The pervasive nature of smart connected devices has intruded on our daily lives and has become an intrinsic part of our world. However, the wide use of the Internet of Things (IoT) in critical application domains has raised concerns for user privacy and security against growing cyber threats. In particular, the implications of cyber exploitation for IoT devices are beyond financial losses and could constitute risks to human life. Most deployed access control solutions for smart IoT systems do not offer policy individualization, the ability to specify or change the policy according to the individual user’s preference. As a result, currently deployed systems are not well suited to specify access control policies in a multi-user environment, where users access the same devices to perform different operations. The system’s security gets tricky when the smart ecosystem involves complicated social relationships, much like in a smart home. Relationship-based access control (ReBAC), widely used in online social networks, offers the ability to consider user relationships in defining access control decisions and supports policy individualization. However, to the best of our knowledge, no such attempt has been made to develop a formal ReBAC model for smart IoT systems. This paper proposes a ReBAC IoT dynamic and fine-grained access control model which considers the social relationships among users along with the attributes to support an attributes-aware relationship-based access control model for smart IoT systems. ReBAC IoT is formally defined, illustrated through different use cases, implemented, and tested.
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Human-machine communication for assistive IoT technologies
Despite the phenomenal advances in the computational power and functionality of electronic systems, human-machine interaction has largely been limited to simple control panels, keyboard, mouse and display. Consequently, these systems either rely critically on close human guidance or operate almost independently from the user. An exemplar technology integrated tightly into our lives is the smartphone. However, the term “smart” is a misnomer, since it has fundamentally no intelligence to understand its user. The users still have to type, touch or speak (to some extent) to express their intentions in a form accessible to the phone. Hence, intelligent decision making is still almost entirely a human task. A life-changing experience can be achieved by transforming machines from passive tools to agents capable of understanding human physiology and what their user wants [1]. This can advance human capabilities in unimagined ways by building a symbiotic relationship to solve real world problems cooperatively. One of the high-impact application areas of this approach is assistive internet of things (IoT) technologies for physically challenged individuals. The Annual World Report on Disability reveals that 15% of the world population lives with disability, while 110 to 190 million of these people have difficulty in functioning [1]. Quality of life for this population can improve significantly if we can provide accessibility to smart devices, which provide sensory inputs and assist with everyday tasks. This work demonstrates that smart IoT devices open up the possibility to alleviate the burden on the user by equipping everyday objects, such as a wheelchair, with decision-making capabilities. Moving part of the intelligent decision making to smart IoT objects requires a robust mechanism for human-machine communication (HMC). To address this challenge, we present examples of multimodal HMC mechanisms, where the modalities are electroencephalogram (EEG), speech commands, and motion sensing. We also introduce an IoT co-simulation framework developed using a network simulator (OMNeT++) and a robot simulation platform Virtual Robot Experimentation Platform (V-REP). We show how this framework is used to evaluate the effectiveness of different HMC strategies using automated indoor navigation as a driver application.
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- Award ID(s):
- 1651624
- NSF-PAR ID:
- 10062477
- Date Published:
- Journal Name:
- 2016 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The pervasive nature of smart connected devices has intruded on our daily lives and has become an intrinsic part of our world. However, the wide use of the Internet of Things (IoT) in critical application domains has raised concerns for user privacy and security against growing cyber threats. In particular, the implications of cyber exploitation for IoT devices are beyond financial losses and could constitute risks to human life. Most deployed access control solutions for smart IoT systems do not offer policy individualization, the ability to specify or change the policy according to the individual user’s preference. As a result, currently deployed systems are not well suited to specify access control policies in a multi-user environment, where users access the same devices to perform different operations. The system’s security gets tricky when the smart ecosystem involves complicated social relationships, much like in a smart home. Relationship-based access control (ReBAC), widely used in online social networks, offers the ability to consider user relationships in defining access control decisions and supports policy individualization. However, to the best of our knowledge, no such attempt has been made to develop a formal ReBAC model for smart IoT systems. This paper proposes a ReBAC IoT dynamic and fine-grained access control model which considers the social relationships among users along with the attributes to support an attributes-aware relationship-based access control model for smart IoT systems. ReBAC IoT is formally defined, illustrated through different use cases, implemented, and tested.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/16488612
