A Prospect Theoretic Approach for Trust Management in IoT Networks under Manipulation Attacks

Abstract

As Internet of Things (IoT) and Cyber-Physical systems become more ubiquitous in our daily lives, it necessitates the capability to measure the trustworthiness of the aggregate data from such systems to make fair decisions. However, the interpretation of trustworthiness is contextual and varies according to the risk tolerance attitude of the concerned application. In addition, there exist varying levels of uncertainty associated with an evidence upon which a trust model is built. Hence, the data integrity scoring mechanisms require some provisions to adapt to different risk attitudes and uncertainties.In this paper, we propose a prospect theoretic framework for data integrity scoring that quantifies the trustworthiness of the collected data from IoT devices in the presence of adversaries who try to manipulate the data. In our proposed method, we consider an imperfect anomaly monitoring mechanism that tracks the transmitted data from each device and classifies the outcome (trustworthiness of data) as not compromised, compromised, or undecided. These outcomes are conceptualized as a multinomial hypothesis of a Bayesian inference model with three parameters. These parameters are then used for calculating a utility value via prospect theory to evaluate the reliability of the aggregate data at an IoT hub. In addition, to take into account different risk attitudes, we propose two types of fusion rule at IoT hub-optimistic and conservative.Furthermore, we put forward asymmetric weighted moving average (AWMA) scheme to measure the trustworthiness of aggregate data in presence of On-Off attacks. The proposed framework is validated using extensive simulation experiments for both uniform and On-Off attacks. We show how trust scores vary under a variety of system factors like attack magnitude and inaccurate detection. In addition, we measure the trustworthiness of the aggregate data using the well-known expected utility theory and compare the results with that obtained by prospect theory. The simulation results reveal that prospect theory quantifies trustworthiness of the aggregate data better than expected utility theory.

A Survey on Consensus Methods in Blockchain for Resource-constrained IoT Networks

“…Adoption of IoT based technologies are poised to make a big impact on various sectors of our daily lives, including energy, manufacturing, intelligent transportation and smart cities. With more and more autonomous deployments of potentially large-scale IoT systems, ensuring security, availability and confidentiality of the data, the devices and the networks become utmost critical [1,2].…”

“…PL. denotes permissionless and P. denotes permissioned 2. Low throughput is less than 100 TPS (transaction per second), medium throughput is between 100 TPS and 1000 TPS, and high throughput is more than 1000 TPS 3.…”