Cyber Physical Systems

Cyber-Physical Systems (CPS) represent a pivotal paradigm at the intersection of computer science, engineering, and various scientific domains. These systems seamlessly integrate computational algorithms with physical processes, creating interconnected networks where the digital and physical realms converge. exemplify the fusion of digital intelligence and physical operations, revolutionizing numerous domains. In the realm of transportation, self-driving cars are prime instances, where intricate algorithms interact with the car's sensors and actuators to navigate through real-world environments. Smart grids showcase CPS in energy management, enabling dynamic adjustments of power distribution based on real-time demand and supply data. In healthcare, wearable devices collect vital signs and relay them to medical professionals, facilitating remote monitoring and timely interventions. Industrial automation leverages CPS to optimize manufacturing processes by integrating sensors, robotics, and data analytics to enhance efficiency and reduce errors. These examples underscore how CPS bridges the gap between the virtual and physical realms, propelling innovation and efficiency across diverse sectors. 

Smart Grids

The first kind of CPS that we have targeted is the smart grids. The smart grid represents a cutting-edge evolution in the way we manage and distribute electrical power. It is a sophisticated network that integrates advanced technologies, communication systems, and real-time data analytics to optimize the generation, transmission, distribution, and consumption of electricity. Unlike traditional grids, the smart grid enables bidirectional communication between utilities and consumers, allowing for more precise monitoring and control of energy flow. This two-way interaction facilitates dynamic adjustments based on real-time demand, promotes the integration of renewable energy sources, and enhances overall grid reliability and resilience. By employing sensors, smart meters, and automation, the smart grid reduces energy wastage, lowers costs, and minimizes environmental impact. Ongoing research focuses on cybersecurity measures to protect against potential threats, as well as the development of advanced algorithms that enable predictive maintenance, demand response, and energy storage integration. The smart grid exemplifies the fusion of technology and energy management, offering a blueprint for a more efficient, sustainable, and adaptable energy future. 

Electric Vehicles

Electric vehicles (EVs) are our next focus within the galaxy of CPS applications. Over the years, EVs have emerged as a transformative solution in the quest for sustainable transportation. Ongoing research in this field is geared towards addressing key challenges and further enhancing EV technology. Battery advancements are a focal point, aiming to extend range, reduce charging times, and increase overall lifespan. Innovations in materials science are vital for creating more efficient and cost-effective batteries. Moreover, researchers are working on developing smart charging infrastructure and vehicle-to-grid (V2G) systems, enabling bidirectional energy flow between EVs and the grid, thereby enhancing grid stability and optimizing energy utilization. AI and machine learning are also being integrated to enhance energy management, predicting charging patterns and optimizing driving efficiency. Addressing environmental concerns, investigations into recycling methods for used EV batteries are gaining prominence. Collaborative efforts across engineering, chemistry, and data science are driving the evolution of electric vehicles, fostering a cleaner and more sustainable future for transportation. 

I have worked on Fully Homomorphic Encryption as part of my final year M.Tech project at CSIR Fourth Paradigm Institutute (CMMACS), Bangalore. Fully homomorphic encryption is an advanced cryptographic scheme that allows to perform some specific operations on the data which is encrypted so as to obtain an encrypted result. The encrypted result when decrypted using the proper key is equivalent/ same as if the operations were carried out on the original data without encryption. The notion was originally proposed by Rivest, Shamir and Dertouzos in 1978. They named it privacy homomorphism and had observed that RSA scheme is multiplicative homomorphic. Since then, it has been an intense area of cryptographic research where the idea is to develop a Fully Homomorphic scheme that would support both binary multiplication and addition. It was in 2009 only, when IBM researcher Craig Gentry devised the first plausible construction of Fully homomorphic encryption.

My concentration was on

• Improvement of Gentry's FHE scheme.

• Analysis of various other construction of FHE and their security measurements.

• Implementation of existing FHE schemes.

• Develop an efficient and practical FHE for user specific applications.