PPSDT: A Novel Privacy-Preserving Single Decision Tree Algorithm for Clinical Decision-Support Systems Using IoT Devices

Abstract

Medical service providers offer their patients high quality services in return for their trust and satisfaction. The Internet of Things (IoT) in healthcare provides different solutions to enhance the patient-physician experience. Clinical Decision-Support Systems are used to improve the quality of health services by increasing the diagnosis pace and accuracy. Based on data mining techniques and historical medical records, a classification model is built to classify patients’ symptoms. In this paper, we propose a privacy-preserving clinical decision-support system based on our novel privacy-preserving single decision tree algorithm for diagnosing new symptoms without exposing patients’ data to different network attacks. A homomorphic encryption cipher is used to protect users’ data. In addition, the algorithm uses nonces to avoid one party from decrypting other parties’ data since they all will be using the same key pair. Our simulation results have shown that our novel algorithm have outperformed the Naïve Bayes algorithm by 46.46%; in addition to the effects of the key value and size on the run time. Furthermore, our model is validated by proves, which meet the privacy requirements of the hospitals’ datasets, frequency of attribute values, and diagnosed symptoms.

A Comprehensive Survey on Secure Outsourced Computation and Its Applications

“…After that, the trained model can be applied to homomorphically predict k most possible diseases for a new patient. Adapted from the work [7], Alabdulkarim et al [209] also implemented a secure clinical decision system utilizing decision tree algorithm. The simulation experiment shows that the proposed scheme achieves better results than the one using naïve Bayesian algorithm [7].…”

Privacy and Security for Resource-Constrained IoT Devices and Networks: Research Challenges and Opportunities

“…In the paper entitled “BeeKeeper 2.0: Confidential Blockchain-Enabled IoT System with Fully Homomorphic Computation” [6], Zhou et al proposed a decentralized computation outsourcing scheme based on fully homographic computation. The test results demonstrated the effectiveness of the proposed scheme in resource-constrained devices.…”

Complex Pignistic Transformation-Based Evidential Distance for Multisource Information Fusion of Medical Diagnosis in the IoT

“…Thanks to the development of information and communication technologies, the IoT is becoming ubiquitous in all kinds of applications. On the other hand, it is well known that clinical medical service is complex, in which the collection, preservation, analysis, and fusion of patient information takes much time and labor many materials [ 3 , 4 ]. Furthermore, traditional medical systems cannot diagnose patients with a high level decision-making due to a single information source, and this affects the quality of clinical medical service.…”