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Sushmita Ruj

Publications and source records attributed to Sushmita Ruj.

At least 37 records · Page 2Linked to original sources

A Technical Look At The Indian Personal Data Protection Bill

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.

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A Secure Fog Based Architecture for Industrial Internet of Things and Industry 4.0

The advent of Industrial IoT (IIoT) along with Cloud computing has brought a huge paradigm shift in manufacturing industries resulting in yet another industrial revolution, Industry 4.0. Huge amounts of delay-sensitive data of diverse nature are being generated which needs to be locally processed and secured due to its sensitivity. But, the low-end IoT devices are unable to handle huge computational overheads. Also, the semi-trusted nature of Cloud introduces several security concerns. To address these issues, this work proposes a secure Fog-based IIoT architecture by suitably plugging a number of security features into it and by offloading some of the tasks judiciously to fog nodes. These features secure the system alongside reducing the trust and burden on the cloud and resource-constrained devices respectively. We validate our proposed architecture through both theoretical overhead analysis and practical experimentation including simulation study and testbed implementation.

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HushRelay: A Privacy-Preserving, Efficient, and Scalable Routing Algorithm for Off-Chain Payments

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.

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Verifiable and Auditable Digital Interchange Framework

We address the problem of fairness and transparency in online marketplaces selling digital content, where all parties are not actively participating in the trade. We present the design, implementation and evaluation of VADER, a highly scalable solution for multi-party fair digital exchange that combines the trusted execution of blockchains with intelligent protocol design and incentivization schemes. We prototype VADER on Hyperledger Fabric and extensively evaluate our system on a realistic testbed spanning five public cloud datacenters, spread across four continents. Our results demonstrate that VADER adds only minimal overhead of 16% in median case compared to a baseline solution, while significantly outperforming a naive blockchain based solution that adds an overhead of 764%.

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FSPVDsse: A Forward Secure Publicly Verifiable Dynamic SSE scheme

A symmetric searchable encryption (SSE) scheme allows a client (data owner) to search on encrypted data outsourced to an untrusted cloud server. The search may either be a single keyword search or a complex query search like conjunctive or Boolean keyword search. Information leakage is quite high for dynamic SSE, where data might be updated. It has been proven that to avoid this information leakage an SSE scheme with dynamic data must be forward private. A dynamic SSE scheme is said to be forward private, if adding a keyword-document pair does not reveal any information about the previous search result with that keyword. In SSE setting, the data owner has very low computation and storage power. In this setting, though some schemes achieve forward privacy with honest-but-curious cloud, it becomes difficult to achieve forward privacy when the server is malicious, meaning that it can alter the data. Verifiable dynamic SSE requires the server to give a proof of the result of the search query. The data owner can verify this proof efficiently. In this paper, we have proposed a generic publicly verifiable dynamic SSE (DSSE) scheme that makes any forward private DSSE scheme verifiable without losing forward privacy. The proposed scheme does not require any extra storage at owner-side and requires minimal computational cost as well for the owner. Moreover, we have compared our scheme with the existing results and show that our scheme is practical.

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Blockchain Enabled Data Marketplace -- Design and Challenges

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.

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Design of Anonymous Endorsement System in Hyperledger Fabric

Permissioned Blockchain has become quite popular with enterprises forming consortium since it prioritizes trust over privacy. One of the popular platforms for distributed ledger solution, Hyperledger Fabric, requires a transaction to be endorsed or approved by a group of special members known as endorsers before undergoing validation. To endorse a transaction, an endorser mentions its identity along with the signature so that it can be verified later. However, for certain transactions, difference in opinion may exist among endorsers. Disclosing the identity of an endorser may lead to conflict within the consortium. In such cases, an endorsement policy which not only allows an endorser to support a transaction discreetly, but at the same time takes into account the decision of the majority is preferred. Thus we propose an Anonymous Endorsement System which uses a threshold endorsement policy in order to address the issue. All these factors motivated us to design a new ring signature scheme, called Fabric' Constant-Sized Linkable Ring Signature (FCsLRS) with Transaction-Oriented linkability for hiding identity of the endorsers. We have implemented the signature scheme in Golang and analyzed its security and performance by varying the RSA (Rivest-Shamir-Adleman) modulus size. Feasibility of implementation is supported by experimental analysis. Signature and tag generation time is quite fast and remains constant irrespective of change in message length or endorsement set size for a given RSA modulus value, assuming all the endorsers generates their signature in parallel. Lastly, we also discuss the integration of the scheme on v1.2 Hyperledger Fabric.

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The Secure Link Prediction Problem

Link Prediction is an important and well-studied problem for social networks. Given a snapshot of a graph, the link prediction problem predicts which new interactions between members are most likely to occur in the near future. As networks grow in size, data owners are forced to store the data in remote cloud servers which reveals sensitive information about the network. The graphs are therefore stored in encrypted form. We study the link prediction problem on encrypted graphs. To the best of our knowledge, this secure link prediction problem has not been studied before. We use the number of common neighbors for prediction. We present three algorithms for the secure link prediction problem. We design prototypes of the schemes and formally prove their security. We execute our algorithms in real-life datasets.

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Keyword-Based Delegable Proofs of Storage

Cloud users (clients) with limited storage capacity at their end can outsource bulk data to the cloud storage server. A client can later access her data by downloading the required data files. However, a large fraction of the data files the client outsources to the server is often archival in nature that the client uses for backup purposes and accesses less frequently. An untrusted server can thus delete some of these archival data files in order to save some space (and allocate the same to other clients) without being detected by the client (data owner). Proofs of storage enable the client to audit her data files uploaded to the server in order to ensure the integrity of those files. In this work, we introduce one type of (selective) proofs of storage that we call keyword-based delegable proofs of storage, where the client wants to audit all her data files containing a specific keyword (e.g., "important"). Moreover, it satisfies the notion of public verifiability where the client can delegate the auditing task to a third-party auditor who audits the set of files corresponding to the keyword on behalf of the client. We formally define the security of a keyword-based delegable proof-of-storage protocol. We construct such a protocol based on an existing proof-of-storage scheme and analyze the security of our protocol. We argue that the techniques we use can be applied atop any existing publicly verifiable proof-of-storage scheme for static data. Finally, we discuss the efficiency of our construction.

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Efficient Proofs of Retrievability with Public Verifiability for Dynamic Cloud Storage

Cloud service providers offer various facilities to their clients. The clients with limited resources opt for some of these facilities. They can outsource their bulk data to the cloud server. The cloud server maintains these data in lieu of monetary benefits. However, a malicious cloud server might delete some of these data to save some space and offer this extra amount of storage to another client. Therefore, the client might not retrieve her file (or some portions of it) as often as needed. Proofs of retrievability (POR) provide an assurance to the client that the server is actually storing all of her data appropriately and they can be retrieved at any point of time. In a dynamic POR scheme, the client can update her data after she uploads them to the cloud server. Moreover, in publicly verifiable POR schemes, the client can delegate her auditing task to some third party specialized for this purpose. In this work, we exploit the homomorphic hashing technique to design a publicly verifiable dynamic POR scheme that is more efficient (in terms of bandwidth required between the client and the server) than the "state-of-the-art" publicly verifiable dynamic POR scheme. We also analyze security and performance of our scheme.

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On the Economic Significance of Ransomware Campaigns: A Bitcoin Transactions Perspective

Bitcoin cryptocurrency system enables users to transact securely and pseudo-anonymously by using an arbitrary number of aliases (Bitcoin addresses). Cybercriminals exploit these characteristics to commit immutable and presumably untraceable monetary fraud, especially via ransomware; a type of malware that encrypts files of the infected system and demands ransom for decryption. In this paper, we present our comprehensive study on all recent ransomware and report the economic impact of such ransomware from the Bitcoin payment perspective. We also present a lightweight framework to identify, collect, and analyze Bitcoin addresses managed by the same user or group of users (cybercriminals, in this case), which includes a novel approach for classifying a payment as ransom. To verify the correctness of our framework, we compared our findings on CryptoLocker ransomware with the results presented in the literature. Our results align with the results found in the previous works except for the final valuation in USD. The reason for this discrepancy is that we used the average Bitcoin price on the day of each ransom payment whereas the authors of the previous studies used the Bitcoin price on the day of their evaluation. Furthermore, for each investigated ransomware, we provide a holistic view of its genesis, development, the process of infection and execution, and characteristic of ransom demands. Finally, we also release our dataset that contains a detailed transaction history of all the Bitcoin addresses we identified for each ransomware.

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An Efficient Secure Distributed Cloud Storage for Append-only Data

Cloud computing enables users (clients) to outsource large volume of their data to cloud servers. Secure distributed cloud storage schemes ensure that multiple servers store these data in a reliable and untampered fashion. We propose an idea to construct such a scheme for static data by encoding data blocks (using error-correcting codes) and then attaching authentication information (tags) to these encoded blocks. We identify some challenges while extending this idea to accommodate append-only data. Then, we propose our secure distributed cloud storage scheme for append-only data that addresses the challenges efficiently. The main advantage of our scheme is that it enables the servers to update the parity blocks themselves. Moreover, the client need not download any data (or parity) block to update the tags of the modified parity blocks residing on the servers. Finally, we analyze the security and performance of our scheme.

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A Survey on Security and Privacy Issues of Bitcoin

Bitcoin is a popular cryptocurrency that records alltransactions in a distributed append-only public ledger calledblockchain. The security of Bitcoin heavily relies on the incentive-compatible proof-of-work (PoW) based distributed consensus pro-tocol, which is run by network nodes called miners. In exchangefor the incentive, the miners are expected to honestly maintainthe blockchain. Since its launch in 2009, Bitcoin economy hasgrown at an enormous rate, and it is now worth about 170 billions of dollars. This exponential growth in the market valueof Bitcoin motivates adversaries to exploit weaknesses for profit,and researchers to discover new vulnerabilities in the system,propose countermeasures, and predict upcoming trends.In this paper, we present a systematic survey that covers thesecurity and privacy aspects of Bitcoin. We start by presenting anoverview of the Bitcoin protocol and its major components alongwith their functionality and interactions within the system. Wereview the existing vulnerabilities in Bitcoin and its underlyingmajor technologies such as blockchain and PoW based consensusprotocol. These vulnerabilities lead to the execution of varioussecurity threats to the normal functionality of Bitcoin. Wethen discuss the feasibility and robustness of the state-of-the-art security solutions. Additionally, we present current privacyand anonymity considerations in Bitcoin and discuss the privacy-related threats to Bitcoin users along with the analysis of theexisting privacy-preserving solutions. Finally, we summarize thecritical open challenges and suggest directions for future researchtowards provisioning stringent security and privacy techniquesfor Bitcoin.

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Cloud Data Auditing Using Proofs of Retrievability

Cloud servers offer data outsourcing facility to their clients. A client outsources her data without having any copy at her end. Therefore, she needs a guarantee that her data are not modified by the server which may be malicious. Data auditing is performed on the outsourced data to resolve this issue. Moreover, the client may want all her data to be stored untampered. In this chapter, we describe proofs of retrievability (POR) that convince the client about the integrity of all her data.

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A Graph Analytics Framework for Ranking Authors, Papers and Venues

A lot of scientific works are published in different areas of science, technology, engineering and mathematics. It is not easy, even for experts, to judge the quality of authors, papers and venues (conferences and journals). An objective measure to assign scores to these entities and to rank them is very useful. Although, several metrics and indexes have been proposed earlier, they suffer from various problems. In this paper, we propose a graph-based analytics framework to assign scores and to rank authors, papers and venues. Our algorithm considers only the link structures of the underlying graphs. It does not take into account other aspects, such as the associated texts and the reputation of these entities. In the limit of large number of iterations, the solution of the iterative equations gives the unique entity scores. This framework can be easily extended to other interdependent networks.

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Certificate Transparency with Enhancements and Short Proofs

Browsers can detect malicious websites that are provisioned with forged or fake TLS/SSL certificates. However, they are not so good at detecting malicious websites if they are provisioned with mistakenly issued certificates or certificates that have been issued by a compromised certificate authority. Google proposed certificate transparency which is an open framework to monitor and audit certificates in real time. Thereafter, a few other certificate transparency schemes have been proposed which can even handle revocation. All currently known constructions use Merkle hash trees and have proof size logarithmic in the number of certificates/domain owners. We present a new certificate transparency scheme with short (constant size) proofs. Our construction makes use of dynamic bilinear-map accumulators. The scheme has many desirable properties like efficient revocation, low verification cost and update costs comparable to the existing schemes. We provide proofs of security and evaluate the performance of our scheme.

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Preferential Attachment Model with Degree Bound and its Application to Key Predistribution in WSN

Preferential attachment models have been widely studied in complex networks, because they can explain the formation of many networks like social networks, citation networks, power grids, and biological networks, to name a few. Motivated by the application of key predistribution in wireless sensor networks (WSN), we initiate the study of preferential attachment with degree bound. Our paper has two important contributions to two different areas. The first is a contribution in the study of complex networks. We propose preferential attachment model with degree bound for the first time. In the normal preferential attachment model, the degree distribution follows a power law, with many nodes of low degree and a few nodes of high degree. In our scheme, the nodes can have a maximum degree $d_{\max}$, where $d_{\max}$ is an integer chosen according to the application. The second is in the security of wireless sensor networks. We propose a new key predistribution scheme based on the above model. The important features of this model are that the network is fully connected, it has fewer keys, has larger size of the giant component and lower average path length compared with traditional key predistribution schemes and comparable resilience to random node attacks. We argue that in many networks like key predistribution and Internet of Things, having nodes of very high degree will be a bottle-neck in communication. Thus, studying preferential attachment model with degree bound will open up new directions in the study of complex networks, and will have many applications in real world scenarios.

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CITEX: A new citation index to measure the relative importance of authors and papers in scientific publications

Evaluating the performance of researchers and measuring the impact of papers written by scientists is the main objective of citation analysis. Various indices and metrics have been proposed for this. In this paper, we propose a new citation index CITEX, which gives normalized scores to authors and papers to determine their rankings. To the best of our knowledge, this is the first citation index which simultaneously assigns scores to both authors and papers. Using these scores, we can get an objective measure of the reputation of an author and the impact of a paper. We model this problem as an iterative computation on a publication graph, whose vertices are authors and papers, and whose edges indicate which author has written which paper. We prove that this iterative computation converges in the limit, by using a powerful theorem from linear algebra. We run this algorithm on several examples, and find that the author and paper scores match closely with what is suggested by our intuition. The algorithm is theoretically sound and runs very fast in practice. We compare this index with several existing metrics and find that CITEX gives far more accurate scores compared to the traditional metrics.

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