Cloud and Internet of Things: Challenges and Opportunities Minitrack

Permanent URI for this collection

https://hdl.handle.net/10125/42638

The Cloud and the burgeoning Internet of Things as supported in The Internet raises broad security issues given the last several years of attacks on both public as well as private sector computers and related hardware. 0 day attacks such at Stuxnet have shown us that operational hardware in the critical infrastructure that supports day-to-day life on this planet can be disrupted and in fact destroyed. The list of attacks is endless, and the dollar loss is in the multiple millions if not billions of dollars.

This Minitrack will seek both short and long term solutions to these security issues, and boldly asks the question: Is the current Internet topology, and its aging protocols reliable enough or even suitable to securely support the potential billions of interconnected devices in the above context? We anticipate submissions not limited to, but in the scope of the following topics:

  • Trustworthy IoT and Cloud infrastructure
  • IoT embedded trust and security
  • IoT architectures
  • End-to-End security for IoT
  • Quality Assurance Techniques for Secure IoT
  • Mobile and Peer-to-Peer clouds
  • Security of Public versus Private Cloud and IoT services
  • Preventing Intellectual Property and Personal Information theft
  • Monitoring, auditing Cloud and IoT Services
  • Identity management in the Cloud and IoT
  • Data privacy and availability in the Cloud and IoT
  • Customer migration from one Cloud provider to another
  • Data in the Cloud and territories (Safe-Harbor)
  • Secure Cloud and IoT interoperability and Service Level Agreements
  • Rights and Policy Management in Cloud Computing and IoT Services
  • Governance, Risk and Compliance in Cloud Computing and IoT Services
  • Security in the Social Cloud of Things
  • Data Breaches and Data Loss
  • Ethical, social and legal issues in Cloud Computing and IoT
  • Ethical dilemmas in autonomous IoT systems
  • Data protection, IoT and quantified self
  • Virtual partitions of the Internet to separate critical resources from public access

Minitrack Co-Chairs:

William Yeager (Primary Contact)
Stanford University Retired
Email: byeager@fastmail.fm

Jean-Henry Morin
University of Geneva, Switzerland
Email: Jean-Henry.Morin@unige.ch

Browse

Recent Submissions

Now showing 1 - 4 of 4
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    Privacy of the Internet of Things: A Systematic Literature Review
    (2017-01-04) Aleisa, Noura; Renaud, Karen
    The Internet of Things’ potential for major privacy invasion is a concern. This paper reports on a systematic literature review of privacy-preserving solutions appearing in the research literature and in the media. We analysed proposed solutions in terms of the techniques they deployed and the extent to which they satisfied core privacy principles. We found that very few solutions satisfied all core privacy principles. We also identified a number of key knowledge gaps in the course of the analysis. In particular, we found that most solution providers assumed that end users would be willing to expend effort to preserve their privacy; that they would be motivated to take action to ensure that their privacy was respected. The validity of this assumption needs to be proved, since it cannot simply be assumed that people would necessarily be willing to engage with privacy-preserving solutions. We suggest this as a topic for future research.
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    Design of Smart Factory Web Services Based on the Industrial Internet of Things
    (2017-01-04) Jung, Jieun; Song, Byunghun; Watson, Kym; Usländer, Thomas
    The Industrial Internet of Things (IIoT) is cited as the latest means for making manufacturing more flexible, cost effective, and responsive to changes in customer demands. However, a major concern surrounding the IIoT is interoperability between devices and machines that function within different protocols and architectures. This paper presents the Smart Factory Web (SFW), which is based on the IIoT concept of improving factory-to-factory interoperability. The proposed SFW enables secure data and service integration in cross-site application scenarios as well as ‘plug & work’ functions for devices, machines, and data analytics software by applying industrial standards, Open Platform Communications Unified Architecture (OPC UA), and Automation Markup Language (AutomationML). To reach the goal, experimental factories that have heterogeneous manufacturing infrastructures are linked and the SFW is implemented in four phases. The usage scenario, called order-driven adaptive production, used to align capacity across factories, will also be validated in the real deployment.
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    ConTaaS: An Approach to Internet-Scale Contextualisation for Developing Efficient Internet of Things Applications
    (2017-01-04) Yavari, Ali; Jayaraman, Prem Prakash; Georgakopoulos, Dimitrios; Nepal, Surya
    The Internet of Things (IoT) is a new internet evolution that involves connecting billions of sensors and other devices to the Internet. Such IoT devices or IoT things can communicate directly. They also allow Internet users and applications to access and distil their data, control their functions, and harness the information and functionality provided by multiple IoT devices to offer novel smart services. IoT devices collectively generate massive amounts of data with an incredible velocity. Processing IoT device data and distilling high-value information from them presents an Internet-scale computational challenge. Contextualisation of IoT data can help improve the value of information extracted from IoT. However, existing contextualisation techniques can only handle small datasets from a modest number of IoT devices. In this paper, we propose a general-purpose architecture and related techniques for the contextualisation of IoT data. In particular, we introduce a Contextualisation-as-a-Service (ConTaaS) architecture that incorporates scalability improving techniques, as well as a proof-of-concept implementation of all these that utilises elastic cloud-based infrastructure to achieve near real-time contextualisation of IoT data. Experimental evaluations validating the efficiency of ConTaaS are also provided in this paper.
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