DeHiDe: Deep Learning-based Hybrid Model to Detect Fake News using Blockchain

The surge in the spread of misleading information, lies, propaganda, and false facts, frequently known as fake news, raised questions concerning social media's influence in today's fast-moving democratic society. The widespread and rapid dissemination of fake news cost us in many ways. For example, individual or societal costs by hampering elections integrity, significant economic losses by impacting stock markets, or increases the risk to national security. It is challenging to overcome the spreading of fake news problems in traditional centralized systems. However, Blockchain-- a distributed decentralized technology that ensures data provenance, authenticity, and traceability by providing a transparent, immutable, and verifiable transaction records can help in detecting and contending fake news. This paper proposes a novel hybrid model DeHiDe: Deep Learning-based Hybrid Model to Detect Fake News using Blockchain. The DeHiDe is a blockchain-based framework for legitimate news sharing by filtering out the fake news. It combines the benefit of blockchain with an intelligent deep learning model to reinforce robustness and accuracy in combating fake news's hurdle. It also compares the proposed method to existing state-of-the-art methods. The DeHiDe is expected to outperform state-of-the-art approaches in terms of services, features, and performance.Comment: 13 Pages, 5 figures, and 1 tabl

Efficient Concurrent Execution of Smart Contracts in Blockchains using Object-based Transactional Memory

This paper proposes an efficient framework to execute Smart Contract Transactions (SCTs) concurrently based on object semantics, using optimistic Single-Version Object-based Software Transactional Memory Systems (SVOSTMs) and Multi-Version OSTMs (MVOSTMs). In our framework, a multi-threaded miner constructs a Block Graph (BG), capturing the object-conflicts relations between SCTs, and stores it in the block. Later, validators re-execute the same SCTs concurrently and deterministically relying on this BG. A malicious miner can modify the BG to harm the blockchain, e.g., to cause double-spending. To identify malicious miners, we propose Smart Multi-threaded Validator (SMV). Experimental analysis shows that the proposed multi-threaded miner and validator achieve significant performance gains over state-of-the-art SCT execution framework.Comment: 49 pages, 26 figures, 11 table

An Efficient Framework for Execution of Smart Contracts in Hyperledger Sawtooth

Blockchain technology is a distributed, decentralized, and immutable ledger system. It is the platform of choice for managing smart contract transactions (SCTs). Smart contracts are self-executing codes of agreement between interested parties commonly implemented using blockchains. A block contains a set of transactions representing changes to the system and a hash of the previous block. The SCTs are executed multiple times during the block production and validation phases across the network. The execution is sequential in most blockchain technologies. In this work, we incorporate a direct acyclic graph (DAG) based parallel scheduler framework for concurrent execution of SCTs. The dependencies among a block's transactions are represented through a concurrent DAG data structure that assists in throughput optimization. We have created a DAG scheduler module that can be incorporated into blockchain platforms for concurrent execution with ease. We have also formally established the safety and liveness properties of the DAG scheduler. For evaluation, our framework is implemented in Hyperledger Sawtooth V1.2.6. The performance across multiple smart contract applications is measured for various scheduler types. Experimental analysis shows that the proposed framework achieves notable performance improvements over the parallel SCT execution frameworks

Cloud Service Provider Evaluation System using Fuzzy Rough Set Technique

Cloud Service Providers (CSPs) offer a wide variety of scalable, flexible, and cost-efficient services to cloud users on demand and pay-per-utilization basis. However, vast diversity in available cloud service providers leads to numerous challenges for users to determine and select the best suitable service. Also, sometimes users need to hire the required services from multiple CSPs which introduce difficulties in managing interfaces, accounts, security, supports, and Service Level Agreements (SLAs). To circumvent such problems having a Cloud Service Broker (CSB) be aware of service offerings and users Quality of Service (QoS) requirements will benefit both the CSPs as well as users. In this work, we proposed a Fuzzy Rough Set based Cloud Service Brokerage Architecture, which is responsible for ranking and selecting services based on users QoS requirements, and finally monitor the service execution. We have used the fuzzy rough set technique for dimension reduction. Used weighted Euclidean distance to rank the CSPs. To prioritize user QoS request, we intended to use user assign weights, also incorporated system assigned weights to give the relative importance to QoS attributes. We compared the proposed ranking technique with an existing method based on the system response time. The case study experiment results show that the proposed approach is scalable, resilience, and produce better results with less searching time.Comment: 12 pages, 7 figures, and 8 table

An Efficient Approach to Move Elements in a Distributed Geo-Replicated Tree

Replicated tree data structures are extensively used in collaborative applications and distributed file systems, where clients often perform move operations. Local move operations at different replicas may be safe. However, remote move operations may not be safe. When clients perform arbitrary move operations concurrently on different replicas, it could result in various bugs, making this operation challenging to implement. Previous work has revealed bugs such as data duplication and cycling in replicated trees. In this paper, we present an efficient algorithm to perform move operations on the distributed replicated tree while ensuring eventual consistency. The proposed technique is primarily concerned with resolving conflicts efficiently, requires no interaction between replicas, and works well with network partitions. We use the last write win semantics for conflict resolution based on globally unique timestamps of operations. The proposed solution requires only one compensation operation to avoid cycles being formed when move operations are applied. The proposed approach achieves an effective speedup of 14.6× to 68.19× over the state-of-the-art approach in a geo-replicated setting. © 2022 IEEE

Efficient parallel execution of block transactions in blockchain

Miners and validators in current blockchains serially execute block transactions. Such serial execution cannot efficiently utilize modern multi-core resources, consequently hampering system throughput. We propose three approaches to improve blockchain throughput by introducing parallel execution of block transactions. We present a static analysis-based DiPETrans approach that groups the block transactions into independent shards and executes them parallelly in a distributed fashion using a leader-follower method. DiPETrans is empirically evaluated with 5 million actual transactions from the Ethereum blockchain. Since static analysis fails to identify the conflicts precisely, we introduce OptSmart to exploit multi-processing on a multi-core system to improve throughput further. Miners and validators use multiple threads to parallelly execute smart contract transactions (SCTs) in a block. A miner concurrently executes SCTs using optimistic read-write software transactional memory systems (RWSTMs) and saves the non-conflicting SCTs in the concurrent bin and conflicting SCTs in the block graph (BG). Later, validators re-execute SCTs deterministically in parallel to validate the block by using information appended by the concurrent miner. In terms of throughput, optimistic object-based STMs (OSTMs) with higher-level objects are known to outperform RWSTMs. We propose ObjSC approach based on optimistic OSTM, and a counter-based smart multi-threaded validator (SMV) that efficiently detects and rejects malicious blocks proposed by the malicious miners. The simulation result shows that the proposed approaches outperform existing approaches. © 2021 ACM

An Efficient Approach to Move Elements in a Distributed Geo-Replicated Tree

Replicated tree data structures are extensively used in collaborative applications and distributed file systems, where clients often perform move operations. Local move operations at different replicas may be safe. However, remote move operations may not be safe. We present an efficient algorithm to perform move operations on the distributed replicated tree while ensuring eventual consistency. The proposed technique is primarily concerned with resolving conflicts efficiently, requires no interaction between replicas, and works well with network partitions. We use the last write win semantics for conflict resolution based on globally unique operation timestamps. The proposed solution requires only one compensation operation to avoid cycles being formed when move operations are applied. The proposed approach achieves an effective speedup of 14.6-68.19× over the state-of-the-art approach in a geo-replicated setting. © 2022 IEEE

Achieving Greater Concurrency in Execution of Smart Contracts using Object Semantics

Popular blockchain such as Ethereum and several others execute complex transactions in blocks through user defined scripts known as smart contracts. Normally, a block of the chain consists of multiple transactions of smart contracts which are added by a miner. To append a correct block into blockchain, miners execute these smart contract transactions (SCT) sequentially. Later the validators serially re-execute the SCT of the block. In the current era of multi-core processors, by employing serial execution of the transactions, the miners and validators fail to utilize the cores properly and as a result have poor throughput. By adding concurrency using object semantics to smart contracts execution, we can achieve the better efficiency and higher throughput. Some authors have used read-write STMs (RWSTMs) for the concurrent execution of SCT. Working with higher level operations provide greater concurrency, better throughput and reduces the number of aborts than RWSTMs. In this paper, we develop an efficient framework to execute the SCT concurrently by miner using optimistic Object-Based Software Transactional Memory systems (OSTMs) and Multi-Version OSTMs (MV-OSTM). A proposed block includes SCT, final states of the shared data-items, hash of the previous block and a block graph (BG). BG captures the conflicting relations among the transactions. Later, the validators re-execute the same SCT concurrently and deterministically with the help of BG given by miner to verify the final state. If the validation is successful then proposed block appended into the blockchain and miner gets incentive otherwise discard the proposed block. MV-OSTM and OSTM miner performs 4.5x and 3.86x average speedups over serial miner. Along with, MV-OSTM and OSTM validator outperforms average 32.81x and 29.76x than serial validator