This paper presents a new privacy-preserving smart metering system. Our scheme is private under the differential privacy model and therefore provides strong and provable guarantees. With our scheme, an (electricity) supplier can periodically collect data from smart meters and derive aggregated statistics while learning only limited information about the activities of individual households. For example, a supplier cannot tell from a user's trace when he watched TV or turned on heating. Our scheme is simple, efficient and practical. Processing cost is very limited: smart meters only have to add noise to their data and encrypt the results with an efficient stream cipher.
Several papers addressed the privacy problems of smart metering in the recent past @cite_9 @cite_8 @cite_20 @cite_19 @cite_11 @cite_1 @cite_14 @cite_0 . However, only a few of them have proposed technical solutions to protect users' privacy. In @cite_20 @cite_11 , the authors discuss the different security aspects of smart metering and the conflicting interests among stakeholders. The privacy of billing is considered in @cite_14 @cite_8 . These techniques uses zero-knowledge proofs to ensure that the fee calculated by the user is correct without disclosing any consumption data.
@cite_14 @cite_8 @cite_9 @cite_1 @cite_0 @cite_19 @cite_20 @cite_11
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Smart grid proposals threaten user privacy by potentially disclosing fine-grained consumption data to utility providers, primarily for time-of-use billing, but also for profiling, settlement, forecasting, tariff and energy efficiency advice. We propose a privacy-preserving protocol for general calculations on fine-grained meter readings, while keeping the use of tamper evident meters to a strict minimum. We allow users to perform and prove the correctness of computations based on readings on their own devices, without disclosing any fine grained consumption. Applying the protocols to time-of-use billing is particularly simple and efficient, but we also support a wider variety of tariff policies. Cryptographic proofs and multiple implementations are used to show the proposed protocols are secure and efficient. Household smart meters that measure power consumption in real-time at fine granularities are the foundation of a future smart electricity grid. However, the widespread deployment of smart meters has serious privacy implications since they inadvertently leak detailed information about household activities. In this paper, we show that even without a priori knowledge of household activities or prior training, it is possible to extract complex usage patterns from smart meter data using off-the-shelf statistical methods. Our analysis uses two months of data from three homes, which we instrumented to log aggregate household power consumption every second. With the data from our small-scale deployment, we demonstrate the potential for power consumption patterns to reveal a range of information, such as how many people are in the home, sleeping routines, eating routines, etc. We then sketch out the design of a privacy-enhancing smart meter architecture that allows an electric utility to achieve its net metering goals without compromising the privacy of its customers. The security and privacy of future smart grid and smart metering networks is important to their rollout and eventual acceptance by the public: research in this area is ongoing and smart meter users will need to be reassured that their data is secure. This paper describes a method for securely anonymizing frequent (for example, every few minutes) electrical metering data sent by a smart meter. Although such frequent metering data may be required by a utility or electrical energy distribution network for operational reasons, this data may not necessarily need to be attributable to a specific smart meter or consumer. It does, however, need to be securely attributable to a specific location (e.g. a group of houses or apartments) within the electricity distribution network. The method described in this paper provides a 3rd party escrow mechanism for authenticated anonymous meter readings which are difficult to associate with a particular smart meter or customer. This method does not preclude the provision of attributable metering data that is required for other purposes such as billing, account management or marketing research purposes. Electricity suppliers have started replacing traditional electricity meters with so-called smart meters, which can transmit current power consumption levels to the supplier within short intervals. Though this is advantageous for the electricity suppliers' planning purposes, and also allows the customers a more detailed look at their usage behavior, it means a considerable risk for privacy. The detailed information can be used to judge whether persons are in the household, when they come home, which electric devices they use (e.g. when they watch TV), and so forth. In this work, we introduce the "smart metering privacy model" for measuring the degree of privacy that a smart metering application can provide. Moreover, we present two design solutions both with and without involvement of trusted third parties. We show that the solution with trusted party can provide "perfect privacy" under certain conditions. The first part of this paper discusses developments wrt. smart (electricity) meters (simply called E-meters) in general, with emphasis on security and privacy issues. The second part will be more technical and describes protocols for secure communication with E-meters and for fraud detection (leakage) in a privacy-preserving manner. Our approach uses a combination of Paillier's additive homomorphic encryption and additive secret sharing to compute the aggregated energy consumption of a given set of users. In this paper, we discuss symmetric-key and public-key protocols for key management in electricity transmission and distribution substations — both for communication within substations, and between substations and the network control center. Key management in the electricity network is widely regarded as a challenging problem, not only because of the scale, but also due to the fact that any mechanism must be implemented in resource-constrained environments. NISTIR 7628, the foundation document for the architecture of the US Smart Grid, mentions key management as one of the most important research areas, and the IEC 62351 standards committee has already initiated a new specification dedicated to key management. In this document, we describe different variants of symmetric-key and public-key protocols. Our design is motivated by the need to keep the mechanism simple, robust, usable and still cost effective. It is important to take into account the complexity and the costs involved not just in the initial bootstrapping of trust but also in subsequent key management operations like key update and revocation. It is vital to determine the complexity and the cost of recovery mechanisms — recovery not only from malicious, targeted attacks but also from unintentional failures. We present a detailed threat model, analysing a range of scenarios from physical intrusion through disloyal maintenance personnel to supply-chain attacks, network intrusions and attacks on central systems. We conclude that while using cryptography to secure wide area communication between the substation and the network control center brings noticeable benefits, the benefits of using cryptography within the substation bay are much less obvious; we expect that any such use will be essentially for compliance. The protocols presented in this paper are informed by this threat model and are optimised for robustness, including simplicity, usability and cost. Smart grids are a hot topic, with the US administration devoting billions of dollars to modernising the electricity infrastructure. Significant action is likely in metering, where the largest and most radical change may come in the European Union. The EU is strongly encouraging its 27 Member States to replace utility meters with ‘smart meters’ by 2022. This will be a massive project: the UK, for example, looks set to replace 47m meters at a cost of perhaps £350 each. Yet it is not at all clear what it means for a meter to be secure. The utility wants to cut energy theft, so it wants the ability to disable any meter remotely; but a prudent nation state might be wary of a facility that could let an attacker turn off the lights. Again, the utility may want to monitor its customers’ consumption by the half hour, so it can price discriminate more effectively; the competition authorities may find this abhorrent. Other parts of government might find it convenient to have access to fine-grained consumption data, but might find themselves up against privacy law. There are at least half-a-dozen different stakeholders with different views on security – which can refer to information, to money, or to the supply of electricity. And it’s not even true that more security is always better: some customers may opt for an interruptible supply to save money. In short, energy metering is ripe for a security-economics analysis, and in this paper we attempt a first cut. We end up with five recommendations for the regulation of a future smart meter infrastructure.