Trust evaluation and management in e-commerce systems using artificial intelligence and emerging technologies

The internet market has a lack of physical presence and physical indication; therefore, it is more complex and difficult to bring trust between sellers and buyers. This is what distinguishes it as a big obstacle for businesses engaged in the several applications of e-commerce platforms. Moreover, it is essential to recognize influences, which enables to create customer interest in e-commerce, and consumers can feel reliable and get interested to buy on an e-commerce platform frequently. Therefore, there is an alarming demand to deal with the aforementioned issues and how to create a trust evaluation-based model that provides feasible support for both current and past sales. The proposed research comprises several trust hypotheses, a business case review, and primary data selections to establish a more reliable and diverse database. The purpose was to examine customer trust from a personal perspective and to decide if the variables of trust are positively influenced by personal characteristics, culture, and experience. The overall objectives of this proposed research are to examine that how to build trust in online markets such as in e-commerce applications, also to investigate the impact of trust between sellers and buyers during their active interaction and online trust formation process. This work is particularly concerned with how different types of users (online stores and internet users) use trust in their trust-building practices. The relationship between trust variables and risks associated with trust adoption was not provided by researchers in existing work. Researchers have failed to explore the dilemma in a multifaceted and multidimensional manner. To deal with these issues, the first contribution provides an effective method that considersthree dimensions that play important roles in any online transaction to help thebuyers to detect fraud. This method measures the similarity between the newtransaction and the past transactions in the products types dimension, the numberof the products sold dimension, and the transactions amount dimension.Our second contribution utilises the trust evaluation between the transactions bymeasuring the similarities between the new transactions of a purchaser and theprevious sales record of a buyer. The proposed model is capable to normalise severaluser evaluations after following their evaluation criteria, which continuously changeswith time. This model also investigates trust and reputation for all users based onthe general merchant rating and the aspects of the transaction time, both havea significant role in any online transaction to help customers gain trust in onlineshopping and identify the frauds. Overall, our model based on eBay and Epinionstransaction datasets derives stable trust values from immutable transactions.Our third contribution is based on mining customer’s comments and feedback expressed in free text. We introduce an algorithm for extracting input on measurements weights, integrating natural language processing methods, information extraction, and subject/topic modelling. Evaluation based on Amazon data sets enables us to demonstrate that order of importance for our predefined dimensions is Rating, Product Type, Price, Time interval, and Quantity Sold. The final contribution is designed in collaboration with the Software-Defined Networking (SDN) and blockchain. SDN allows versatile implementation and advancement of modern networking applications due to the programmability approach, and decoupling of the control plane from the data plane, the concept and way of developing and operating interconnected networks has evolved dramatically and reduced the obstacles in the e-commerce markets. Moreover, SDN also experiences a variety of challenges, such as trust limitation and single point failure in a distributed network framework. Blockchain-based SDN has become an evolving architecture to protect a distributed network framework with the introduction of blockchainapplications. In this model, the major objective of our research is to optimize the security between various E-commerce applications/businesses, also to mitigate the single point failure of security vulnerabilities via Blockchain-based SDN framework. Our proposed model also utilises the trust between E-commerce applications with the help of blockchain-based trust key distribution.