Abstract A zero-knowledge proof or protocol is a cryptographic technique for verifying private data without revealing it in its clear form. In this paper, we evaluate the potential for zero-knowledge distributed ledger technology to alleviate asymmetry of information in the asset-backed securitization market. To frame this inquiry, we conducted market data analyses, a review of prior literature, stakeholder interviews with investors, originators and security issuers and collaboration with blockchain engineers and researchers. We introduce a new system which could enable all market participants in the securitization lifecycle (e.g. investors, rating agencies, regulators and security issuers) to interact on a unique decentralized platform while maintaining the privacy of loan-level data, therefore providing the industry with timely analytics and performance data. Our platform is powered by zkLedger (Narula et al. 2018), a zero-knowledge protocol developed by the MIT Media Lab and the first system that enables participants of a distributed ledger to run publicly verifiable analytics on masked data.
Yasar Khan, Toqeer Ali Syed, Megat Fariz, Fernando Moreira · 7 authors
Abstract An electronic business transaction among untrusted bodies without consulting a mutually trusted party has remained widely accepted problem. Blockchain resolves this problem by introducing peer‐to‐peer network with a consensus algorithm and trusted ledger. Blockchain originally introduced for cryptocurrency that came with proof‐of‐work consensus algorithm. Due to some performance issues, scientists brought concept of permissioned Blockchain. Hyperledger Fabric is a permissioned Blockchain targeting business‐oriented problems for industry. It is designed for efficient transaction execution over Blockchain with pluggable consensus model; however, there is limitation of rapid application development. Hyperledger introduced a new layer called Hyperledger Composer on top of the Fabric layer, which provides an abstract layer to model the business application readily and quickly. Composer provides a smart contract to extend the functionality and flexibility of Fabric layer and provides a way of communication with other systems to meet business requirements. Hyperledger Composer uses role‐based access control (RBAC) model to secure access to its valuable assets. However, RBAC is not enough because many business deals require continuous assets monitoring. Our proposed model, BlockU, covers all possible access control models required by a business. BlockU can monitor assets continuously during transactions and updates attributes accordingly. Moreover, we incorporate hooks in Hyperledger Composer to implement extended permission model that provides extensive permission management capability on an asset. Subsequently, our proposed enhanced access control model is implemented with a minimal change to existing Composer code base and is backward compatible with the current security mechanism.
Md Sadek Ferdous, Mohammad Jabed Morshed Chowdhury, Mohammad A. Hoque, Alan Colman
In recent years, blockchain technology has received unparalleled attention from academia, industry, and governments all around the world. It is considered a technological breakthrough anticipated to disrupt several application domains. This has resulted in a plethora of blockchain systems for various purposes. However, many of these blockchain systems suffer from serious shortcomings related to their performance and security, which need to be addressed before any wide-scale adoption can be achieved. A crucial component of any blockchain system is its underlying consensus algorithm, which in many ways, determines its performance and security. Therefore, to address the limitations of different blockchain systems, several existing as well novel consensus algorithms have been introduced. A systematic analysis of these algorithms will help to understand how and why any particular blockchain performs the way it functions. However, the existing studies of consensus algorithms are not comprehensive. Those studies have incomplete discussions on the properties of the algorithms and fail to analyse several major blockchain consensus algorithms in terms of their scopes. This article fills this gap by analysing a wide range of consensus algorithms using a comprehensive taxonomy of properties and by examining the implications of different issues still prevalent in consensus algorithms in detail. The result of the analysis is presented in tabular formats, which provides a visual illustration of these algorithms in a meaningful way. We have also analysed more than hundred top crypto-currencies belonging to different categories of consensus algorithms to understand their properties and to implicate different trends in these crypto-currencies. Finally, we have presented a decision tree of algorithms to be used as a tool to test the suitability of consensus algorithms under different criteria.
Traditional Blockchain Sharding approaches can only tolerate up to n/3 of nodes being adversary because they rely on the hyper-geometric distribution to make a failure (an adversary does not have n/3 of nodes globally but can manipulate the consensus of a Shard) hard to happen. The system must maintain a large Shard size (the number of nodes inside a Shard) to sustain the low failure probability so that only a small number of Shards may exist. In this paper, we present a new approach of Blockchain Sharding that can withstand up to n/2 of nodes being bad. We categorise the nodes into different classes, and every Shard has a fixed number of nodes from different classes. We prove that this design is much more secure than the traditional models (only have one class) and the Shard size can be reduced significantly. In this way, many more Shards can exist, and the transaction throughput can be largely increased. The improved Blockchain Sharding approach is promising to serve as the foundation for decentralised autonomous organisations and decentralised database.
We improve the fundamental security threshold of eventual consensus Proof-of-Stake (PoS) blockchain protocols under the longest-chain rule by showing, for the first time, the positive effect of rounds with concurrent honest leaders. Current security analyses reduce consistency to the dynamics of an abstract, round-based block creation process that is determined by three events associated with a round: (i) event $A$: at least one adversarial leader, (ii) event $S$: a single honest leader, and (iii) event $M$: multiple, but honest, leaders. We present an asymptotically optimal consistency analysis assuming that an honest round is more likely than an adversarial round (i.e., $\Pr[S] + \Pr[M] > \Pr[A]$); this threshold is optimal. This is a first in the literature and can be applied to both the simple synchronous communication as well as communication with bounded delays. In all existing consistency analyses, event $M$ is either penalized or treated neutrally. Specifically, the consistency analyses in Ouroboros Praos (Eurocrypt 2018) and Genesis (CCS 2018) assume that $\Pr[S] - \Pr[M] > \Pr[A]$; the analyses in Sleepy Consensus (Asiacrypt 2017) and Snow White (Fin. Crypto 2019) assume that $\Pr[S] > \Pr[A]$. Moreover, all existing analyses completely break down when $\Pr[S] < \Pr[A]$. These thresholds determine the critical trade-off between the honest majority, network delays, and consistency error. Our new results can be directly applied to improve the security guarantees of the existing protocols. We also provide an efficient algorithm to explicitly calculate these error probabilities in the synchronous setting. Furthermore, we complement these results by analyzing the setting where $S$ is rare, even allowing $\Pr[S] = 0$, under the added assumption that honest players adopt a consistent chain selection rule.
Víctor Gayoso Martínez, Luis Hernández–Álvarez, Luis Hernández Encinas
Blockchain is one of the most interesting emerging technologies nowadays, with applications ranging from cryptocurrencies to smart contracts. This paper presents a review of the cryptographic tools necessary to understand the fundamentals of this technology and the foundations of its security. Among other elements, hash functions, digital signatures, elliptic curves, and Merkle trees are reviewed in the scope of their usage as building blocks of this technology.
Edgar González Fernández, Guillermo Morales-Luna, Feliú Sagols
Current requirements for ensuring data exchange over the internet to fight against security breaches have to consider new cryptographic attacks. The most recent advances in cryptanalysis are boosted by quantum computers, which are able to break common cryptographic primitives. This makes evident the need for developing further communication protocols to secure sensitive data. Zero-knowledge proof systems have been around for a while and have been considered for providing authentication and identification services, but it has only been in recent times that its popularity has risen due to novel applications in blockchain technology, Internet of Things, and cloud storage, among others. A new zero-knowledge proof system is presented, which bases its security in two main problems, known to be resistant, up to now, against quantum attacks: the graph isomorphism problem and the isomorphism of polynomials problem.
Muhammad Ajmal Azad, Samiran Bag, Feng Hao, Andrii Shalaginov
The Internet of Things (IoT) is the network of connected computing devices that have the ability to transfer valued data between each other via the Internet without requiring human intervention. In such a connected environment, the social IoT (SIoT) has become an emerging trend where multiple IoT devices owned by users support communication within a social circle. Trust management in the SIoT network is imperative as trusting the information from compromised devices could lead to serious compromises within the network. It is important to have a mechanism where the devices and their users evaluate the trustworthiness of other devices and users before trusting the information sent by them. The privacy preservation, decentralization, and self-enforcing management without involving trusted third parties are the fundamental challenges in designing a trust management system for SIoT. To fulfill these challenges, this article presents a novel framework for computing and updating the trustworthiness of participants in the SIoT network in a self-enforcing manner without relying on any trusted third party. The privacy of the participants in the SIoT is protected by using homomorphic encryption in the decentralized setting. To achieve the properties of self-enforcement, the trust score of each device is automatically updated based on its previous trust score and the up-to-date tally of the votes by its peers in the network with zero-knowledge proofs (ZKPs) to enforce that every participant follows the protocol honestly. We evaluate the performance of the proposed scheme and present evaluation benchmarks by prototyping the main functionality of the system. The performance results show that the system has a linear increase in computation and communication overheads with more participants in the network. Furthermore, we prove the correctness, privacy, and security of the proposed system under a malicious adversarial model.
Sri Aravinda Krishnan Thyagarajan, Adithya Bhat, Bernardo Magri, Daniel Tschudi · 5 authors
Although blockchains aim for immutability as their core feature, several instances have exposed the harms with perfect immutability. The permanence of illicit content inserted in Bitcoin poses a challenge to law enforcement agencies like Interpol, and millions of dollars are lost in buggy smart contracts in Ethereum. A line of research then spawned on Redactable blockchains with the aim of solving the problem of redacting illicit contents from both permissioned and permissionless blockchains. However, all the existing proposals follow the build-new-chain approach for redactions, and cannot be integrated with existing systems like Bitcoin and Ethereum. We present Reparo, a generic protocol that acts as a publicly verifiable layer on top of any blockchain to perform repairs, ranging from fixing buggy contracts to removing illicit contents from the chain. Reparo facilitates additional functionalities for blockchains while maintaining the same provable security guarantee; thus, Reparo can be integrated with existing blockchains and start performing repairs on the pre-existent data. Any system user may propose a repair and a deliberation process ensues resulting in a decision that complies with the repair policy of the chain and is publicly verifiable. Our Reparo layer can be easily tailored to different consensus requirements, does not require heavy cryptographic machinery and can, therefore, be efficiently instantiated in any permission-ed or -less setting. We demonstrate it by giving efficient instantiations of Reparo on top of Ethereum (with PoS and PoW), Bitcoin, and Cardano. Moreover, we evaluate Reparo with Ethereum mainnet and show that the cost of fixing several prominent smart contract bugs is almost negligible. For instance, the cost of repairing the prominent Parity Multisig wallet bug with Reparo is as low as 0.000000018% of the Ethers that can be retrieved after the fix.
Christian Sri Kusuma Aditya, M. Akash, pothuru eswar akash, M. Amitkumar · 8 authors
The complexity of providing secure access, protecting critical data and end-user privacy in cloud data centre is leading to a demand for a new approach in network and data security. Recently, blockchain technology is being used in claims management to provide a decentralized and secure solution. The issue of security is crucial in the Virtual machine authorization in the cloud data centers. In the traditional approach of VM authorization, SSH key and IP address is given to the user to log into virtual machines. This opens much vulnerability as it might get spoofed or sniffed from the network, leading to accesses of private data to intruder. In this work, we propose a method which intends to aid in the security of the VM authorization using claims-based authorization system in conjunction with Blockchain based decentralized storage. Furthermore, the proposed system automates the process of launching a VM in OpenStack orchestration software.
Permission delegation in access control provides the subject with a second method to obtain object permissions in addition to permission granting. It is especially applicable when the owner and manager of the object are inconsistent. With the development of the Internet of Things, there are more and more scenes where object owners and managers are inconsistent, but the research on permission delegation in access control based on blockchain is not perfect. Therefore, once implemented in these blockchain-based access control algorithms, the permission delegation tends to have an unauthorized access. Based on the analysis of the causes for the unauthorized access vulnerability, this paper proposes a token-constrained permission delegation algorithm (TCPDA), which converts the access control policy corresponding to permissions into constraints for permission use, embeds the constraints in the permission token, and forms constraints on the transfer of tokens. Only subjects that meet the constraint conditions can receive tokens, thereby solving unauthorized access vulnerability caused by permission delegation. Since not all access control models can transform strategies into constraints and integrate them into blockchain tokens, this paper also proposes a permission delegation algorithm for decision-making entities to make desirable decisions. Finally, the security analysis shows that the two proposed schemes can overcome the unauthorized access vulnerability caused by permission delegation, and the algorithm performance is analyzed through experiments.
The security of operation and maintenance phase in systems that share long-life cycles like weapon systems is of great importance. Even if the system passes the security evaluation at the development stage before release, it can be adversely affected by the penetration of counterfeit components (parts) during the operation and maintenance phase. Such security issues are concatenated with data related to supply chain, accordingly, system parts need to fulfill the traceability on a fundamental basis. In addition to traceability, supply chains should also meet the data security standards of availability, integrity and confidentiality in the long run. Also, even without trusted third party, these data should be available to users. In this paper, we, therefore, propose a framework that utilizes blockchain and key escrow encryption system in a bid to optimize the security of supply chains for long-lifecycle systems and provide better measures to improve services for global business survivability.
In today’s fourth industrial revolution, various blockchain technologies are being actively researched. A blockchain is a peer-to-peer data-sharing structure lacking central control. If a user wishes to access stored data, she/he must employ a private key to prove ownership of the data and create a transaction. If the private key is lost, blockchain data cannot be accessed. To solve such a problem, public blockchain users can recover the key using a wallet program. However, key recovery in a permissioned blockchain (PBC) has been but little studied. The PBC server is Honest-but-Curious (HBC), and should not be able to learn anything of the user; the server should simply recover and store the key. The server must also be resistant to malicious attacks. Therefore, key recovery in a PBC must satisfy various security requirements. Here, we present a password-protected secret sharing (PPSS) key recovery system, protected by a secure password from a malicious key storage server of a PBC. We describe existing key recovery schemes and our PPSS scheme.
Peng Zhao, Hongbing Cheng, Yicheng Fang, Xiaoqing Wang
The exponential growth of storage space in blockchain network has become a serious problem to hinder the distribution of blockchain and the expansion of blockchain nodes. In this paper. We propose a security strategy for distributed storage blockchains, which can delete part of blockchains so that nodes only store part of a blockchain. We design a kind of semi-full node between full node and light node according to the requirement of the strategy, besides describe the process of deleting block and synchronizing block, and the running logic of the semi-full node. Finally, we perform comprehensive experiments of the truncated MCMC random algorithm. The results show that in the case of multi-node, the truncated block will not affect the block chain network. Compared with the traditional block design, our storage strategies can reduce storage requirements under most of situation, thus enable blockchains to be deployed on mobile or smaller storage computers.
Increasing list of records is with blockchain where each record is linked with the help of cryptography. Every block in the chain contains timestamp, transaction details and hash of a previous block, hash is cryptographic hash. This is a secured system, which we plan to replace the current online payment system. A current online payment gateway is prone to hackers where the attacker can tamper into the network, thus creating money loss. And not only this but also the transaction has to go through multiple payment systems which consumes time, also creating a risk of transaction getting failed. So, our system would be using blockchain that allows online transactions which would allow online payments to be sent directly from one party to another without going through a financial institution and in a secured way. This system allows online transactions between two parties based on cryptographic proof without relying and trusting for a third party. To record transactions, we use proof of work algorithm which makes computationally impractical for an attacker to change. Digital signatures provide part of the solution for ensuring the security and integrity of the data that is recorded onto a blockchain.
In the digital era, electronic medical record (EMR) has been a major way for hospitals to store patients’ medical data. The traditional centralized medical system and semi-trusted cloud storage are difficult to achieve dynamic balance between privacy protection and data sharing. The storage capacity of blockchain is limited and single blockchain schemes have poor scalability and low throughput. To address these issues, we propose a secure and efficient medical data storage and sharing scheme based on double blockchain. In our scheme, we encrypt the original EMR and store it in the cloud. The storage blockchain stores the index of the complete EMR, and the shared blockchain stores the index of the shared part of the EMR. Users with different attributes can make requests to different blockchains to share different parts according to their own permissions. Through experiments, it was found that cloud storage combined with blockchain not only solved the problem of limited storage capacity of blockchain, but also greatly reduced the risk of leakage of the original EMR. Content Extraction Signature (CES) combined with the double blockchain technology realized the separation of the privacy part and the shared part of the original EMR. The symmetric encryption technology combined with Ciphertext-Policy Attribute-Based Encryption (CP–ABE) not only ensures the safe storage of data in the cloud, but also achieves the consistency and convenience of data update, avoiding redundant backup of data. Safety analysis and performance analysis verified the feasibility and effectiveness of our scheme.
Blockchain, a type of a decentralized network system that allows mutually distrustful parties to transact securely without involving third parties, has recently been attracting increasing attention. Hence, there must be a consensus mechanism to ensure a distributed consensus among all participants. Such a consensus mechanism may also be used to guarantee fairness, correctness and security of such decentralized systems. Thus, in this paper we propose a novel consensus mechanism named GSCS that is an improved version of PoW. Compared with existing consensus mechanisms (such as PoW, PoS and so on), GSCS provides strong resistance to resource centralization, the quantum attack and other malicious attacks. In this work, we first present the serial mining puzzle to resist collusive mining and the quantum attack. It guarantees that participants can only obtain a negligible advantage by solving the relevant problem in parallel. Second, GSCS considers the influence of participant credibility. The credibility is reflected by the mining behavior of each participant and directly influence to the mining difficulty of participant. Thus, credible participants enjoy a higher probability of winning the mining competition than do participants who are not credible. Finally, performance of GSCS is analyzed in terms of the common prefix, chain quality, chain growth, and power cost. The results indicate that GSCS is security- and incentive-compatible with suitable security parameter settings. In brief, GSCS has the potential to ensure a more secure and robust environment for decentralized blockchain systems.
Macià Mut–Puigserver, Miquel À. Cabot-Nadal, M. Magdalena Payeras–Capellà
Recently several proposals of blockchain-based solutions for traditional e-commerce applications have been presented, taking advantage of the fact that blockchain is a technology that offers an immutable registry of data. Among these proposals we can find solutions for certified notifications, digital signature of contracts, escrow protocols, fair payments and registered deliveries. In order to execute fair exchanges, most solutions involve trusted third parties, known as TTP, supervising the exchanges in a way or another. Until now, two solutions have been presented for Registered electronic Delivery (eDelivery) services. This service allows a user to prove that he has sent some data to a set of receivers. These protocols differ in the properties achieved and also in the use of trusted third parties. The first protocol is a blockchain-based solution without TTP for the eDelivery of non-confidential data. The second protocol allows also the eDelivery of confidential data. However, this second proposal requires the involvement of a TTP in a non-mandatory resolution phase. In this paper we present a new protocol that achieves the best properties of the previous solutions at the same time. The new protocol doesn't require the involvement of a TTP at any moment while it allows the eDelivery of confidential data, satisfying the security requirements for this service.
Modern machine learning techniques have achieved surprisingly good standard test accuracy, yet classical machine learning theory has been unable to explain the underlying reason behind this success. The phenomenon of adversarial examples further complicates our understanding of what it means to have good generalization ability. Classifiers that generalize well to the test set are easily fooled by imperceptible image modifications, which can often be computed without knowledge of the classifier itself. The adversarial error of a classifier measures the error under which each test data point can be modified by an algorithm before it is given as input to the classifier. Followup work has showed that a tradeoff exists between optimizing for standard generalization error versus for adversarial error. This calls into question whether standard generalization error is the correct metric to measure. We try to understand the generalization capability of modern machine learning techniques through the lens of adversarial examples. To reconcile the apparent tradeoff between the two competing notions of error, we create new security definitions and classifier constructions which allow us to prove an upper bound on the adversarial error that decreases as standard test error decreases. We introduce a cryptographic proof technique by defining a security assumption in a simpler attack setting and proving a security reduction from a restricted black-box attack problem to this security assumption. We then investigate the double descent curve in the interpolation regime, where test error can continue to decrease even after training error has reached zero, to give a natural explanation for the observed tradeoff between adversarial error and standard generalization error. The second part of our work investigates further this notion of a black-box model by looking at the separation between being able to evaluate a function and being able to actually understand it. This is formalized through the notion of function obfuscation in cryptography. Given some concrete implementation of a function, the implementation is considered obfuscated if a user cannot produce the function output on a test input without querying the implementation itself. This means that a user cannot actually learn or understand the function even though all of the implementation details are presented in the clear. As expected this is a very strong requirement that does not exist for all functions one might be interested in. In our work we make progress on providing obfuscation schemes for simple, explicit function classes. The last part of our work investigates non-statistical biases and algorithms for nonconvex optimization problems. We show that the continuous-time limit of stochastic gradient descent does not converge directly to the local optimum, but rather has a bias term which grows with the step size. We also construct novel, non-statistical algorithms for two parametric learning problems by employing lattice basis reduction techniques from cryptography.
Blockchain is making headlines due to it promises to provide a decentralized, transparent, tamper-resistant, traceable and verifiable historical transaction records that can resist faults of any single node. According to the latest data from State of the Dapps, developers have currently released 3,717 Decentralized Applications (DApps), only three have an average of more than 10,000 daily active users. Most of the real-world DApps exercise little of their potential power. The key reason is that the current permissioned blockchain systems suffer from poor performance and lack of confidentiality. To address this issue, we present Hybridchain, a system that combines blockchain with Trusted Execution Environment (TEE). Hybridchain decouples computation from consensus and adopts hierarchical network to minimize the computational burden and latency of on-chain execution by performing most of the heavy-weight computation off-chain. Hybridchain leverages secure communication protocols to enable each participant to share transaction data in a secure way. To mitigate the small enclave memory restriction of TEE, Hybridchain extends the enclave memory that allows blockchain applications running in TEE to securely store transaction records to the whole key-value storage codes placed outside of TEE. Analysis and experiments of sealed-bid auction show that Hybridchain can support confidentiality-preserving along with high performance.
With the public key being the parameter users are mostly addressed by on blockchain network, an intruder can connect transactional patterns to the public key and make a probable revelation of the identity of the user. Due to the diversity in approaches in achieving privacy, integrating the principle of transparency in any blockchain - edge computing platform will present some structural security challenges. Thus, an attempt should be made to achieve confidentiality whilst not eliminating a key principle of blockchain - transparency. Based on elliptic curve cryptosystem (ECC), we present a privacy-aware scheme that preserves the privacy details of the user in a blockchain-edge computing environment based on a combination of randomly generated public keys and digital signatures. The resilience and practicality of our scheme were tested on AVISPA and NS2 respectively. The results indicated our scheme was robust against attacks, efficient and low on computation resources of edge devices.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques