Single Point Of Failure Problem Research Articles

Intelligent software defined networking: Long short term memory‐graded rated unit enabled block‐attack model to tackle distributed denial of service attacks

AbstractSoftware defined networking (SDN) is the next‐generation network. SDN enhances the programming flexibility, speed and automation to improve the network's performance. In recent times SDN has played a vital role in networking technology. It communicates with underlying hardware infrastructure and directs traffic on a network. The most complicated issue in SDN is the control plane's single point of failure (SPF). The main reason for raising the SPF problem in SDN by distributed denial of service (DDoS) attacks. The network collapses during failures in SDN, and the control plane is considered a management controller. Therefore, a novel intrusion detection and prevention system (IDPS) is proposed in the proposed approach to address SDN's problems mentioned above. In the proposed approach, a long short term memory (LSTM) and graded rated unit (GRU) deep learning model is proposed as the “Block‐Attack” model. The main objective of using LSTM and GRU in the proposed approach is to enhance the rate of accuracy in detecting DDoS attacks in an SDN environment. The CICDDoS2019 dataset is used for experimental result analysis in the proposed approach. Initially, the dataset is fed into the preprocessing stage. Using the K‐medoid technique, raw datasets are preprocessed to reduce the model's sensitivity to low density. In the proposed approach, the support vector machine based machine learning (SVM‐ML) technique is utilized to prevent DDoS attacks in a Mininet‐based emulation. Then, LSTM and GRU deep learning (DL) techniques are used to define the block‐attack model to enhance the detection performance. The experimental results of the proposed approach “Block‐Attack” model attain 98.5% of accuracy to detect and prevent the DDoS attacks and 95.5% of accuracy for SVM based method.

An optimized protocol for cost effective communication in a multi-agent environment

Mobile agents can migrate and communicate through interaction messages in a multi-agent environment. A multi-agent environment should provide a mechanism where mobile agents can be tracked easily and communication among them can take place while consuming the least amount of resources. Among all the proposed schemes the home based and forward pointing based scheme seems to be the best in achieving the desired objectives. The analysis shows that besides offering some advantages the aforementioned approach suffers from using high amounts of memory, high transmission cost, and the single point of failure problems. In this research we propose managing forwarding pointers intelligently by removing them from hosts when they are not required, preventing unnecessary update messages when the agent's mobility goes high, calculating the shortest path instantly after the agent's migration, and acknowledging only high priority interaction messages. We have validated our proposed approach with the help of experiments on a simulation tool OCEMAgents. The results show that the proposed approach has achieved all the objectives that are claimed and it has reduced memory and network overhead by minimizing the usage of forwarding pointers and by reducing the transmission cost. Besides that the proposed approach can effectively handle the single point of failure problem. Based on the results, we can safely declare that the proposed approach can be cost-effective if it is implemented in a real multi-agent system.

Privacy-Preserving Data Mining on Blockchain-Based WSNs

Currently, the computational power present in the sensors forming a wireless sensor network (WSN) allows for implementing most of the data processing and analysis directly on the sensors in a decentralized way. This shift in paradigm introduces a shift in the privacy and security problems that need to be addressed. While a decentralized implementation avoids the single point of failure problem that typically applies to centralized approaches, it is subject to other threats, such as external monitoring, and new challenges, such as the complexity of providing decentralized implementations for data mining algorithms. In this paper, we present a solution for privacy-aware distributed data mining on wireless sensor networks. Our solution uses a permissioned blockchain to avoid a single point of failure in the system. Contracts are used to construct an onion-like structure encompassing the Hoeffding trees and a route. The onion-routed query conceals the network identity of the sensors from external adversaries, and obfuscates the actual computation to hide it from internally compromised nodes. We validate our solution on a use case related to an air quality-monitoring sensor network. We compare the quality of our model against traditional models to support the feasibility and viability of the solution.

A decentralized lightweight authentication protocol under blockchain

AbstractWith the continuous development of blockchain technology, blockchain gradually becomes to play an important role in the fields of finance, medicine, and new energy. In the certification of the membership of the blockchain, a third‐party certificate authority (CA) is used for certification. Considering the centralized structure of CA, and it is difficult for users to evaluate the credibility of CA. A decentralized blockchain membership authentication scheme and a key agreement protocol based on the elliptic curve are proposed by us. The protocol effectively addresses the credibility and single point of failure problems of centralized CAs in the traditional model. Through analysis, our scheme can effectively perform user registration and membership authentication instead of CAs. The security and correctness of the protocol was also analyzed using the formal protocol analysis tool ProVerif and the Ck model. The key authentication protocol we proposed can resist a variety of attacks, and the computational time consumption and Communication costs are relatively low.

Conditional Privacy Protection Scheme based on Blockchain and Ring Signcryption in VANETs

<p>As the infrastructure of intelligent transportation systems, Vehicular Ad hoc Networks (VANETs) improve the efficiency of transportation. Meanwhile, key management and privacy leakage of users in VANETs are two vital security aspects. It is extremely important to perform these actions promptly and efficiently. Based on the idea of batch authentication and ring signcryption, a conditional privacy protection scheme of anonymous multi-receiver is proposed in this paper. On the one hand, the scheme with ring list selection has an optional privacy level. On the other hand, the blockchain prevents the single point of failure problem in key management and shares the public keys of vehicles promptly in Road Side Units (RSUs). Finally, experiments show that the proposed scheme has higher efficiency with certain security as the security analysis shows.</p> <p> </p>

Blockchain for deep learning: review and open challenges.

Deep learning has gained huge traction in recent years because of its potential to make informed decisions. A large portion of today’s deep learning systems are based on centralized servers and fall short in providing operational transparency, traceability, reliability, security, and trusted data provenance features. Also, training deep learning models by utilizing centralized data is vulnerable to the single point of failure problem. In this paper, we explore the importance of integrating blockchain technology with deep learning. We review the existing literature focused on the integration of blockchain with deep learning. We classify and categorize the literature by devising a thematic taxonomy based on seven parameters; namely, blockchain type, deep learning models, deep learning specific consensus protocols, application area, services, data types, and deployment goals. We provide insightful discussions on the state-of-the-art blockchain-based deep learning frameworks by highlighting their strengths and weaknesses. Furthermore, we compare the existing blockchain-based deep learning frameworks based on four parameters such as blockchain type, consensus protocol, deep learning method, and dataset. Finally, we present important research challenges which need to be addressed to develop highly trustworthy deep learning frameworks.

Hierarchical blockchain structure for node authentication in IoT networks

Internet of Things (IoT) networks are large peer-to-peer networks of small devices that require a competent security system that is scalable and adaptable to the limited resources of the IoT devices. Node authentication is a crucial part of IoT security. The current authentication solutions require a centralized trusted party for authentication, which presents a single point of failure. Blockchain as a peer-to-peer network with decentralized authentication can provide a decentralized solution for node authentication. In existing literature, most blockchain applications in IoT are connected to existing blockchain networks by more computationally capable devices, thereby limiting their adaptability for IoT networks and presenting single point of failure problem. Considering the issues, this paper proposes a blockchain-based decentralized structure for authentication by arranging the IoT devices into clusters based on their computational capability, energy reserve and their location. The devices in each cluster are authenticated by a hierarchical structure of interconnected blockchains. To reduce the processing load we introduced a consensus protocol based on verifying identity-based encryption key signature of the device and its related cluster. The proposed structure simulation has shown a reduction of the processor and memory load of IoT devices. Further testing using Docker container network and Raspberry Pi devices network has shown that the proposed blockchain structure and consensus algorithm have reduced computational load. The analysis of the structure security and performance shows it offers comprehensive security protection while being lightweight and scalable.

Blockchain in oil and gas industry: Applications, challenges, and future trends

Today's systems, approaches, and technologies leveraged for managing oil and gas supply chain operations fall short of providing operational transparency, traceability, audit, security, and trusted data provenance features. Also, a large portion of the existing systems are centralized, manual, and highly disintegrated, which make them vulnerable to manipulation and the single point of failure problem. In this survey, we explore the potential opportunities and applications of blockchain technology in managing the exploration, production, and supply chain and logistics operations in the oil and gas industry as it can offer traceability, immutability, transparency, and audit features in a decentralized, trusted, and secure manner. We discuss state-of-the-art blockchain-based schemes, research projects, business initiatives, and case studies to highlight the practicability of blockchain in the oil and gas industry. We present the potential opportunities brought about by blockchain technology in various use cases and application scenarios. We present several systems that use blockchain-based smart contracts to automate critical services such as petroleum product tracking and tracing, international trade document protection, and coordination of purchasing and bidding activities for granting oil exploration rights to petroleum exploration and development companies. Finally, we present open challenges acting as future research directions.

Decision Making using the Blockchain Proof of Authority Consensus

As the modern world migrates towards an interconnected environment, be it financially, socially, or industrially, the need for distributed systems has become paramount. Emergent paradigms need decentralized solutions to better handle the single point of failure problem, one example is given by the Internet of Things (IoT), in which devices need to be connected to a central hub to function, or the secure decision making process. Blockchain comes with the solution that overcomes some of the shortcomings in existing systems and provides a secure alternative when designing decentralized systems. This paper proposes a decision making system based on the Proof of Authority consensus protocol enabled by the blockchain paradigm.

Trustworthy IoT Data Streaming Using Blockchain and IPFS

Today’s resource-constrained IoT streaming devices generate large amounts of data which is stored, processed, analyzed for value creation, and accessed using centralized systems, technologies, platforms, and services. Most existing systems leveraged for storing and accessing IoT streaming data fall short in providing transparency, traceability, reliability, trustworthiness, and security features. Also, they are vulnerable to the single point of failure problem due to centralization. In this paper, we propose a blockchain-based solution for resource-constrained IoT streaming devices that allows data chunks to be transferred in a decentralized, transparent, traceable, reliable, secure, and trustful manner. We preserve the privacy and confidentiality of the IoT streamed data through a proxy re-encryption network. We use the decentralized storage of the Interplanetary File System (IPFS) to store and share the IoT streaming data, thereby dealing with the large-size data storage problem. We present system diagrams and eleven algorithms along with their full implementation details. We perform security analysis to show our smart contract code is secure enough against well-known security threats and vulnerabilities. We compare our proposed approach with the existing solutions to show its novelty and effectiveness. We make our smart contract code publicly available on the GitHub repository.

Towards Public Integrity Audition for Cloud-IoT Data Based on Blockchain

With the rapidly developing of Internet of Things (IoT), the volume of data generated by IoT systems is increasing quickly. To release the pressure of data management and storage, more and more enterprises and individuals prefer to integrate cloud service with IoT systems, in which the IoT data can be outsourced to cloud server. Since cloud service provider (CSP) is not fully trusted, a variety of methods have been proposed to deal with the problem of data integrity checking. In traditional data integrity audition schemes, the task of data auditing is usually performed by Third Party Auditor (TPA) which is assumed to be trustful. However, in real-life TPA is not trusted as people thought. Therefore, these schemes suffer from the underlying problem of single-point failure. Moreover, most of the traditional schemes are designed by RSA or bilinear map techniques which consume heavy computation and communication cost. To overcome these shortcomings, we propose a novel data integrity checking scheme for cloud-IoT data based on blockchain technique and homomorphic hash. In our scheme, the tags of all data blocks are computed by a homomorphic hash function and stored in blockchain. Moreover, each step within the process of data integrity checking is signed by the performer, and the signatures are stored in blockchain through smart contracts. As a result, each behavior for data integrity checking in our scheme can be traced and audited which improves the security of the scheme greatly. Furthermore, batch-audition for multiple data challenges is also supported in our scheme. We formalize the system model of our scheme and give the concrete construction. Detailed performance analyses demonstrate that our proposed scheme is efficient and practical without the trust-assumption of TPA.

A V2V charging allocation protocol for electric vehicles in VANET

This paper tackles the problem of the propagation of charging information in Vehicular Ad-hoc Networks (VANETs) and the decentralized allocation of Vehicle-to-Vehicle (V2V) charging pairs. Electric Vehicles (EVs) have gained the attention of various sectors as a green alternative to the air-polluting fuel-based vehicles. However, due to the limitation of the EVs' battery capacity and the shortage in the number of charging stations causing significant waiting time to charge, V2V charging has emerged as a promising solution to help address these issues. Mainly, V2V solutions need to define two mechanisms: an information dissemination mechanism and a charging pairs allocation mechanism. In the literature, two architectures are proposed: centralized and semi-distributed using VANET. However, in addition to suffering from the single point of failure problem, centralized solutions consider only connected vehicles during the charging pair allocation. On the other hand, existing VANET based solutions address the problem of charging information dissemination while still performing the allocation of V2V charging pairs in a centralized way. In this paper, we propose an ad-hoc-based solution for V2V charging where both information dissemination and charging pairs allocation are performed over VANET. To do so, at the application layer of VANET, a decentralized protocol for V2V is proposed. This protocol is divided into two phases: providers announcement where consumers in the network can discover the nearby providers, and provider-consumer allocation where providers select the appropriate consumer based on the received OFFERs. At the network layer, Quality of Service-Optimized Link State Routing (QoS-OLSR) is used to find routing paths using the Multi-Point Relays (MPRs). These MPRs are in fact utilized by the protocol to propagate the announcement of the providers to the network. The simulation results show high performance of the proposed protocol in terms of packet delivery ratio and end-to-end delay. In addition, in terms of payoff and allocation rate, the proposed protocol performs better than centralized allocation in the presence of disconnected EVs.

A Semi-Centralized Dynamic Key Management Framework for In-Vehicle Networks

The current in-vehicle network lacks a robust security communication mechanism between Electronic Control Units (ECUs). Although different proposed frameworks aim to secure the Controller Area Network (CAN) bus communication, few of them consider relevant aspects such as key refreshing and management, ECU maintenance, and vehicle manufacturing process. Despite the fact that a centralized key distribution provides an efficient mechanism, security and safety fully depend on this centralized key generator, which may lead to a single point of failure problem. In this work, we present a semi-centralized dynamic key management framework that provides a decentralized and dynamic key generation during the vehicle's operation. Our framework not only increases security and safety even if the centralized key generator is offline but also reduces the number of keys, the communication payload inside the network, and the complexity of cryptographic material sharing during the vehicle's lifetime. Moreover, we propose a dynamic generation of session keys for different groups of ECU and external devices, which is a requirement for intelligent vehicles and future Internet of Vehicles. In order to evaluate the performance, we implement our framework on three hardware platforms with different computational power and validate its advantage, efficiency, and flexibility by comparing it with other frameworks.

HASFC: A MANO-Compliant Framework for Availability Management of Service Chains

Most softwarized telco services are conveniently framed as service function chains (SFCs). Indeed, being structured as a combination of interconnected nodes, service chains may suffer from the single point of failure problem, meaning that an individual node malfunctioning could compromise the whole chain operation. To guarantee highly available (HA) levels, service providers are required to introduce redundancy strategies to achieve specific availability demands, where cost constraints have to be taken into account as well. Along these lines we propose HASFC, a framework designed to support, through a dedicated REST interface, the MANO infrastructure in deploying SFCs with an optimal availability/cost trade-off. Our framework is equipped with: an availability model builder aimed to construct probabilistic models of the SFC nodes in terms of failure/repair actions; and a chaining and selection module to compose the possible redundant SFCs, and extract the best candidates thereof. Beyond providing architectural details, we demonstrate the functionalities of HASFC through a use case that considers the IP Multimedia Subsystem, an SFC-like structure adopted to manage multimedia contents within 4G/5G networks.

Blockchain for Waste Management in Smart Cities: A Survey

Smart cities have the potential to overcome environmental problems caused by improper waste disposal by improving human health, protecting the aquatic ecosystem, and reducing air pollution. However, today’s systems, approaches, and technologies leveraged for waste management are manual and centralized. This fact makes them vulnerable to manipulation and the single point of failure problem. Also, a large portion of the existing waste management systems within smart cities fall short in providing operational transparency, traceability, audit, security, and trusted data provenance features. In this paper, we explore the key role of blockchain technology in managing waste within smart cities as it can offer traceability, immutability, transparency, and audit features in a decentralized, trusted, and secure manner. We discuss the opportunities brought about by blockchain technology in various waste management use cases and application scenarios, including real-time tracing and tracking of waste, reliable channelization and compliance with waste treatment laws, efficient waste resources management, protection of waste management documentation, and fleet management. We introduce a framework that leverages blockchain-based smart contracts to automate the key services in terms of waste management of smart cities. We compare the existing blockchain-based waste management solutions based on important parameters. Furthermore, we present insightful discussions on several ongoing blockchain-based research projects and case studies to highlight the practicability of blockchain in waste management. Finally, we present open challenges that act as future research directions.

Blockchain-Based Forward Supply Chain and Waste Management for COVID-19 Medical Equipment and Supplies.

The year 2020 has witnessed unprecedented levels of demand for COVID-19 medical equipment and supplies. However, most of today’s systems, methods, and technologies leveraged for handling the forward supply chain of COVID-19 medical equipment and the waste that results from them after usage are inefficient. They fall short in providing traceability, reliability, operational transparency, security, and trust features. Also, they are centralized that can cause a single point of failure problem. In this paper, we propose a decentralized blockchain-based solution to automate forward supply chain processes for the COVID-19 medical equipment and enable information exchange among all the stakeholders involved in their waste management in a manner that is fully secure, transparent, traceable, and trustworthy. We integrate the Ethereum blockchain with decentralized storage of interplanetary file systems (IPFS) to securely fetch, store, and share the data related to the forward supply chain of COVID-19 medical equipment and their waste management. We develop algorithms to define interaction rules regarding COVID-19 waste handling and penalties to be imposed on the stakeholders in case of violations. We present system design along with its full implementation details. We evaluate the performance of the proposed solution using cost analysis to show its affordability. We present the security analysis to verify the reliability of the smart contracts, and discuss our solution from the generalization and applicability point of view. Furthermore, we outline the limitations of our solution in form of open challenges that can act as future research directions. We make our smart contracts code publicly available on GitHub.

The network architecture optimization based on the server load balancing technology

The paper takes the authentication gateway system for internal office network as the research object, for the performance bottleneck and single point of failure problem of the single authentication gateway deployed in the existing primary and standby modes, chooses an authentication gateway integration method based on CA certificate. The practical results show that: through implementing the authentication gateway cluster design and introducing load balancing mechanism, this method solves the performance, stability and single point of failure of the authentication gateway, and improves the resource utilization of the authentication gateway device. This method introduced in this paper can be used for reference for the network architecture optimization based on the server load balancing technology.

Blockchain for Electric Vehicles Energy Trading: Requirements, Opportunities, and Challenges

Today’s technologies, techniques, and systems leveraged for managing energy trading operations in electric vehicles fall short in providing operational transparency, immutability, fault tolerance, traceability, and trusted data provenance features. They are centralized and vulnerable to the single point of failure problem, and less trustworthy as they are prone to the data modifications and deletion by adversaries. In this paper, we present the potential advantages of blockchain technology to manage energy trading operations between electric vehicles as it can offer data traceability, immutability, transparency, audit, security, and confidentiality in a fully decentralized manner. We identify and discuss the essential requirements for the successful implementation of blockchain technology to secure energy trading operations among electric vehicles. We present a detailed discussion on the potential opportunities offered by blockchain technology to secure the energy trading operations of electric vehicles. We discuss several blockchain-based research projects and case studies to highlight the practicability of blockchain technology in electric vehicles energy trading. Finally, we identify and discuss open challenges in fulfilling the requirements of electric vehicles energy trading applications.

Blockchain-Based Solution for Distribution and Delivery of COVID-19 Vaccines.

Distribution and delivery of Coronavirus 2019 (COVID-19) vaccines have become challenging after their emergence. Today’s platforms and systems leveraged for managing data related to COVID-19 vaccines’ distribution and delivery fall short in providing transparency, trackability and traceability, immutability, audit, and trust features. Also, they are vulnerable to the single point of failure problem due to centralization. Such limitations hindering the safe, secure, transparent, trustworthy, and reliable distribution and delivery process of COVID-19 vaccines. In this paper, we propose an Ethereum blockchain-based solution for managing data related to COVID-19 vaccines’ distribution and delivery. We develop smart contracts to automate the traceability of COVID-19 vaccines while ensuring data provenance, transparency, security, and accountability. We integrate the Ethereum blockchain with off-chain storage to manage non-critical and large-sized data. We present algorithms and discuss their full implementation, testing, and validation details. We evaluate the proposed solution by performing cost and security analysis as well as comparing it with the existing non-blockchain and blockchain-based solutions. Performance evaluation results reveal that the proposed solution is low-cost, and our smart contracts are secure enough against possible attacks and vulnerabilities. The smart contracts code along with testing scripts is made publicly available.

DARE: A decentralized association rules extraction scheme for embedded data sets in distributed IoT devices

In the context of smart home, it is very important to identify usage patterns of Internet of things (IoT) devices. Finding these patterns and using them for decision-making can provide ease, comfort, practicality, and autonomy when executing daily activities. Performing knowledge extraction in a decentralized approach is a computational challenge considering the tight storage and processing constraints of IoT devices, unlike deep learning, which demands a massive amount of data, memory, and processing capability. This article describes a method for mining implicit correlations among the actions of IoT devices through embedded associative analysis. Based on support, confidence, and lift metrics, our proposed method identifies the most relevant correlations between a pair of actions of different IoT devices and suggests the integration between them through hypertext transfer protocol requests. We have compared our proposed method with a centralized method. Experimental results show that the most relevant rules for both methods are the same in 99.75% of cases. Moreover, our proposed method was able to identify relevant correlations that were not identified by the centralized one. Thus, we show that associative analysis of IoT device state change is efficient to provide an intelligent and highly integrated IoT platform while avoiding the single point of failure problem.