Tor is now using a centralized measurement system called Sbws to measure the bandwidth of relays to guide clients in selecting relays to balance traffic. Sbws has been proven to be vulnerable to multiple attacks because of the centralized structure and exposed measurements. We present SmartMeasurer, a secure and decentralized system for bandwidth measurement. Combining smart contract, Oracle Chainlink and ECC technology, we achieve decentralization while hiding the measurement circuits among the general circuits by exploiting the dual identity of randomly dynamic measurers and guards. We analyze the security of our system and demonstrate that it defends against three types of attacks. Our experiments on both private and public Tor networks show that our system is decentralized while keeping the error and the average of our measurements converges to a small interval of 0.30 Mbps. Compared to other existing methods, our system reduces trust assumptions and the costs of using smart contract, and enhances the practical feasibility of the solution.
Open access
Internet Traffic Analysis and Secure E-voting
Cryptography and Data Security
Physical Unclonable Functions (PUFs) and Hardware Security
Deebakkarthi Chinnasame Rani, Sai Ganesh Janakiraman, K. S. Chandra, Elambharathi Padmavathi Thangavel · 7 authors
Presented herein is a novel algorithm for multi-round, zero-knowledge proof (ZKP), devised specifically for authenticating factorisation proofs within a variety of cryptographic applications. This advanced algorithm, while maintaining computational complexity within acceptable bounds, offers a secure and proficient solution. The functionality of the algorithm is marked by multiple rounds of interaction between the Prover and Verifier. Initially, the Prover generates a random value and calculates a commitment. Subsequently, the Verifier issues a random challenge, eliciting a computed response from the Prover. To validate the proof, the Verifier verifies the equality of the commitment and the computed response. Efficaciousness of the proposed multi-round ZKP algorithm is demonstrated across diverse input sizes and parameters. Results indicate a success rate exceeding 90% on average, showcasing the robustness of the method. The recurring interaction between the Verifier and Prover enhances the Prover's authentication, thereby improving the algorithm’s reliability. Implementation of the algorithm, achievable through standard cryptographic tools and protocols, can fortify the security of multiple cryptographic applications. A significant application can be found in Digital Identity Management Systems (DIMS). Currently, these systems are vulnerable to a myriad of threats, including identity spoofing, data breaches, and internal security risks. The application of the ZKP algorithm can simultaneously augment security and withhold sensitive information, potentially transforming the DIMS security landscape. Future research may focus on improving the efficiency and scalability of the multi-round ZKP algorithm. There also remains a vast potential for exploring additional applications of this technique within various cryptographic domains.
The integration of fog computing and blockchain in the Internet of Medical Things (IoMT) domain has wholly transformed the healthcare industry and e-health services. In IoMT, the patient’s personal health data is shared on an open channel that makes the IoMT system an easy target for attackers. Therefore, confidentiality and authentication are the key security requirements for an IoMT system. Although few works have been proposed to provide secure communication in conventional healthcare infrastructures, limited work has been done to achieve data confidentiality and authentication in blockchain-based IoMT under fog environment. Therefore, this work proposes a blockchain-assisted certificateless aggregate signcryption called BCSoM scheme that achieves data confidentiality and device/patient authentication. In the proposed work, first, IoMT devices generate a signcrypted text and transmit it to an aggregator that generates an aggregated signcrypted text and sends it to a receiver fog server. The receiver fog server verifies the signcrypted text through the blockchain and also performs unsigncryption to retrieve the original message. The proposed scheme is proven secure under the Discrete Logarithm (DL) and Computational Diffe–Hellman (CDH) assumptions. Finally, a thorough performance analysis using the Hyperledger Fabric platform and cryptographic libraries shows that the proposed scheme is computationally more efficient when compared to existing works.
Timed data release refers to protecting sensitive data that can be accessed only after a pre-determined amount of time has passed. While blockchain-based solutions for timed data release provide a promising approach for decentralizing the process, designing an attack-resilient timed-release service that is resilient to malicious adversaries in a blockchain network is inherently challenging. A timed-release service on a blockchain network is inevitably exposed to the risk of post-facto attacks where adversaries may launch attacks after the data is released in the blockchain network. Existing incentive-based solutions for timed data release in Ethereum blockchains guarantee protection under the assumption of a fully rational adversarial environment in which every peer acts rationally. However, these schemes fail invariably when even a single participating peer node in the protocol starts acting maliciously and deviates from the rational behavior. In this paper, we propose a systematic solution for attack-resilient and practical blockchain-based timed data release in a mixed adversarial environment, where both malicious adversaries and rational adversaries exist. We first propose an effective uncertainty-aware reputation measure to capture the behaviors of the peer involved in timed data release activities in the network. In light of such a measure, we present the design of a basic protocol that consists of two critical ingredients, namely reputation-aware peer recruitment and verifiable enforcement protocols. The former, prior to the start of the enforcement protocols, performs peer recruitment based on the reputation measure to make the design probabilistically attack-resilient to the post-facto attacks. The latter is responsible for contractually guarding the recruited peers at runtime by transparently reporting observed adversarial behaviors. However, the basic recruitment design is only aware of the reputation of the peers and it does not consider the working time schedule of the participating peers and as a result, it results in lower attack-resilience. To enhance the attack resilience further without impacting the verifiable enforcement protocols, we propose a temporal graph-based reputation-aware peer recruitment algorithm that carefully determines the peer recruitment plan to make the service more attack-resilient. In our proposed approach, we formally capture the timed data release service as a temporal graph and we develop a novel maximal attack-resilient path-finding algorithm on the temporal graph for the participating peers. We implement a prototype of the proposed approach using Smart Contracts and deploy it on the Ethereum official test network, Rinkeby. For extensively evaluating the proposed techniques, we perform simulation experiments to validate the effectiveness of the reputation-aware timed data release protocols as well as our proposed temporal-graph-based improvements. The results demonstrate the effectiveness and strong attack resilience of the proposed mechanisms and our approach incurs only a modest gas cost.
Lucas Mayr, Lucas Palma, Gustavo Zambonin, Wellington Fernandes Silvano · 5 authors
Private key management is a complex obstacle arising from the traditional public key infrastructure model. However, before any related security breach can be addressed, it must first be reliably detected. Certificate Transparency (CT) is an example of a certificate issuance monitoring strategy, developed to detect the possible malfeasance of certification authorities (CAs). To the best of our knowledge, CT and other detection mechanisms do not cover digitally signed documents made by an end user, which are also susceptible to CA misbehavior. We modify the CT framework to handle signed documents via logging certificates in the blockchain to enable the secure and user-friendly monitoring of one-time signatures, backdating protection, and effective CA misbehavior detection. Moreover, to demonstrate the feasibility of our proposal, we present distinct deployment scenarios and analyze the storage, performance, and monetary costs.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Federated Learning (FL) is a well-known paradigm of distributed machine learning on mobile and IoT devices, which preserves data privacy and optimizes communication efficiency. To avoid the single point of failure problem in FL, decentralized federated learning (DFL) has been proposed to use peer-to-peer communication for model aggregation, which has been considered an attractive solution for machine learning tasks on distributed personal devices. However, this process is vulnerable to attackers who share false models and data. If there exists a group of malicious clients, they might harm the performance of the model by carrying out a poisoning attack. In addition, in DFL, clients often lack the incentives to contribute their computing powers to do model training. In this paper, we proposed Blockchain-based Decentralized Federated Learning (BDFL), which leverages a blockchain for decentralized model verification and auditing. BDFL includes an auditor committee for model verification, an incentive mechanism to encourage the participation of clients, a reputation model to evaluate the trustworthiness of clients, and a protocol suite for dynamic network updates. Evaluation results show that, with the reputation mechanism, BDFL achieves fast model convergence and high accuracy on real datasets even if there exist 30\% malicious clients in the system.
Ciphertext policy-attribute-based encryption (CP-ABE), which provides fine-grained access control and ensures data confidentiality, is widely used in data sharing. However, traditional CP-ABE schemes often choose to outsource data to untrusted third-party cloud service providers for storage or to verify users' access rights through third parties, which increases the risk of privacy leakage and also suffers from the problem of opaque permission verification. This paper proposes an access control scheme based on blockchain and CP-ABE, which is based on multiple authorization centers and supports policy updating. In addition, blockchain technology's distributed, decentralized, and tamper-proof features are utilized to solve the trust crisis problem in the data-sharing process. Security analysis and performance evaluation show that the proposed scheme improves the computational efficiency by 18%, 26%, and 68% compared to previous references. The proposed scheme also satisfies the indistinguishability under chosen-plaintext attack (IND-CPA).
Mustafa Ibrahim Alnajjar, Mehmet Sabır Kiraz, Ali H. Al‐Bayatti, Süleyman Kardaş
A distributed ledger is a shared and synchronized database across multiple designated nodes, often referred to as miners, validators, or peers. These nodes record, distribute, and access data to ensure security and transparency. However, these nodes can be compromised and manipulated by selectively choosing which user transactions to include, exclude, or reorder, thereby gaining an unfair advantage. This is known as a miner/maximal extractable value (MEV) attack. Existing solutions can be classified into various categories, such as MEV auction platforms and time-based ordering properties, which rely on private transaction Mempools. In this paper, we first identify some architectural weaknesses inherent in the latest proposals that divide the block creation and execution roles into separate functions: block builders and block executors. The existing schemes mainly suffer from the verifiability of the decryption process, where a corrupted builder or executor can simply deny the inclusion of specific targeted transactions by exploiting the fact that all transactions are in plain format. To address this, we propose an enhanced version that incorporates a verifiable decryption process. On a very high level, within our proposal, whenever an Executor or a Builder performs a decryption, the decrypted values must be broadcasted. This enables any entity in the network to publicly verify whether the decryption was executed correctly, thus preventing malicious behavior by either party from going undetected. We also define a new adversary model for MEV and conduct a comprehensive security analysis of our protocol against all kinds of potential adversaries related to MEV. Finally, we present the performance analysis of the proposed solution.
Open access
2 source records
Physical Unclonable Functions (PUFs) and Hardware Security
This paper presents secure mempool designs under asymmetric DoS attacks. We formulate safety definitions under two abstract DoSes, namely eviction- and locking-based attacks. We propose a safe transaction admission framework for securing mempools, named saferAd, that achieves both eviction- and locking-safety. The proven security stems from an upper bound of the attack damage under locking DoSes and a lower bound of the attack cost under eviction DoSes. The evaluation by replaying real transaction traces shows saferAd incurs negligible latency or insignificant change of validator revenue.
P. Thanalakshmi, A. Rishikhesh, Joel Marion Marceline, Gyanendra Prasad Joshi · 5 authors
Blockchain transactions are decentralized, secure, and transparent, and they have altered industries. However, the emergence of quantum computing presents a severe security risk to the traditional encryption algorithms used in blockchain. Post-quantum signatures are required to preserve integrity and reliability. Furthermore, combining the InterPlanetary File System (IPFS) with blockchain provides a long-term strategy for data storage and sharing. This study investigates the integration of post-quantum signatures with the IPFS in a blockchain system, which can considerably enhance blockchain system efficiency. We increase security and efficiency by recording hash values of signatures and public keys within the blockchain and storing their actual content using the IPFS. The study compares NIST-recommended post-quantum signatures with the ECDSA in a Bitcoin exchange scheme to show how effective the system is in countering quantum threats while maintaining optimal performance. This research makes an important addition to the long-term viability and dependability of blockchain technology in the face of the growing landscape of quantum computing breakthroughs.
K. R. Raghunandan, Bhavya Kallapu, Radhakrishna Dodmane, Krishnaraj Rao N S · 6 authors
The global production of information continuously increases in quantity and variety. However, the tools and technologies developed to handle such large volumes of data have not adequately met the security and privacy requirements. Existing cloud security systems, often managed by a trusted third party, are susceptible to various security risks. To address these challenges and ensure the protection of personal information, blockchain technology emerges as a crucial solution with substantial potential. This research uses the blockchain-powered attribute-aware encryption method to establish a real-time secure communication approach over the cloud. By employing attribute-based encryption technology, data owners can implement fine-grained search permissions for data users. The proposed solution incorporates accessible encryption technology to enable secure access to encrypted data and facilitate keyword searches on the blockchain. This study provides a functional comparison of recently developed attribute-based encryption algorithms. The access control strategy comprises two access tree types and a linear secret-sharing system, serving as the main components. The elliptic curve’s base field was set to 512b, and the bilinear pairing parameter type used was Type-A. This approach involves storing keywords on a remote server and encrypting them using attribute-based encryption. Furthermore, the encrypted data blockchain and the corresponding ciphertext are stored in the blockchain. Numerical experiments were conducted to evaluate the system’s key generation, trapdoor building, and keyword retrieval capabilities.
Zero-knowledge Range Proof(ZKRP) has gained increasing interest due to its applications in blockchain and cryptocurrencies in particular.ZKRP provides a mechanism to prove that a hidden integer belongs to a given interval without revealing any information about hidden integers.Some ZKRP depends on an honest and reliable third party.Others avoid from the third party.Currently, one of the famous ZKRP is the so-called Bulletproofs proposed by Bunz et al.Applying well-known homomorphic encryption methods in realizing ZKRP is a prospective direction.This paper proposes a new ZKRP based on one of the well-known homomorphic encryption methods-the order-preserving encryption method.
Blockchain integrates peer-to-peer networks, distributed consensus, smart contracts, cryptography, etc. It has the unique advantages of weak centralization, anti-tampering, traceability, openness, transparency, etc., and is widely used in various fields, e.g., finance and healthcare. However, due to its open and transparent nature, attackers can analyze the ledger information through clustering techniques to correlate the identities between anonymous and real users in the blockchain system, posing a serious risk of privacy leakage. The ring signature is one of the digital signatures that achieves the unconditional anonymity of the signer. Therefore, by leveraging Distributed Key Generation (DKG) and Elliptic Curve Cryptography (ECC), a blockchain-enabled secure ring signature scheme is proposed. Under the same security parameters, the signature constructed on ECC has higher security in comparison to the schemes using bilinear pairing. In addition, the system master key is generated by using the distributed key agreement, which avoids the traditional method of relying on a trusted third authorizer (TA) to distribute the key and prevents the key leakage when the TA is not authentic or suffers from malicious attacks. Moreover, the performance analysis showed the feasibility of the proposed scheme while the security was ensured.
Open access
Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Due to the modern relevance of blockchain technology, smart contracts present both substantial risks and benefits. Vulnerabilities within them can trigger a cascade of consequences, resulting in significant losses. Many current papers primarily focus on classifying smart contracts for malicious intent, often relying on limited contract characteristics, such as bytecode or opcode. This paper proposes a novel, two-layered framework: 1) classifying and 2) directly repairing malicious contracts. Slither’s vulnerability report is combined with source code and passed through a pre-trained RandomForestClassifier (RFC) and Large Language Models (LLMs), classifying and repairing each suggested vulnerability. Experiments demonstrate the effectiveness of fine-tuned and prompt-engineered LLMs. The smart contract repair models, built from pre-trained GPT-3.5-Turbo and fine-tuned Llama-2-7B models, reduced the overall vulnerability count by 97.5% and 96.7% respectively. A manual inspection of repaired contracts shows that all retain functionality, indicating that the proposed method is appropriate for automatic batch classification and repair of vulnerabilities in smart contracts.
UNSTRUCTURED This paper explores the relationship between the development of the internet and health care, highlighting their parallel growth and mutual influence. It delves into the transition from the early, static days of Web 1.0, akin to siloed physician expertise in health care, to the more interactive and patient-centric era of Web 2.0, which was accompanied by advancements in medical technologies and patient engagement. This paper then focuses on the emerging era of Web3—the decentralized web—which promises a transformative shift in health care, particularly in how patient data are managed, accessed, and used. This shift toward Web3 involves using blockchain technology for decentralized data storage to enhance patient data access, control, privacy, and value. This paper also examines current applications and pilot projects demonstrating Web3’s practical use in health care and discusses key questions and considerations for its successful implementation.
With the development of big data and cloud computing, ensuring authenticity and validity has become paramount issue. This paper introduces a novel verification mechanism, which is based on game theory and smart contracts, to validate the genuineness of results from cloud services given to users. It not only vouches for the veracity of these results but also promotes participation from trustworthy cloud service providers by introducing a strategically designed incentive system. The designed game-theoretical model combined with the execution sequence of the smart contracts acts as a deterrent against deceitful actions by potential malicious service entities. Experimental results prove the effectiveness and feasibility of this method.
Attribute-based anonymous credentials offer users fine-grained access control in a privacy-preserving manner. However, in such schemes obtaining a user's credentials requires knowledge of the issuer's public key, which obviously reveals the issuer's identity that must be hidden from users in certain scenarios. Moreover, verifying a user's credentials also requires the knowledge of issuer's public key, which may infer the user's private information from their choice of issuer. In this paper, we introduce the notion of double issuer-hiding attribute-based credentials (${\sf DIHAC}$) to tackle these two problems. In our model, a central authority can issue public-key credentials for a group of issuers, and users can obtain attribute-based credentials from one of the issuers without knowing which one it is. Then, a user can prove that their credential was issued by one of the authenticated issuers without revealing which one to a verifier. We provide a generic construction, as well as a concrete instantiation for${\sf DIHAC}$based on structure-preserving signatures on equivalence classes (JOC's 19) and a novel primitive which we calltag-based aggregatable mercurial signatures. Our construction is efficient without relying on zero-knowledge proofs. We provide rigorous evaluations on personal laptop and smartphone platforms, respectively, to demonstrate its practicability.
Wenxuan Ye, Chendi Qian, Xueli An, Xueqiang Yan · 5 authors
Integrating native AI support into the network architecture is an essential objective of 6G. Federated Learning (FL) emerges as a potential paradigm, facilitating decentralized AI model training across a diverse range of devices under the co-ordination of a central server. However, several challenges hinder its wide application in the 6G context, such as malicious attacks and privacy snooping on local model updates, and centralization pitfalls. This work proposes a trusted architecture for supporting FL, which utilizes Distributed Ledger Technology (DLT) and Graph Neural Network (GNN), including three key features. First, a pre-processing layer employing homomorphic encryption is incorporated to securely aggregate local models, preserving the privacy of individual models. Second, given the distributed nature and graph structure between clients and nodes in the pre-processing layer, GNN is leveraged to identify abnormal local models, enhancing system security. Third, DLT is utilized to decentralize the system by selecting one of the candidates to perform the central server's functions. Additionally, DLT ensures reliable data management by recording data exchanges in an immutable and transparent ledger. The feasibility of the novel architecture is validated through simulations, demonstrating improved performance in anomalous model detection and global model accuracy compared to relevant baselines.
We present an implementation of a Web3 platform that leverages the Groth16 Zero-Knowledge Proof schema to verify the validity of questionnaire results within Smart Contracts. Our approach ensures that the answer key of the questionnaire remains undisclosed throughout the verification process, while ensuring that the evaluation is done fairly. To accomplish this, users respond to a series of questions, and their answers are encoded and securely transmitted to a hidden backend. The backend then performs an evaluation of the user's answers, generating the overall result of the questionnaire. Additionally, it generates a Zero-Knowledge Proof, attesting that the answers were appropriately evaluated against a valid set of constraints. Next, the user submits their result along with the proof to a Smart Contract, which verifies their validity and issues a non-fungible token (NFT) as an attestation of the user's test result. In this research, we implemented the Zero-Knowledge functionality using Circom 2 and deployed the Smart Contract using Solidity, thereby showcasing a practical and secure solution for questionnaire validity verification in the context of Smart Contracts.
In traditional cloud storage systems, users benefit from the convenience of data accessibility but face significant risks related to security. Ciphertext-policy attribute-based encryption (CP-ABE) schemes are employed to achieve fine-grained access control in cloud services to ensure confidentiality while maintaining data-sharing capabilities. However, existing approaches are impaired by two critical issues: illegal authorization and privacy leakage. Despite extensive discussions in the literature on interoperability, performance, scalability, and stability, the security of ABE-based cloud storage and data-sharing systems against adversaries-particularly those involving adaptively corrupt attribute authorities gaining unauthorized access to users' data-has not been sufficiently explored. Notably, few existing works even address security in the presence of adversaries, raising concerns about the practicality of these systems in real-world scenarios where malicious behavior is a genuine threat. Another pressing issue is privacy leakage, where sensitive user information, such as medical histories in healthcare use cases, embedded within the access policies, may be exposed to all users. This problem is exacerbated in ABE schemes that integrate blockchain technology for enhanced decentralization and interoperability, as using a public ledger shared across multiple users can further compromise privacy. To address these, we propose an enhanced blockchain-based data governance system that employs blockchain technology and attribute-based encryption to prevent illegal authorization and privacy leakage. Our novel ABE encryption system supports multi-authority use cases while hiding access policy and ensuring identity privacy, which also protects data sharing against corrupt authorities. Utilizing the Advanced Encryption Standard (AES) for data encryption, our system is optimized for real-world efficiency. Notably, the encrypted data is stored in a decentralized storage system, like the InterPlanetary File System (IPFS), which does not rely on any centralized service provider and can, therefore, be leveraged to achieve resilience against single-point failures. With the integration of smart contracts and multi-authority attribute-based encryption, coupled with blockchain's inherent transparency and traceability, our system realizes a balanced solution for fine-grained access control with preserved privacy, further fortifying against credential misuse. Besides the system design, we also present security proofs to demonstrate the robustness of the proposed system.
Muhammed Siraj, Mohd Izuan Hafez Ninggal, Nur Izura Udzir, Muhammad Daniel Hafiz Abdullah · 5 authors
Sensitive records stored in the cloud such as healthcare records, private conversation and credit card information are targets of hackers and privacy abuse. Current information and record management systems have difficulties achieving privacy protection of such sensitive records in a secure, transparent, decentralized and trustless environment. The Blockchain technology is a nascent and a promising technology that facilitates data sharing and access in a secure, decentralized and trustless environment. The technology enables the use of smart contracts that can be leveraged to complement existing traditional systems to achieve security objectives that were never possible before. In this paper, we propose a framework based on Blockchain technology to enable privacy-preservation in a secured, decentralized, transparent and trustless environment. We name our framework SmartCoAuth. It is based on Ethereum Smart Contract functions as the secure, decentralized, transparent authentication and authorization mechanism in the framework. It also enables tamper-proof auditing of access to the protected records. We analysed how SmartCoAuth could be integrated into a cloud application to provide reliable privacy-preservation among stakeholders of healthcare records stored in the cloud. The proposed framework provides a satisfactory level of data utility and privacy preservation.
The ‘Big Four’ accountancy firms dominate the auditing market, auditing almost all the Financial Times Stock Exchange (FTSE) 100 companies. This leads to people having to accept auditing results even if they may be poor quality and/or for inadequate purposes. In addition, accountants may provide different auditing results with the same financial data. These issues are hard for regulators such as the Financial Reporting Council to identify because of insufficient resources or inconsistent compliance. In this paper, we proposed a triple-entry accounting protocol to allow users to report Bitcoin transactions to a third-party auditor to comply with regulations such as the travel rule. It allows the auditor to easily detect anomalies and identify the non-compliant parties, whilst the blockchain itself provides a transparent and immutable record of these anomalies. Despite building on a public ledger, our solution preserves privacy and offers an interoperability layer for information exchange. Merkle proofs were used to record non-compliant transactions whilst allowing compliant transactions to be pruned from an auditor’s active database.
Abstract Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) are the most efficient proof systems in terms of proof size and verification. Currently, Groth’s scheme from EUROCRYPT 2016, $$\textsf{Groth16}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Groth</mml:mi> <mml:mn>16</mml:mn> </mml:mrow> </mml:math> , is the state-of-the-art and is widely deployed in practice. $$\textsf{Groth16}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Groth</mml:mi> <mml:mn>16</mml:mn> </mml:mrow> </mml:math> is originally proven to achieve knowledge soundness, which does not guarantee the non-malleability of proofs. There has been considerable progress in presenting new zk-SNARKs or modifying $$\textsf{Groth16}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Groth</mml:mi> <mml:mn>16</mml:mn> </mml:mrow> </mml:math> to efficiently achieve strong Simulation extractability, which is shown to be a necessary requirement in some applications. In this paper, we revise the Random oracle based variant of $$\textsf{Groth16}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Groth</mml:mi> <mml:mn>16</mml:mn> </mml:mrow> </mml:math> proposed by Bowe and Gabizon, BG18, the most efficient one in terms of prover efficiency and CRS size among the candidates, and present a more efficient variant that saves 2 pairings in the verification and 1 group element in the proof. This supersedes our preliminary construction, presented in CANS 2020 (Baghery et al. in CANS 20, volume 12579 of LNCS, Springer, Heidelberg. pp 453-461, 2020), which saved 1 pairing in the verification, and was proven in the generic group model. Our new construction also improves on BG18 in that our proofs are in the algebraic group model with Random Oracles and reduces security to standard computational assumptions in bilinear groups (as opposed to using the full power of the generic group model (GGM)). We implement our proposed simulation extractable zk-SNARK (SE zk-SNARK) along with BG18 in the library, and compare the efficiency of our scheme with some related works. Our empirical experiences confirm that our SE zk-SNARK is more efficient than all previous simulation extractable (SE) schemes in most dimensions and it has very close efficiency to the original $$\textsf{Groth16}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>Groth</mml:mi> <mml:mn>16</mml:mn> </mml:mrow> </mml:math> .