Visible to the public Secure Real-Time Heterogeneous IoT Data Management System

TitleSecure Real-Time Heterogeneous IoT Data Management System
Publication TypeConference Paper
Year of Publication2019
AuthorsIslam, M. S., Verma, H., Khan, L., Kantarcioglu, M.
Conference Name2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)
Date Publisheddec
Keywordsauthorisation, cloud, cloud computing, composability, cryptography, cyber-physical system security, Data analysis, data privacy, Data security, diverse IoT devices, drone-based data, drones, edge computing, edge device, embedded devices, end-to-end data encryption mechanism, heterogeneous data, Internet of Things, IoT, IoT devices, IOT edge computing, large-scale data analytics, machine learning, neural style transfer, on-device computing, performance evaluation, Predictive Metrics, pubcrawl, real-time data collection, real-time data processing system, real-time monitoring, Real-time Systems, Resiliency, Scalability, secure platform, secure real-time heterogeneous IoT data management, secure systems, security, sensitive data, Software, streaming IoT data, surveillance, time data analytics system, Trusted Execution Environment, trusted platform modules
AbstractThe growing adoption of IoT devices in our daily life engendered a need for secure systems to safely store and analyze sensitive data as well as the real-time data processing system to be as fast as possible. The cloud services used to store and process sensitive data are often come out to be vulnerable to outside threats. Furthermore, to analyze streaming IoT data swiftly, they are in need of a fast and efficient system. The Paper will envision the aspects of complexity dealing with real time data from various devices in parallel, building solution to ingest data from different IOT devices, forming a secure platform to process data in a short time, and using various techniques of IOT edge computing to provide meaningful intuitive results to users. The paper envisions two modules of building a real time data analytics system. In the first module, we propose to maintain confidentiality and integrity of IoT data, which is of paramount importance, and manage large-scale data analytics with real-time data collection from various IoT devices in parallel. We envision a framework to preserve data privacy utilizing Trusted Execution Environment (TEE) such as Intel SGX, end-to-end data encryption mechanism, and strong access control policies. Moreover, we design a generic framework to simplify the process of collecting and storing heterogeneous data coming from diverse IoT devices. In the second module, we envision a drone-based data processing system in real-time using edge computing and on-device computing. As, we know the use of drones is growing rapidly across many application domains including real-time monitoring, remote sensing, search and rescue, delivery of goods, security and surveillance, civil infrastructure inspection etc. This paper demonstrates the potential drone applications and their challenges discussing current research trends and provide future insights for potential use cases using edge and on-device computing.
Citation Keyislam_secure_2019