A pinboard by
Ajay Chaudhary

Ph.D. Research Scholar, Indian Institute of Technology, Roorkee, India


Integration of IoT and Cloud Computing in order to deliver things as a service to the end user.

My research mainly focused Integrations of IoT and Cloud Computing for providing things as a service. The key aspects of my research are study and design IoT protocol for seamless communication between IoT devices and Cloud even in constraint environment, design low-power IoT devices and gateway to handle an enormous amount of IoT data. Also on the cloud side, i tries to develop an efficient algorithm to process the massive IoT data and get useful business logic out of it.


Privacy preserving Internet of Things: From privacy techniques to a blueprint architecture and efficient implementation

Abstract: The Internet of Things (IoT) is the latest web evolution that incorporates billions of devices that are owned by different organizations and people who are deploying and using them for their own purposes. IoT-enabled harnessing of the information that is provided by federations of such IoT devices (which are often referred to as IoT things) provides unprecedented opportunities to solve internet-scale problems that have been too big and too difficult to tackle before. Just like other web-based information systems, IoT must also deal with the plethora of Cyber Security and privacy threats that currently disrupt organisations and can potentially hold the data of entire industries and even countries for ransom. To realize its full potential, IoT must deal effectively with such threats and ensure the security and privacy of the information collected and distilled from IoT devices. However, IoT presents several unique challenges that make the application of existing security and privacy techniques difficult. This is because IoT solutions encompass a variety of security and privacy solutions for protecting such IoT data on the move and in store at the device layer, the IoT infrastructure/platform layer, and the IoT application layer. Therefore, ensuring end-to-end privacy across these three IoT layers is a grand challenge in IoT. In this paper, we tackle the IoT privacy preservation problem. In particular, we propose innovative techniques for privacy preservation of IoT data, introduce a privacy preserving IoT Architecture, and also describe the implementation of an efficient proof of concept system that utilizes all these to ensure that IoT data remains private. The proposed privacy preservation techniques utilise multiple IoT cloud data stores to protect the privacy of data collected from IoT. The proposed privacy preserving IoT Architecture and proof of concept implementation are based on extensions of OpenIoT - a widely used open source platform for IoT application development. Experimental evaluations are also provided to validate the efficiency and performance outcomes of the proposed privacy preserving techniques and architecture.

Pub.: 18 Mar '17, Pinned: 18 Sep '17

Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach

Abstract: Current developments in ICTs such as in Internet-of-Things (IoT) and Cyber–Physical Systems (CPS) allow us to develop healthcare solutions with more intelligent and prediction capabilities both for daily life (home/office) and in-hospitals. In most of IoT-based healthcare systems, especially at smart homes or hospitals, a bridging point (i.e., gateway) is needed between sensor infrastructure network and the Internet. The gateway at the edge of the network often just performs basic functions such as translating between the protocols used in the Internet and sensor networks. These gateways have beneficial knowledge and constructive control over both the sensor network and the data to be transmitted through the Internet. In this paper, we exploit the strategic position of such gateways at the edge of the network to offer several higher-level services such as local storage, real-time local data processing, embedded data mining, etc., presenting thus a Smart e-Health Gateway. We then propose to exploit the concept of Fog Computing in Healthcare IoT systems by forming a Geo-distributed intermediary layer of intelligence between sensor nodes and Cloud. By taking responsibility for handling some burdens of the sensor network and a remote healthcare center, our Fog-assisted system architecture can cope with many challenges in ubiquitous healthcare systems such as mobility, energy efficiency, scalability, and reliability issues. A successful implementation of Smart e-Health Gateways can enable massive deployment of ubiquitous health monitoring systems especially in clinical environments. We also present a prototype of a Smart e-Health Gateway called UT-GATE where some of the discussed higher-level features have been implemented. We also implement an IoT-based Early Warning Score (EWS) health monitoring to practically show the efficiency and relevance of our system on addressing a medical case study. Our proof-of-concept design demonstrates an IoT-based health monitoring system with enhanced overall system intelligence, energy efficiency, mobility, performance, interoperability, security, and reliability.

Pub.: 10 Feb '17, Pinned: 18 Sep '17

A unified face identification and resolution scheme using cloud computing in Internet of Things

Abstract: In the Internet of Things (IoT), identification and resolution of physical object is the crucial technology for authenticating object’s identity, controlling service access, and establishing trust between object and cloud service. With the development of computer vision and pattern recognition technologies, face has been used as a high-security identification and identity authentication method which has been deployed in various applications. Face identification can ensure the consistency between individual in physical-space and his/her identity in cyber-space during the physical-cyber space mapping. However, face is a non-code and unstructured identifier. With the increase of applications in current big data environment, the characteristic of face identification will result in the growing demands for computation power and storage capacity. In this paper, we propose a face identification and resolution scheme based on cloud computing to solve the above problem. The face identification and resolution system model is presented to introduce the processes of face identifier generation and matching. Then, parallel matching mechanism and cloud computing-based resolution framework are proposed to efficiently resolve face image, control personal data access and acquire individual’s identity information. It makes full use of the advantages of cloud computing to effectively improve computation power and storage capacity. The experimental result of prototype system indicates that the proposed scheme is practically feasible and can provide efficient face identification and resolution service.

Pub.: 04 Apr '17, Pinned: 18 Sep '17

Privacy-preserving protocols for secure and reliable data aggregation in IoT-enabled Smart Metering systems

Abstract: As the Internet of Things (IoT) gets more pervasive, its areas of usage expands. Smart Metering systems is such an IoT-enabled technology that enables convenient and high frequency data collection compared to existing metering systems. However, such a frequent data collection puts the consumers’ privacy in risk as it helps expose the consumers’ daily habits. Secure in-network data aggregation can be used to both preserve consumers’ privacy and reduce the packet traffic due to high frequency metering data. The privacy can be provided by performing the aggregation on concealed metering data. Fully homomorphic encryption (FHE) and secure multiparty computation (secure MPC) are the systems that enable performing multiple operations on concealed data. However, both FHE and secure MPC systems have some overhead in terms of data size or message complexity. The overhead is compounded in the IoT-enabled networks such as Smart Grid (SG) Advanced Metering Infrastructure (AMI). In this paper, we propose new protocols to adapt FHE and secure MPC to be deployed in SG AMI networks that are formed using wireless mesh networks. The proposed protocols conceal the smart meters’ (SMs) reading data by encrypting it (FHE) or computing its shares on a randomly generated polynomial (secure MPC). The encrypted data/computed shares are aggregated at some certain aggregator SM(s) up to the gateway of the network in a hierarchical manner without revealing the readings’ actual value. To assess their performance, we conducted extensive experiments using the ns-3 network simulator. The simulation results indicate that the secure MPC-based protocol can be a viable privacy-preserving data aggregation mechanism since it not only reduces the overhead with respect to FHE but also almost matches the performance of the Paillier cryptosystem when it is used within a proper sized AMI network.

Pub.: 24 Apr '17, Pinned: 18 Sep '17