Secure data compression and analytics for IoT

We have witnessed that the Internet of Things (IoT) provides novel ways for different verticals to acquire various data and gain valuable knowledge and insights by applying machine learning and data analytic techniques. IoT has shown great potential to improve efficiency and safety in home automation, industrial production, transportation, agriculture, energy management and many others. With the fast development of diverse IoT applications and an expected 50 to 500 billion sensor and actuation devices connected to the IoT in coming years, this imposes many critical challenges to future communication networks as well as storage and computing infrastructure. First, the massive amount of data is and will stress our current networking, storage, cloud computing installed capacity. Second, the unfulfilled need for strict and lightweight security and privacy in IoT has caused deep concerns among end-users. Security in IoT solutions has become one of the most important criteria for customers and users to select among a variety of IoT products and services. Therefore, to enable a sustainable growth, the IoT is in need of technologies that provide an end-to-end solution to securely and efficiently acquire, transfer, store and process massive amounts of sensor data, minimize the communication and transmission load and storage requirements.

This PhD project is partly financed by Innovation Fund Denmark and will focus on the development of data compression schemes with built-in security by leveraging advanced signal processing techniques for IoT ecosystem, as well as design and implementation of machine learning and data analytics on compressed and encrypted data. In particular, the applicant will bridge the fundamental theory in sparse signal processing with practice in implementation. The underlying goal of results is to develop new techniques for the benefit of entire IoT ecosystem, including sensor devices, and communication, storage and computation infrastructure. The applicant is expected to deploy such designs in practical systems to demonstrate the results.

Our group operates at the intersection of theory and implementation of coding, communication and computation, distributed systems, and Cloud/Edge technologies. For this reason, we encourage applicants with a strong theoretical profile or a strong implementation/programming profile (or ideally both) to apply. Our group also counts with a new and well-funded laboratory to deploy large storage servers pods (hundreds of TB each pod), computing servers, ARM micro-servers for energy efficient edge operations, software defined networking switches with built-in computation capabilities, and a number of end-user devices, single-board computers and sensors.

This project will have interactions with companies (e.g., Develco Products A/S) and local start-ups (e.g., Chocolate Cloud ApS) and is expected to result in high impact publications in journals, conference participation, and patent filings.

Our goal is to design and develop secure data compression and analytics for future IoT ecosystem leveraging advanced signal processing techniques.