Abstract:
The birth of Blockchain technology in the form of Bitcoin, has triggered a wide interest by demonstrating the possibility of eliminating the need of need of an intermediary and revolutionized the interactions between people and machines by increasing trust. Initially restricted to the domain of cryptocurrencies, people started realizing the potential of technology to go beyond just cryptocurrencies which led to the adoption of blockchain technology to solve real-world scenarios.One such scenario is the problems in e-governance systems among the public domain sectors. For the scope of this thesis we mainly focused on the problems inLand record and revenue sectors.In this thesis, we analyze the integration of blockchain technology to the existing business processes and in doing so, we address problems such as data integrity,privacy, and more importantly the lack of common platform between the organizations involved. The evolution of blockchain technology led to the introduction of permissioned blockchain platforms, Hyperledger Fabric is a leading permissioned blockchain platform which is used in the development of our project.Finally the objective of this thesis is to evaluate the performance of blockchain based implementation of a land revenue & recording automation system.

Gunda Abhishek

Abstract:
Privacy is a fundamental right for every human, but in today’s world, this is not ensured in every sector. The health sector is such an example where patients privacy is not respected, and sensitive data like prescription dosages, medical bill amounts and their entire medical history are leaked online without any encryption. We designed, implemented and deployed an architecture in this research where we tried to use PKI infrastructure and Hyperledger fabric and simulated workflow of healthcare sector while ensuring that patients’ medical records are in complete control of patient only. Hyperledger fabric, which is a blockchain framework, provides integrity to the medical records, which can be verified at any later point of time. Proxy re-encryption has been used to provide medical records access to others but only with permission from the patient. Besides patients and hospitals, this architecture also involves other institutions like insurance companies and pharmacies to provide various services to the patients. Lastly, we performed some performance experiments on the architecture to check the throughput and latencies.

Devendra K Meena

Abstract:
Since the introduction of the Bitcoin, the world’s first decentralized currency bySatoshi Nakamoto , both academic and industrial interest in blockchain technology has exploded. Blockchains can be categorized into two broad classes: permissionless and permissioned blockchain systems.Hyperledger Fabric is a permissioned blockchain system for running distributed applications. Fabric has a modular architecture and provides support for pluggable consensus. Currently, it has two consensus mechanisms namely Solo and Kafka ordering services which are not byzantine fault tolerant.In this thesis, we present the secure sharding blockchain agreement protocol namely Elastico in Hyperledger Fabric v1.4. We implement a new consensus mechanism in Fabric which prevents the system from byzantine failures.Based on our implementation of Elastico in Fabric v1.4, we observe that it is not better than Kafka in terms of throughput. Despite lower throughput, the implementation of Elastico is byzantine fault tolerant.

Ayushi Agarwal

Abstract:
Ethereum is a platform where users can build and deploy decentralized applications and smart contracts. The participants in the Ethereum network are ’pseudo-anonymous’ which makes it almost impossible to detect anomalous behaviour in the system. Thus, it serves as a noteworthy place to perform some malicious activity and then go undetected. With the sudden hype of blockchain technology, anomaly detection also received much attention in the past decade. Anomalies in the network are the ones who execute fraudulent trans-actions or whose behavior is abnormal. The abnormalities must be detected and removed as early as possible to ensure the faith of participants on the largest blockchain platform.There exists lots of work on the Bitcoin cryptocurrency in which they performed well, but this thesis presents work on anomaly detection in the Ethereum for the first time to the best of our knowledge.In this thesis, we considered anomaly detection for Ethereum network using machine learning techniques. Our goal is to detect which users are most suspicious. To this end,we have used various machine learning classifiers on Ethereum transaction data. We evaluated the accuracy and precision of each method and backed them with experimental results. Next, we have done some graph-based analysis on Ethereum data. We also tried to deduce the similarity index for smart contracts based on user interaction. We can use these methods for any setting which has an internal graph structure. We have chosenEthereum due to its availability and popularity of the dataset. This work provides a good starting point for anomaly detection on Ethereum Network.

Ajay Singh

Abstract:
Ethereum is the second most valuable cryptocurrency, just after Bitcoin. The biggest difference between Bitcoin and Ethereum is the ability to write smart contracts - small programs that sit on the blockchain. As the contracts are on the blockchain, they become immutable making them attractive for various decentralised applications (or dApps) like e-governance, healthcare manage-ment and data provenance.However, the biggest advantage of smart contracts - their immutability also poses the biggest threat from a security standpoint. This is because any bug found in the smart contract after deployment cannot be patched. Recent attacks like the DAO attack and the Parity attack have caused massive monetary losses. In such a scenario it becomes imperative to develop and interact with smart contracts that are secure.In this thesis we analyze the Ethereum Smart Contracts from a security viewpoint. We present a study of the security vulnerabilities observed in Ethereum smart contracts and develop a novel taxonomy for the same. We then analyse the different security tools available. For this, we create vulnerability benchmark – a set of 180 vulnerable contracts across different categories identified in the taxonomy. The results of the tools on this benchmark are analysed to help developers and end-users make an informed decision about which tool to use depending on their use-cases.We further collect byte-codes for 1.9M smart contracts from the main Ethereum blockchain and analyse them on various parameters like duplicity, total ether balance, etc. We observe that a small fraction of contracts dominate the others on every parameter we analysed. These 2900 contracts are identified as ‘Contracts of Importance’ and are further analysed using the tools available to gain valuable insights into the insecurity patterns and trends in Ethereum smart contracts.

Bishwas C Gupta