Method to Increase Dependability in a Cloud-Fog-Edge Environment

Robots can be very different, from humanoids to intelligent self-driving cars or just IoT systems that collect and process local sensors’ information. This paper presents a way to increase dependability for information exchange and processing in systems with Cloud-Fog-Edge architectures. In an ideal interconnected world, the recognized and registered robots must be able to communicate with each other if they are close enough, or through the Fog access points without overloading the Cloud. In essence, the presented work addresses the Edge area and how the devices can communicate in a safe and secure environment using cryptographic methods for structured systems. The presented work emphasizes the importance of security in a system’s dependability and offers a communication mechanism for several robots without overburdening the Cloud. This solution is ideal to be used where various monitoring and control aspects demand extra degrees of safety. The extra private keys employed by this procedure further enhance algorithm complexity, limiting the probability that the method may be broken by brute force or systemic attacks.

[1]  Hajar Mousannif,et al.  Data quality in internet of things: A state-of-the-art survey , 2016, J. Netw. Comput. Appl..

[2]  Iqbal H. Sarker,et al.  A Survey of Context-Aware Access Control Mechanisms for Cloud and Fog Networks: Taxonomy and Open Research Issues , 2020, Sensors.

[3]  Liviu Miclea,et al.  Remotely Operated Robot with Live Camera Feed , 2019 .

[4]  Karin Bernsmed Accountable Health Care Service Provisioning in the Cloud , 2014, 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing.

[5]  Khaled M. Khan Security Dynamics of Cloud Computing , 2009 .

[6]  Ovidiu Stan,et al.  Smart environmental monitoring beacon , 2018, 2018 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR).

[7]  Antonio Iera,et al.  The Internet of Things: A survey , 2010, Comput. Networks.

[8]  Paul J. M. Havinga,et al.  Resource Management Techniques for Cloud/Fog and Edge Computing: An Evaluation Framework and Classification , 2021, Sensors.

[9]  N. Jazdi,et al.  Cyber physical systems in the context of Industry 4.0 , 2014, 2014 IEEE International Conference on Automation, Quality and Testing, Robotics.

[10]  Fulong Chen,et al.  An Aggregate Signature Scheme Based on a Trapdoor Hash Function for the Internet of Things , 2019, Sensors.

[11]  M. Ali Babar,et al.  Architectural Resilience in Cloud, Fog and Edge Systems: A Survey , 2020, IEEE Access.

[12]  Amir Masoud Rahmani,et al.  Reliability and high availability in cloud computing environments: a reference roadmap , 2018, Human-centric Computing and Information Sciences.

[13]  H. J. Cai,et al.  The Integer Factorization Algorithm With Pisano Period , 2019, IEEE Access.

[14]  Nicholas Kyriakopoulos,et al.  A comparative analysis of network dependability, fault-tolerance, reliability, security, and survivability , 2009, IEEE Communications Surveys & Tutorials.

[15]  Carl E. Landwehr,et al.  Basic concepts and taxonomy of dependable and secure computing , 2004, IEEE Transactions on Dependable and Secure Computing.

[16]  Moussa Ayyash,et al.  Edge-Computing Architectures for Internet of Things Applications: A Survey , 2020, Sensors.

[17]  Taher El Gamal A public key cryptosystem and a signature scheme based on discrete logarithms , 1984, IEEE Trans. Inf. Theory.

[18]  Rolf H. Weber,et al.  Internet of Things - Legal Perspectives , 2010 .

[19]  Muhammad Attique,et al.  Analytical Study of Hybrid Techniques for Image Encryption and Decryption , 2020, Sensors.

[20]  Jung Hee Cheon,et al.  A New Approach to Discrete Logarithm Problem with Auxiliary Inputs , 2012, IACR Cryptol. ePrint Arch..

[21]  Donato Di Paola,et al.  IoT-aided robotics applications: Technological implications, target domains and open issues , 2014, Comput. Commun..

[22]  Thomas Fahringer,et al.  A reliability-aware resource provisioning scheme for real-time industrial applications in a Fog-integrated smart factory , 2019, Microprocess. Microsystems.

[23]  Zièd Choukair,et al.  Trust Assurance in Cloud Services with the Cloud Broker Architecture for Dependability , 2015, 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems.

[24]  Xin Wang,et al.  A Secure and Verifiable Outsourced Access Control Scheme in Fog-Cloud Computing , 2017, Sensors.

[25]  Katia Obraczka,et al.  Phantom of the cloud: Towards improved cloud availability and dependability , 2015, 2015 IEEE 4th International Conference on Cloud Networking (CloudNet).

[26]  Nishant Doshi,et al.  Security and Privacy Issues in Cloud, Fog and Edge Computing , 2019, EUSPN/ICTH.

[27]  Antonio Iera,et al.  Understanding the Internet of Things: definition, potentials, and societal role of a fast evolving paradigm , 2017, Ad Hoc Networks.

[28]  Jidong Huang,et al.  Study on the use of Microsoft Kinect for robotics applications , 2012, Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium.

[29]  Uwe Aßmann,et al.  A Capability-based Framework for Programming Small Domestic Service Robots , 2015 .