Dynamic Access Control Policy based on Blockchain and Machine Learning for the Internet of Things

Abstract

The Internet of Things (IoT) is now destroying the barriers between the real and digital worlds. However, one of the huge problems that can slow down the development of this global wave, or even stop it, concerns security and privacy requirements. The criticality of these latter comes especially from the fact that the smart objects may contain very intimate information or even may be responsible for protecting people’s lives. In this paper, the focus is on access control in the IoT context by proposing a dynamic and fully distributed security policy. Our proposal will be based, on one hand, on the concept of the blockchain to ensure the distributed aspect strongly recommended in the IoT; and on the other hand on machine learning algorithms, particularly on reinforcement learning category, in order to provide a dynamic, optimized and self-adjusted security policy.

Authors and Affiliations

Aissam OUTCHAKOUCHT, Hamza ES-SAMAALI, Jean Philippe LEROY

Keywords

Related Articles

Scalable Scientific Workflows Management System SWFMS

In today’s electronic world conducting scientific experiments, especially in natural sciences domain, has become more and more challenging for domain scientists since “science” today has turned out to be more complex due...

Cost Optimization of Cloud Computing Services in a Networked Environment

Cloud computing service providers' offer their customers' services maximizing their revenues, whereas customers wish to minimize their costs. In this paper we shall concentrate on consumers' point of view. Cloud computin...

Community Perception of the Security and Acceptance of Mobile Banking Services in Bahrain: An Empirical Study

Bahraini banks and financial organizations have applied remote enabled service using the internet and a mobile device to increase efficiency, reduce costs and improve quality of services. There is need for these organiza...

Improved Sliding Mode Nonlinear Extended State Observer based Active Disturbance Rejection Control for Uncertain Systems with Unknown Total Disturbance

This paper presents a new strategy for the active disturbance rejection control (ADRC) of a general uncertain system with unknown bounded disturbance based on a nonlinear sliding mode extended state observer (SMESO). Fir...

Fault Attacks Resistant Architecture for KECCAK Hash Function

The KECCAK cryptographic algorithms widely used in embedded circuits to ensure a high level of security to any systems which require hashing as the integrity checking and random number generation. One of the most efficie...

Download PDF file
  • EP ID EP260618
  • DOI 10.14569/IJACSA.2017.080757
  • Views 73
  • Downloads 0

How To Cite

Aissam OUTCHAKOUCHT, Hamza ES-SAMAALI, Jean Philippe LEROY (2017). Dynamic Access Control Policy based on Blockchain and Machine Learning for the Internet of Things. International Journal of Advanced Computer Science & Applications, 8(7), 417-424. https://europub.co.uk/articles/-A-260618