Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

A Middleware for the Internet of Things

The Internet of Things (IoT) connects everyday objects including a vast array of sensors, actuators, and smart devices, referred to as things to the Internet, in an intelligent and pervasive fashion. This connectivity gives rise to the possibility of using the tracking capabilities of things to impinge on the location privacy of users. Most of the existing management and location privacy protection solutions do not consider the low-cost and low-power requirements of things, or, they do not account for the heterogeneity, scalability, or autonomy of communications supported in the IoT. Moreover, these traditional solutions do not consider the case where a user wishes to control the granularity of the disclosed information based on the context of their use (e.g. based on the time or the current location of the user). To fill this gap, a middleware, referred to as the Internet of Things Management Platform (IoT-MP) is proposed in this paper.Comment: 20 pages, International Journal of Computer Networks & Communications (IJCNC) Vol.8, No.2, March 201

A Trust Model Based on Service Classification in Mobile Services

Internet of Things (IoT) and B3G/4G communication are promoting the pervasive mobile services with its advanced features. However, security problems are also baffled the development. This paper proposes a trust model to protect the user's security. The billing or trust operator works as an agent to provide a trust authentication for all the service providers. The services are classified by sensitive value calculation. With the value, the user's trustiness for corresponding service can be obtained. For decision, three trust regions are divided, which is referred to three ranks: high, medium and low. The trust region tells the customer, with his calculated trust value, which rank he has got and which authentication methods should be used for access. Authentication history and penalty are also involved with reasons.Comment: IEEE/ACM Internet of Things Symposium (IOTS), in conjunction with GreenCom 2010, IEEE, Hangzhou, China, December 18-20, 201

Adding Salt to Pepper: A Structured Security Assessment over a Humanoid Robot

The rise of connectivity, digitalization, robotics, and artificial intelligence (AI) is rapidly changing our society and shaping its future development. During this technological and societal revolution, security has been persistently neglected, yet a hacked robot can act as an insider threat in organizations, industries, public spaces, and private homes. In this paper, we perform a structured security assessment of Pepper, a commercial humanoid robot. Our analysis, composed by an automated and a manual part, points out a relevant number of security flaws that can be used to take over and command the robot. Furthermore, we suggest how these issues could be fixed, thus, avoided in the future. The very final aim of this work is to push the rise of the security level of IoT products before they are sold on the public market.Comment: 8 pages, 3 figures, 4 table