Ram Govind Singh’s research while affiliated with Indian Statistical Institute and other places

The astounding growth of the Internet has generated digital asset extensively. Users are concerned about asset management so that the asset can be conveyed successfully to the descendent posthumously. Very few works have addressed designing and modeling of digital asset inheritance (DAI) from a technical design perspective. They have several inherent limitations such as incorrect death confirmation, high participation of nominee, the possibility of failure to obtain recovery key, and are based on many unreasonable assumptions, thus inefficient to design in the real life. In this paper, we have formalized the different categories of digital assets and defined the various security goals, required functionalities, and necessary entities to build an asset inheritance model. We have also proposed a new protocol named digital asset inheritance protocol (DAIP) using certificateless encryption (CLE) and identity-based system (IBS) to convey the user’s online persona efficiently to the descendent after his death. DAIP allows the nominee to successfully retrieve the asset after the user’s demise, even if a nominee is uninformed regarding the asset. We, then, provide rigorous security proofs of various properties using real–ideal worlds paradigm. Finally, we have implemented DAIP model using PBC and pycryptodome library. The simulation results affirm that it can be practically efficient to implement.

The Indian Personal Data Protection Bill 2019 provides a legal framework for protecting personal data. It is modeled after the European Union's General Data Protection Regulation(GDPR). We present a detailed description of the Bill, the differences with GDPR, the challenges and limitations in implementing it. We look at the technical aspects of the bill and suggest ways to address the different clauses of the bill. We mostly explore cryptographic solutions for implementing the bill. There are two broad outcomes of this study. Firstly, we show that better technical understanding of privacy is important to clearly define the clauses of the bill. Secondly, we also show how technical and legal solutions can be used together to enforce the bill.

Payment channel networks (PCN) are used in cryptocurrencies to enhance the performance and scalability of off-chain transactions. Except for opening and closing of a payment channel, no other transaction requests accepted by a PCN are recorded in the Blockchain. Only the parties which have opened the channel will know the exact amount of fund left at a given instant. In real scenarios, there might not exist a single path which can enable transfer of high value payments. For such cases, splitting up the transaction value across multiple paths is a better approach. While there exists several approaches which route transactions via several paths, such techniques are quite inefficient, as the decision on the number of splits must be taken at the initial phase of the routing algorithm (e.g., SpeedyMurmur [42]). Algorithms which do not consider the residual capacity of each channel in the network are susceptible to failure. Other approaches leak sensitive information, and are quite computationally expensive [28]. To the best of our knowledge, our proposed scheme HushRelay is an efficient privacy preserving routing algorithm, taking into account the funds left in each channel, while splitting the transaction value across several paths. Comparing the performance of our algorithm with existing routing schemes on real instances (e.g., Ripple Network), we observed that HushRelay attains a success ratio of 1, with an execution time of 2.4 sec. However, SpeedyMurmur [42] attains a success ratio of 0.98 and takes 4.74 sec when the number of landmarks is 6. On testing our proposed routing algorithm on the Lightning Network, a success ratio of 0.99 is observed, having an execution time of 0.15 sec, which is 12 times smaller than the time taken by SpeedyMurmur.