ABSTRACT
Imagine returning home tired in the evening and being greeted by your IoT-enabled lock on the front door that says: ‘Cheer up! Welcome back to your home located at XYZ Street’.
Yes, this is possible!
As the IoT devices permeate our daily lives, it is also mandatory to club them to the authentic users, irrespective of their glasses, scarves, dim-lit conditions and, of course, their expressions and their state of mind.
IoT as a technology has the immense potential to revolutionize all aspects of modern life ranging from healthcare to logistics, household appliances, entertainment and transportation. However, challenges follow avant-garde. Reliability and security are major concerns in different layers of any IoT system due to the highly unreliable nature of the underlying wireless channel and physical vulnerabilities. This is expedited by the exponential growth of the number of devices and our dependency on them. It calls for development of policies and governance strategies without restricting innovation. The paper discusses several challenges in this domain and proposes a user-defined biometric-based asymmetric cryptographic algorithm for security. Textual and image datasets are presently in use. We propose a genetic-based approach to perform mutation and crossover on the data so as to provide better performance. There exist more than 100 unique public-private key pairs for data encryption and decryption. The butterfly effect is used to determine the performance of the proposed asymmetric cipher. Results show that our cipher is providing the butterfly effect with above 50% sensitivity of key and plaintext. Analysis is performed using Python via Anaconda Jupyter Notebook. The images are processed using the Open Source Computer Vision Library. IoT simulation is done using OMNeT++.
