Trusted Personalised Marketing Communications with Big Data Analytics for Product Offerings Using Encryption Algorithm

Abstract

Digital marketing is becoming popular and every organisation is trying to promote their business through digital adverting platforms. The service industry is known for personalisation where services are personalised as per the requirement of customers. The service ensures customer satisfaction and helps in retaining existing customers. In this research, a secure IoT environment with big data analytics is developed to achieve a Smart and secure environment. Initially, a Hadoop and Top-k query processing algorithm is proposed in this work to handle data acquisition, which reduces the redundancy in the collected data. Continuously, a Shannon-Fano algorithm is presented for data compression. To protect the confidentiality of big data, the system usually encrypted the big data before uploading them to the cloud. Accordingly, a Fully Homomorphic encryption algorithm is introduced to encrypt the data to enhance cloud storage security. Subsequently, to preserve improved privacy, secure data transportation, and data access management, the Secure and Robust Data Access Management (SRDAM) Algorithm is presented. Customers will be able to manage their consent, modify their profile, and fully control their data subject rights with the help of the proper consumer identity and access management solution. The proposed work is evaluated in the Matlab software and the performance metrics are accuracy, precision, recall, F1 score, and encryption time. The accuracy of the proposed method is approximately 3% higher than the existing Dnn4C, 6% than the RNN LM, 7.5% higher than the DNN LM, 8% higher than the SLAMC, and 9% higher than the N-gram methods. Accordingly, these results reveal that the proposed method has the best performance and it produces secure data transportation, and data access management, respectively.