Efficient and Privacy-Preserving Data Aggregation Scheme for Smart Grid Against Internal Adversaries

In smart grids, smart meters periodically collect users' fine-grained multi-dimensional energy data, which poses great concerns on users' privacy and security. Existing privacy preserving multi-dimensional aggregation schemes suffer from heavy computational burdens, especially for smart meters with limited computational resources. To address these limitations, in this paper we propose an efficient and flexible multi-dimensional data aggregation scheme called MDA-SMuSha, by which smart meters employ the Shamir's multi-secret sharing to generate a set of shared secrets, with the first one kept locally, while the remained ones are packaged and then uploaded to a control center via an aggregator. By the MDA-SMuSha scheme, aggregation results of smart meters' multi-dimensional energy data during multiple periods can be obtained, with only one time of Paillier encryption conducted on the smart meters. In addition, it allows the control center to send query requests flexibly, i.e., at a pre-specified frequency or whenever it wants to obtain statistical data of interests. Rigorous security analyses show that the MDA-SMuSha scheme satisfies security requirements of privacy-preservation, authenticity and data integrity as well as fault-tolerance. Both theoretical analyses and experiment results show that the MDA-SMuSha scheme outperforms state-of-the art methods in terms of computation costs, with comparable communication costs.

Electricity theft-induced power loss is a pressing issue in both traditional and smart grid environments. In smart grids, smart meters can be used to track power consumption behaviour and detect any suspicious activity. However, smart meter readings can be compromised by deploying intrusion tactics or launching cyber attacks. In this regard, machine learning models can be used to assess the daily consumption patterns of customers and detect potential electricity theft incidents. Whilst existing research efforts have extensively focused on batch learning algorithms, this paper investigates the use of online machine learning algorithms for electricity theft detection in smart grid environments, based on a recently proposed dataset. Several algorithms including Naive Bayes, K-nearest Neighbours, K-nearest Neighbours with self-adjusting memory, Hoeffding Tree, Extremely Fast Decision Tree, Adaptive Random Forest and Leveraging Bagging are considered. These algorithms are evaluated using an online machine learning platform considering both binary and multi-class theft detection scenarios. Evaluation metrics include prediction accuracy, precision, recall, F-1 score and kappa statistic. Evaluation results demonstrate the ability of the Leveraging Bagging algorithm with an Adaptive Random Forest base classifier to surpass all other algorithms in terms of all the considered metrics, for both binary and multi-class theft detection. Hence, it can be considered as a viable option for electricity theft detection in smart grid environments.

Smart grid, characterized by high efficiency, security, and flexibility, is gradually replacing the traditional power grid. Data aggregation technology is frequently used to avoid user privacy disclosure as a result of power consumption data transmission in the smart grid. However, traditional one-dimensional data aggregation schemes fail to meet the demands of fine-grained analysis. Therefore, this paper proposes an efficient privacy-preserving multi-dimensional data aggregation (P 2 MDA) scheme in smart grid by virtue of homomorphic encryption and superincreasing sequence. The security analysis indicates that the proposed scheme is proved to be secure in the random oracle model, satisfying all security and privacy requirements. The extensive performance analysis shows that in comparison to the related schemes, the proposed scheme achieves lowest computation and communication costs, thus appropriate for practical applications.

While real-time electricity consumption data of users in smart grids can enable value-added services, such as Big Data analytics, each individual user's privacy needs to be protected. How to balance data utility and privacy protection is a significant issue, of which privacy-preserving data aggregation (PPDA) is a viable solution. Prior to this, researchers have proposed a number of PPDA schemes to address the above challenge. Unluckily, most of them suffer from security and privacy drawbacks, while others are inappropriate for resource-limited smart meters due to high cost of cryptographic operations. To tackle this issue, in this article, we propose a pairing-free and exponentiation-free certificateless PPDA scheme named CL-PPDA for smart grids. We prove the security of our design and analyze its performance. Comparative analyses with state-of-the-art work in theory and experiment show that our design not only has better security properties, but also has competitive computation overhead, especially on the resource-constrained smart meter side. Besides, we present an extension of our CL-PPDA scheme to support multidimensional data aggregation, which further enriches the functionality of our design.

With the development of the wireless communication technology and the popularity of mobile devices, the mobile wireless network (MWN) has been widely used in our daily life. Through the access point (AP), users could access the Internet anytime and anywhere using their mobile devices. Therefore, MWNs can bring much convenience to us. Due to the limitation of APs coverage, the seamless handover frequently occurs in practical applications. How to guarantee the users privacy and security and identify the real identity when he/she brings harm to the system becomes very challenging. To achieve such goals, many anonymous handover authentication (AHA) protocols have been proposed in the last several years. However, most of them have high computation costs because mobile nodes need to carry out the bilinear pairing operations or the hash-to-point operations. Besides, most of them cannot satisfy some critical requirements, such as non-traceability and perfect forward secrecy. In this paper, we first outline the security requirements of AHA protocols, and then propose a new AHA protocol to eliminate weaknesses existing in previous AHA protocols. Based on the hardness of two famous mathematical problems, we demonstrate that the proposed AHA protocol is secure against different kinds of attacks and can meet a variety of security requirements. It can be seen from the details of implementations that the proposed AHA protocol also has much less computation cost than three latest AHA protocols.

Currently, SM9 algorithm has received more and more attention as a new cryptographic product. The SM9 algorithm encryption and decryption principle relies on the mapping relationship on the elliptic curve. Although this mapping relationship improves the security, it will slightly reduce the efficiency. The goal of this article is to improve the efficiency of the SM9 algorithm. Different from the traditional assembly line acceleration method, we decided to start with the basic operation of the algorithm itself. There is a bilinear pairing operation on the elliptic curve, which completes the point to point on the elliptic curve. The calculation complexity directly determines the SM9 algorithm. For this reason, we propose two new bilinear pair processing methods. The former uses the properties of isomorphic mapping to transfer the operations involved in the calculation of bilinear pairs from a large feature domain to a small feature domain, reducing the number of operations on the feature domain. The latter is for special operations in the bilinear pairing process, adding intermediate variables to convert them into low-time-consuming multiplication operations. According to the traditional Miller algorithm, the calculation of bilinear pairs requires 900 multiplication time units. Our solution can reduce this value to 700 and 800 multiplication time units respectively. In addition, the two algorithms have not changed the mapping relationship of the bilinear pair. On the premise of ensuring the correct mapping relationship, the efficiency of the SM9 algorithm is improved.

Smart grids allow automated meter readings and facilitate two-way communications between the smart meters and utility control centers. As the smart grid becomes more intelligent, it becomes increasingly vulnerable to cyber-attacks. Smart grid security mainly focuses on mutual authentication and key management techniques. An impeding factor in grid security is the memory and processing constraints of the smart meters. The aim of this thesis is to propose a lightweight mutual authentication protocol with an effective key renewal mechanism between a residential smart meter and a gateway. The authentication protocol proposed in the thesis, guarantees source authentication, data integrity, message confidentiality, as well as non-repudiation. The security analysis renders this protocol robust against several attacks. Furthermore, its performance analysis provides meticulous results as to how the proposed protocol is efficient in terms of computation overhead, average delay and buffer occupancy at the gateway.

Recent development of smart cities includes advanced and necessary use of modern smart grid (SG), than the traditional power grid. The paradigm of SG has also transformed houses into a home area networks (HAN). In HAN, several smart devices and appliances are connected to the electricity control centers (ECC). Appliances share their load and consumption related information to ECC through smart meters. The consumption data may be used for supply-demand management, for example, by ramping production up or down as needed. However, security and privacy of the consumers data are greatly important, since fine-grained smart meter data may reveal an users presence/absence in his/her house. To address this issue, several public-key-based or identity-based data aggregation schemes have been proposed in the literature. However, most of such schemes either suffer from the complexity of certificate management or key escrow problem. To eliminate these issues, in this paper we propose an efficient certificate-based data aggregation (CB-DA) scheme. In the proposed CB-DA scheme, the owner selects a secret key and then use the secret key along with certificates as decryption/signing keys.

A smart grid is an intelligent power grid. In recent years, the smart grid environment and its applications are incorporated into a variety of areas. The smart grid environment, however, can expose much more information than the old environments. In the environment, smart devices can be media in the exposure of various and specific pieces of information as well as energy consumption. This poses a huge risk in that it, combined with other pieces of information, may expose much more information. The current smart grid environment raises a need to develop anonymous signature and authentication techniques to prevent privacy breaches. Trying to meet this need, the principal investigator conducted research for three years. This paper discusses both the research trends investigated by him and the limitations of the development research and future research in need. Smart grid security requires the development of encrypted anonymous authentication that is applicable to power plant security, including nuclear power plants as well as expandable test beds.

Smart grid (SG) achieves more convenient and efficient power transmission through the rapid development of the information and communication technology. In addition to the transmission of electrical energy, the SG system also involves privacy and control information of service providers, which is closely related to people's livelihood. However, at present, the data in the SG system are transmitted in the form of plaintext, which does not have complete protection measures for entity privacy and communication data security. Focusing on preserving entity privacy and data security, this article proposes an anonymous secure authentication protocol (ASAP-SG) for the SG environment. Based on elliptic curve cryptography and physical unclonable function, ASAP-SG can realize authentication and key agreement between smart meters and service providers. The security of ASAP-SG has been verified with proverif tool and proven strictly under the real-or-random model. Furthermore, heuristic analysis manifests that ASAP-SG can successfully resist known security attacks. Finally, a fully comparison with the other five most advanced schemes reveals that ASAP-SG consumes the optimal computation cost on both smart meters and service providers and reduces the communication overhead by 33.3%–45.8%, on the basis of satisfying ten security objectives. These features make ASAP-SG more suitable for resource-constrained SG environment.

The smart meters in electricity grids enable fine-grained consumption monitoring. Thus, suppliers could adjust their tariffs. However, as smart meters are deployed within the smart grid field, authentication and key establishment between smart grid parties (smart meters, aggregators, and servers) become an urgency. Besides, as privacy is becoming a big concern for smart meters, smart grid parties are reluctant to leak their real identities during the authentication phase. In this paper, we analyze the recent authentication schemes in smart grids and other applied fields, and propose an anonymous authentication and key establishment scheme between smart grid parties: FAuth. The proposed scheme is based on bilinear maps and the computational Diffie–Hellman problem. We changed the way the smart meter parties registered at Key Generation Center, making the proposed scheme robust against various potential attacks that could be launched by the Key Generation Center, as the scheme could avoid the private key of the smart meter parties from leaking to the Key Generation Center. Besides, the proposed scheme reduced the computational load, both at the smart meter side and at the aggregator side, which make it perfectly suitable for computation-constrained devices. Security proof results show the proposed scheme is secure under the BAN logic and random oracle model.

Machine learning (ML)-based intrusion detection system (IDS) approaches have been significantly applied and advanced the state-of-the-art system security and defense mechanisms. In smart grid computing environments, security threats have been significantly increased as shared networks are commonly used, along with the associated vulnerabilities. However, compared to other network environments, ML-based IDS research in a smart grid is relatively unexplored, although the smart grid environment is facing serious security threats due to its unique environmental vulnerabilities. In this article, we conducted an extensive survey on ML-based IDS in smart grids based on the following key aspects: (1) The applications of the ML-based IDS in transmission and distribution side power components of a smart power grid by addressing its security vulnerabilities; (2) dataset generation process and its usage in applying ML-based IDSs in the smart grid; (3) a wide range of ML-based IDSs used by the surveyed papers in the smart grid environment; (4) metrics, complexity analysis, and evaluation testbeds of the IDSs applied in the smart grid; and (5) lessons learned, insights, and future research directions.

Smart Grid is undergoing a huge transformation with the rise of smart metering systems and integration of renewable sources of energy. Although privacy attacks on smart grid have received significant research interest, loss of availability due to cyber-attacks is an underexplored area. Availability can be impacted with numerous attack surfaces consisting of e.g., metering equipment, switches, communication network that can cause grid shutdown. In this paper, we develop novel, realistic mathematical models for studying the effects of loss of availability attacks within smart grid environments. In addition, we integrate our models as part of a permissioned Blockchain platform solution viz., SGChain that can help in recovering from such attacks by providing a secured transmission of customer utility usage amongst co-operating peers of grid operators. Building upon the concept of a demand-response (DR) signal, we enable a local grid operator to monitor the usage regularly via the Blockchain in order to calculate increasing or decreasing energy supply levels from distributors for subsequent time cycles. Through evaluation experiments, we study how meter data corruption attacks induce overconsumption of energy with three actual consumers over a period of 48 hours. The attacks and users are classified as low, medium and high levels to show the validity of our DR signal chaincode. Our results demonstrate that even under high impact attacks, our approach fosters self-regulation in smart grid environments for detection/mitigation of availability attacks, while also maintaining a stable grid energy state.

Smart grid networks require sufficient protection so as to safeguard the sensitive data that is exchanged among the smart meter, gateway node, data aggregators and utility service providers. To this end, numerous schemes have been presented based on a myriad of techniques such as public key cryptography, bilinear pairing operations, device identities and elliptic curve cryptography among others. However, many security loopholes still lurk in these protocols. In addition, performance is another serious issue that needs to be solved especially for smart gas meters. In this paper, a symmetric key based message verification protocol is presented. Extensive security evaluation is executed to show that the proposed protocol offers mutual authentication, key agreement and untraceability. It is also resilient against man-in-the-middle, verifier leakage, message replay, impersonation and known session key attacks. In terms of performance, the proposed protocol has the least communication costs and lower computation overheads compared with its peers.

Vehicular Ad hoc networks (VANETs) as spontaneous wireless communication technology of vehicles has a wide range of applications like road safety, navigation and other electric car technologies, however its practicability is greatly hampered by cyber-attacks. Due to message broadcasting in an open environment during communication, VANETs are inherently vulnerable to security and privacy attacks. However to address the cyber-security issues with optimal computation overhead is a matter of current security research challenge. So this paper designs a secure and efficient certificate-less aggregate scheme (ECLAS) for VANETs applicable in a smart grid scenario. The proposed scheme is based on elliptic curve cryptography to provide conditional privacy-preservation by incorporating usage of time validated pseudo-identification for communicating vehicles besides sorting out the KGC (Key Generation Center) escrow problem. The proposed scheme is comparatively more efficient to relevant related research work because it precludes expensive computation operations likes bilinear pairings as shown by the performance evaluation. Similarly, communication cost is within the ideal range to most related works while considering the security requirements of VANETs system applicable in a smart grid environment.