Metering Infrastructure In Smart Grid Research Articles

KMS–AMI: an efficient and scalable key management scheme for secure two-way communications in advanced metering infrastructure of smart grid

KMS–AMI: an efficient and scalable key management scheme for secure two-way communications in advanced metering infrastructure of smart grid

Antiquantum Privacy Protection Scheme in Advanced Metering Infrastructure of Smart Grid Based on Consortium Blockchain and RLWE

Smart meters in advanced metering infrastructure (AMI) collect fine-grained, real-time power consumption data may result in user privacy leakage. Aiming at the problem that existing privacy protection schemes cannot resist quantum attacks, an antiquantum privacy protection scheme in AMI of smart grid based on consortium blockchain and ring learning with errors (RLWE) is proposed. The scheme has the following contributions. First, the RLWE-based secure communication scheme is designed in this article, which ensures the resistance of the scheme to quantum attacks. Second, all smart meters in AMI use anonymous identity to communicate with the control center, and the fine-grained power consumption data is also encrypted and digitally signed to prevent user privacy leakage and tampering of power consumption data. And the scheme does not use bilinear pairings and exponential operations and has efficient computational performance. Third, a two-tier consortium blockchain storage system consisted of regional gateways and data aggregators are designed to eliminate the single point of failure problems of the data aggregators. The practical byzantine fault tolerance consensus mechanism is improved to reduce the communication cost in the consensus process. The scheme's security is proven theoretically, and the experimental results show that the scheme has a low computational cost.

An Unconditionally Secured Privacy-Preserving Authentication Scheme for Smart Metering Infrastructure in Smart Grid

Industry 4.0 allows faster data accessibility, improved performance, fault identification, and remote control of machines within any smart factory. Due to the massive generation of delay-sensitive data, this system demands a robust security mechanism against security threats. In order to mitigate such potential attacks and provide security-free services, this article proposes an edge-based conditional privacy-preserving authentication scheme based on quantum key distribution protocol for secure authentication and secure communication within smart grid infrastructure. Apart from guaranteeing security against threats such as node impersonation, message tampering, and repudiation, the scheme also defends man-in-the-middle attacks, replay attacks, etc. We validate the proposed protocol through a simulation study. The result indicates that it performs reasonably well and enables unconditional security for the data exchanged between entities of smart grid infrastructure.

Cost-Benefit Analysis of Advanced Metering Infrastructure of Smartgrid: A Case Study of Dhaka City

The aim of this research is to present a methodological approach to obtain the cost-benefit impact at environmental and socioeconomic level, related to the integration of advanced metering infrastructure (AMI) into utilities and their residential customers. The methodology used to quantify the costs and benefits of implementing such technology in smargrid domain at Dhaka city. The socioeconomic benefits estimated in this research were related to job creation, energy consumption decrease, reduction of non-technical losses, and the reduction of CO2 emissions. An economic analysis using the net present value is presented here for assessing the impact caused by smart metering implementation. Also, sensitivity is analyzed for energy price, AMI cost and duration of the project. The result shows that AMI system implantation has advantages over current situation.

Quality of Service Improvement in Neighborhood Area Networking for AMI With ZigBee-Based Tunable Clustered Scale-Free Topology and RPL Routing

This paper deals with the unique development of tunable clustered scale-free neighbourhood area networking (TSFNAN) using ZigBee for establishment of smart grid communication. The complexity of ZigBee based multihop mesh links between gateway and smart meters (SMs) are reduced by extracting the hop reduction feature of scale free and tunable clustering schemes. Further, the routing protocol for low power and lossy networking (RPL) is also adopted to avoid the requirement of route discovery during data transmission. The different service challenges of neighbourhood area networking (NAN) in advanced metering infrastructure of smart grid can thus be met with improved quality of service. A Markov chain delay model is developed to analyse the latency and packet loss in data transmission. The gateway position and the number of SMs are made scalable by correlating the hop count with the tunable clustering coefficient. The proposed system is simulated for a given area with (i) four clusters each containing 2500 SMs and (ii) one cluster containing 10000 SMs. A prototype model with 20 ZigBee nodes is experimented with different coverage range. The system performance is discussed and compared for all such case studies and an encouraging result suggests its practical feasibility with improved QoS.

LIKA: Lightweight Identity Based Key Agreement Protocol for Secure Data Transmission in Advanced Metering Infrastructure of Smart Grid

Integration of information communication technology via the Internet of Things devices and sensors can enable an efficient power service for utility providers to consumers in advanced metering infrastructure. Authentication and cryptographic mechanisms protect identity, data security and privacy from unauthorised interception for smart meters to servers. In the last couple of years, many key agreement protocols have been prescribed and deployed to fix those issues. Unfortunately, the deployed protocols did not work inside the same protocols, specifically parameter detection and recognition for session key generation, as they entail high computation time and communication bits overheads. Furthermore, the absence of forward secrecy and user anonymity affects the authentication. Therefore, we have proposed a lightweight identity-based key agreement (LIKA) utilising the Diffie–Hellman cryptography with a trusted authority. It seeks to cover both the security and performance criteria with equal weight. The protocol is evaluated by the Canetti and Krawczyk adversarial model, Avispa and cryptographic analysis released the session keys that were not considered as an adversary during mutual authentication. Moreover, as compared to related work, the proposed protocol took the least amount of time (5.319 ms and 1056 bits) for the entire process of session key generation. Furthermore, comparative analysis has shown that the LIKA adequately encompasses computation, communication, and security assessments. Consequently, it is more convenient for practical implementation for a smart grid.

Cloud‐based authentication and key management protocol for advanced metering infrastructure in smart grid

AbstractIn smart grid networks, the advanced metering infrastructure (AMI) enables sensors and communication networks to measure electricity consumed or generated by users. However, among the challenges to be overcome related to security in the AMI system is resistance to computer attacks, such as impersonation, denial of service, man in the middle, and redirection, which can compromise privacy, confidentiality, and availability of electrical systems. An efficient and effective authentication system is necessary to guarantee the privacy and confidentiality of data without compromising system performance, thus characterizing a challenge (need for a tradeoff between security and performance), which involves limited computing power and bandwidth and a high number of meters to be installed in a certain geographic area. This article introduces a group authentication and key agreement protocol that ensures both confidentiality and privacy of communications and avoids several computer attacks. It showed better communication and computational cost‐based performance compared to other protocols. Automated validation of internet security protocols and applications formally validated it, while security protocol animator tool simulated an intrusion, with good results.

Fed_ADBN: An efficient intrusion detection framework based on client selection in AMI network

AbstractData transmission between smart meters and data center is facing network security threats in advanced metering infrastructure of smart grid. The traditional solution is to move the data to the data center to build a centralized attack detection model, or divide the collected data into several independent and identically distributed datasets to build a distributed attack detection model. However, the long‐distance transmission and the centralized storage of data not only increase the communication overhead and time overhead, but also increase the risk of being attacked, causing privacy disclosure during the process of building the model. In this paper, we propose an efficient intrusion detection framework Fed_ADBN based on federated attention deep belief network and client selection. Clients cooperate with the data center to jointly build a horizontal federated learning framework. Under the premise of protecting data security by keeping data on the clients, we design a client selection algorithm based on client computing power, communication quality and security risks, which can improve the operating efficiency of federated learning. We also deploy a deep belief neural network with attention mechanism in each client to accurately detect possible network attacks in AMI network in real time. Experimental results show that compared with state‐of‐the‐art methods, the proposed framework can not only maintain good detection accuracy but also protect privacy.

Detection of False Data Injection Attacks in Industrial Wireless Sensor Networks Exploiting Network Numerical Sparsity

Existing studies on false data injection attacks, a type of stealth attacks against sensor networks aimed at compromising the system in the cyber-physical security domain, have primarily been conducted on wired systems for applications such as advanced metering infrastructure in smart grid. However, the emerging trend of the widespread deployment of industrial wireless sensor networks for various new functionalities as well as for replacement of legacy systems, on the other hand, calls for both data aggregation methods that are cost-effective, scalable and easily implementable, as well as feasible approaches to detect injected false data in coordination with such data aggregation models. In this paper, we propose a numerical sparsity-based detection scheme operating upon a network coding-based data aggregation model paired with compressed sensing-based decoding, against attacks that alter the overall network sparsity by compromising and injecting falsified data into multiple sensor nodes in the network. Both the applicative scope and performance of the proposed scheme are analyzed and compared to a more straightforward but realistically challenging approach of directly examining network compressibility, i.e. the number of sufficiently large readings of active nodes extracted from the decoded network signal. Numerical studies illustrate the proposed method is applicable for the usually sparsely active industrial wireless sensor networks, and offers faster, reliable decisions when the aforementioned false data injection attacks are launched.

PMAKE: Privacy-aware multi-factor authenticated key establishment scheme for Advance Metering Infrastructure in smart grid

Advanced Metering Infrastructure (AMI) ensures bidirectional communication for analysis and improvement of energy usage between service providers and customers. Establishing secure and efficient key exchange has become an important issue for the Internet-based smart grid environment. To ensure a secure, reliable and efficient operation in the smart grid environment, AMI should be protected from security attacks. On the other hand, since smart meters are installed in customer’s homes and businesses without hardware protection mechanisms that could be susceptible to physical attacks, where a dishonest customer may attempt to temper the metering data in order to make differences in billing. In this paper, an efficient privacy-aware multi-factor authenticated key establishment scheme (PMAKE) is proposed. One of the notable properties of the proposed scheme is that it can ensure physical security of the smart meters. From the performance analyses, we can claim that our scheme is secure and suitable for the resource limited smart meters.

Secure and Lightweight Authentication Scheme for Smart Metering Infrastructure in Smart Grid

In this article, a secure and lightweight authentication scheme, which provides trust, anonymity, and mutual authentication, with reduced energy, communicational, and computational overheads, is proposed for resource-constrained smart meters (SMs). The designed mutual authentication-based key agreement protocol leverages the advantages of fully hashed menezes-qu-vanstone key exchange mechanism along with Elliptic curve cryptography and one-way hash functions. Moreover, it allows to securely establish and verify the trust between the two communicating parties, i.e., SMs and neighbourhood area network gateway. These entities communicate over the insecure channel and form an important component of the smart metering infrastructure. Furthermore, extensive performance evaluation validates the supremacy of the designed protocol over the state-of-the-art in furnishing higher security features with minimal communicational and computational overheads. The obtained results also reflect that the proposed protocol is fit for implementation on resource-constrained SMs as it leads to minimal energy consumption.

Comparison analysis of electricity theft detection methods for advanced metering infrastructure in smart grid

While smart grid technologies are deployed to help achieve improved grid reliability and efficiency, energy companies are vulnerable to cyber-attacks leading to billions of dollars loss. The selection of an appropriate classification method for the electricity theft detection relies on operational requirements and resource constraints in real scenarios. Since unsupervised methods have high error rates, we employ a semi-supervised anomaly detection method [the principal component analysis (PCA)] technique for the electricity theft detection. PCA is compared with the peer-to-peer (P2P) method based on linear equations. The P2P method assumes known particular electricity theft patterns and in the absence of which, the P2P method detection system results in 100% false alarm. While PCA does not require any prior assumptions about the pattern of the electricity theft, 4% false alarm rate is observed. Our analysis shows an average of 45% improvement in the detection accuracy rate in comparison with the P2P method.

Comparison analysis of electricity theft detection methods for advanced metering infrastructure in smart grid

While smart grid technologies are deployed to help achieve improved grid reliability and efficiency, energy companies are vulnerable to cyber-attacks leading to billions of dollars loss. The selection of an appropriate classification method for the electricity theft detection relies on operational requirements and resource constraints in real scenarios. Since unsupervised methods have high error rates, we employ a semi-supervised anomaly detection method [the principal component analysis (PCA)] technique for the electricity theft detection. PCA is compared with the peer-to-peer (P2P) method based on linear equations. The P2P method assumes known particular electricity theft patterns and in the absence of which, the P2P method detection system results in 100% false alarm. While PCA does not require any prior assumptions about the pattern of the electricity theft, 4% false alarm rate is observed. Our analysis shows an average of 45% improvement in the detection accuracy rate in comparison with the P2P method.

A Novel Identity-Based Key Establishment Method for Advanced Metering Infrastructure in Smart Grid

Security is fundamental to the operation of smart grid and its advanced metering infrastructure (AMI). Key establishment is the core component in key management schemes and plays a crucial role in satisfying the security requirements. In recent years, many key establishment protocols have been proposed in the context of smart grids. However, their high overhead and complexity have undermined their ability to be practically employed in AMI. In this paper, we propose a novel identity-based key establishment protocol which employs elliptic curves at its core and has the lowest computational overhead among current secure protocols, especially at the meter side. We have given a detailed and comparative analysis of both security and computational burden for the proposed protocol as well as the previous efforts. We have evaluated the resilience of different protocols to well-known attacks by discussion, however, for the proposed protocol, we have also used AVISPA tool to formally verify its security. Compared to the previous solutions, the proposed protocol either is more secure or scores higher in performance benchmarks run on the same hardware.

An improved routing algorithm for advanced metering infrastructure in smart grid

The advanced metering infrastructure (AMI) is a key component of information transmission networks in smart grid because it connects distribution stations to grid users. However, the ever-increasing amount of information transmitted through smart meters inevitably results in heavy path loads and route congestion in AMI, which can lead to transmission delay and data packet loss. Therefore, in this paper, we proposed a routing algorithm based on load balancing that enabled data packets to select the optimal route between smart meter and data aggregator unit. We defined the routing optimization objective function for estimating the path load by using load factor,and employed an ant colony algorithm combined with simulated annealing (ACA-SA) to solve the optimization problem. Furthermore, with considering the quality of service (QoS) requirements of latency and reliability for AMI applications, two routing methods were proposed: the method with variable initial pheromone for delay-sensitive applications, whereas the method with variable visibility for applications with low packet-loss rate requirements. Analytical and simulation results demonstrated that the proposed algorithm can offer real-time and reliable communication for AMI in smart grid.

Hardware-Oriented Authentication for Advanced Metering Infrastructure

This paper introduces a novel authentication scheme for advanced metering infrastructure of smart grid using ring oscillator physically unclonable functions (ROPUFs). The scope of the design covers the communication between the utility company and the smart meter network. The scheme is based on hardware-oriented security and can be implemented on existing smart meters. Authentication keys of 64 bits are used for security level 1 communication. The size of keys can increase up to 1024 bits for security level 5. The cryptographic keys used in this scheme are extremely difficult to model by adversaries as each key is used only once. These authentication keys are generated from ROPUF response bits using the Hamming code. The design of the scheme ensures fault tolerance as ring oscillator comparison pairs with high frequency differences are selected to prevent bit flips and only 10% discrepancy is tolerated in parity bits. The proposed scheme is highly secure and efficient in terms of latency and data storage. As a proof of concept, two different machine learning algorithms, support vector machine and multigene genetic programming, are used to show that the scheme cannot be modeled by adversaries.

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can’t satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

Securing Metering Infrastructure of Smart Grid: A Machine Learning and Localization Based Key Management Approach

In smart cities, advanced metering infrastructure (AMI) of the smart grid facilitates automated metering, control and monitoring of power distribution by employing a wireless network. Due to this wireless nature of communication, there exist potential threats to the data privacy in AMI. Decoding the energy consumption reading, injecting false data/command signals and jamming the networks are some hazardous measures against this technology. Since a smart meter possesses limited memory and computational capability, AMI demands a light, but robust security scheme. In this paper, we propose a localization-based key management system for meter data encryption. Data are encrypted by the key associated with the coordinate of the meter and a random key index. The encryption keys are managed and distributed by a trusted third party (TTP). Localization of the meter is proposed by a method based on received signal strength (RSS) using the maximum likelihood estimator (MLE). The received packets are decrypted at the control center with the key mapped with the key index and the meter’s coordinates. Additionally, we propose the k-nearest neighbors (kNN) algorithm for node/meter authentication, capitalizing further on data transmission security. Finally, we evaluate the security strength of a data packet numerically for our method.

A Novel Non-cryptographic Security Services for Advanced Metering Infrastructure in Smart Grid

A Novel Non-cryptographic Security Services for Advanced Metering Infrastructure in Smart Grid

Energy-theft detection issues for advanced metering infrastructure in smart grid

With the proliferation of smart grid research, the Advanced Metering Infrastructure (AMI) has become the first ubiquitous and fixed computing platform. However, due to the unique characteristics of AMI, such as complex network structure, resource-constrained smart meter, and privacy-sensitive data, it is an especially challenging issue to make AMI secure. Energy theft is one of the most important concerns related to the smart grid implementation. It is estimated that utility companies lose more than $25 billion every year due to energy theft around the world. To address this challenge, in this paper, we discuss the background of AMI and identify major security requirements that AMI should meet. Specifically, an attack tree based threat model is first presented to illustrate the energy-theft behaviors in AMI. Then, we summarize the current AMI energy-theft detection schemes into three categories, i.e., classification-based, state estimation-based, and game theory-based ones, and make extensive comparisons and discussions on them. In order to provide a deep understanding of security vulnerabilities and solutions in AMI and shed light on future research directions, we also explore some open challenges and potential solutions for energy-theft detection.