Prabal Banerjee

Prabal Banerjee, Chander Govindarajan, Praveen Jayachandran et al.

Content sharing platforms such as Youtube and Vimeo have promoted pay per view models for artists to monetize their content. Yet, artists remain at the mercy of centralized platforms that control content listing and advertisement, with little transparency and fairness in terms of number of views or revenue. On the other hand, consumers are distanced from the publishers and cannot authenticate originality of the content. In this paper, we develop a reliable and fair platform for content sharing without a central facilitator. The platform is built as a decentralized data storage layer to store and share content in a fault-tolerant manner, where the peers also participate in a blockchain network. The blockchain is used to manage content listings and as an auditable and fair marketplace transaction processor that automatically pays out the content creators and the storage facilitators using smart contracts. We demonstrate the system with the blockchain layer built on Hyperledger Fabric and the data layer built on Tahoe-LAFS,and show that our design is practical and scalable with low overheads.

Subhra Mazumdar, Prabal Banerjee, Sushmita Ruj

Lightning Network can execute unlimited number of off-chain payments, without incurring the cost of recording each of them in the blockchain. However, conditional payments in such networks is susceptible to Griefing Attack. In this attack, an adversary doesn't resolve the payment with the intention of blocking channel capacity of the network. We propose an efficient countermeasure for the attack, known as Griefing-Penalty. If any party in the network mounts a griefing attack, it needs to pay a penalty proportional to the collateral cost of executing a payment. The penalty is used for compensating affected parties in the network. We propose a new payment protocol HTLC-GP or Hashed Timelock Contract with Griefing-Penalty to demonstrate the utility of the countermeasure. Upon comparing our protocol with existing payment protocol Hashed Timelock Contract, we observe that the average revenue earned by the attacker decreases substantially for HTLC-GP as compared to HTLC. We also study the impact of path length for routing a transaction and rate of griefing-penalty on the budget invested by an adversary for mounting the attack. The budget needed for mounting griefing attack in HTLC-GP is 12 times more than the budget needed by attacker in HTLC, given that each payment instance being routed via path length of hop count 20.

Prabal Banerjee, Nishant Nikam, Subhra Mazumdar et al.

Data owners upload large files to cloud storage servers, but malicious servers may potentially tamper data. To check integrity of remote data, Proof of Retrievability (PoR) schemes were introduced. Existing PoR protocols assume that data owners and third-party auditors are honest and audit only the potentially malicious cloud server to check integrity of stored data. In this paper we consider a system where any party may attempt to cheat others and consider collusion cases. We design a protocol that is secure under such adversarial assumptions and use blockchain smart contracts to act as mediator in case of dispute and payment settlement. We use state channels to reduce blockchain interactions in order to build a practical audit solution. We implement and evaluate a prototype using Ethereum as the blockchain platform and show that our scheme has comparable performance.

Prabal Banerjee, Sushmita Ruj

Data is of unprecedented importance today. The most valuable companies of today treat data as a commodity, which they trade and earn revenues. To facilitate such trading, data marketplaces have emerged. Present data marketplaces are inadequate as they fail to satisfy all the desirable properties - fairness, efficiency, security, privacy and adherence to regulations. In this article, we propose a blockchain enabled data marketplace solution that fulfills all required properties. We outline the design, show how to design such a system and discuss the challenges in building a complete data marketplace.