. SA-3: in a mobile domain the transience of the connections precludes establishing a social graph, as these connections are transient

The defenses to Sybil attacks are divided into three categories:

1. Social graph-based Sybil detection (SGSD): includes Social network-based Sybil defense (SNSD) and Social community-based Sybil detection (SCSD), both suitable defenses for SA-1.  Six different graph-based Sybil detection schemes available in the literature are summarized in Table II.
2. Behavior classification-based Sybil detection, suitable for defense against SA-2.   The typical social networking activities for most users include befriending, uploading and tagging photos, browsing user profiles, etc., and analysts have found that the state transition diagram among these activities is quite distinct between honest users and Sybil users (Figure 4).
3. Mobile Sybil defense (MSD): includes friend relationship-based Sybil detection (FRSD), cryptography-based mobile Sybil detection, and feature-based mobile Sybil detection.  All three defenses suitable for SA-3.

The authors identify three key research challenges in detecting Sybil attacks in the IoT:

1. Sybil defense in mobile social networks (MSNs): the absence of a social graph and user behavior history reduces the ability of graph and behavior-based techniques to detect Sybils. 
2. Privacy and Sybil defense: using user behavior history to classify users as honest or dishonest compromises the privacy of those users.
3. Cooperative Sybil defense: to address the challenge of Sybil identification in mobile scenarios, coordination with centralized social network servers to jointly observe user behavior for improved classification.

References

1. [Microsoft IoT]     Microsoft Corporation, “Internet of Things: The Future of Your Business Technology”, http://www.microsoft.com/windowsembedded/en-us/internet-of-things.aspx (Accessed on October 30, 2014).
2. [Cisco IoT]     Cisco Systems Corporation, “Internet of Things (IoT)”, http://www.cisco.com/web/solutions/trends/iot/overview.html (Accessed on October 30, 2014).
3. [Google IoT]     Google Corporation, “The Physical Web”, https://google.github.io/physical-web/ (Accessed on October 30, 2014).
4. [IEEE IoTJ]     IEEE Internet of Things Journal, http://iot-journal.weebly.com (Accessed on October 30, 2014).
5. [Ortiz et al.]     Antonio Ortiz, Dina Hussein, Soochang Park, Son Han, and Noel Crespi, “The Cluster Between Internet of Things and Social Networks: Review and Research Challenges”, IEEE Internet of Things Journal, vol. 1, no. 3, June 2014, pp 206—215.http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6802330
6. [Zhang, Sun et al.]     Yuan Zhang, Limin Sun, Houbing Song, and Xiaojun Cao, “Ubiquitous WSN for Healthcare: Recent Advances and Future Prospects”, IEEE Internet of Things Journal, vol. 1, no. 4, August 2014, pp 311—318.http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6827212
7. [Zhang, Liang et al.]     Kuan Zhang, Xiaohui Liang, Rongxing Lu, and Xuemin Shen, “Sybil Attacks and Their Defenses in the Internet of Things”,IEEE Internet of Things Journal, vol. 1, no. 5, October 2014, pp 372--383.http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6868197
8. [ComSoc ETS     IEEE Communications Society Emerging Technologies Standing Committee, http://www.comsoc.org/about/emerging-technologies (Accessed on October 30, 2014).
9. [ComSoc IoT]     IEEE Communications Society Internet of Things Subcommittee, http://cms.comsoc.org/eprise/main/SiteGen/TC_IOT/Content/Home.html (Accessed on October 30, 2014).
10. [Globecom 2014 IF]     IEEE Global Communications Conference (GLOBECOM) 2014 Industry Forum Session, http://globecom2014.ieee-globecom.org/ifepanel.html (Accessed on October 30, 2014).
11. [ICC 2015 IoTS]     IEEE International Conference on Communications (ICC) 2015 Internet of Things Symposium, http://icc2015.ieee-icc.org/sites/icc2015.ieee-icc.org/files/u39/1-4-SAC%20Internet_of_Things_ICC2015_ext2.pdf (Accessed on October 30, 2014).
12. [WF-IoT]     IEEE World Forum on Internet of Things 2014, http://sites.ieee.org/wf-iot/about/ (Accessed on October 30, 2014).
13. [IEEE IoT]     IEEE Internet of Things, http://iot.ieee.org (Accessed on October 30, 2014).

Statements and opinions given in a work published by the IEEE or the IEEE Communications Society are the expressions of the author(s). Responsibility for the content of published articles rests upon the authors(s), not IEEE nor the IEEE Communications Society.