As smart grids are getting popular and being widely implemented, preserving the privacy of consumers is becoming more substantial. Power generation and pricing in smart grids depends on the continuously gathered information from the consumers. However, having access to the data relevant to the electricity consumption of each individual consumer is in conflict with its privacy. One common approach for preserving privacy is to aggregate data of different consumers and to use their smart-meters for calculating the bills. But in this approach, malicious consumers who send erroneous data to take advantage or disrupt smart grid cannot be identified. In this paper, we propose a new statistical-based scheme for data gathering and billing in which the privacy of consumers is preserved, and at the same time, if any consumer with erroneous data can be detected. Our simulation results verify these matters.
The papers @cite_0 and @cite_15 focus on outsourcing to clouds or distributed systems. For encryption process, it is important to use a secure key management scheme. The cryptographic technique ensures that no privacy sensitive information would be revealed. But, there is still the challenge of how to efficiently query encrypted multidimensional metering data stored in an untrusted heterogeneous distributed system environment. @cite_17 addresses this issue and introduces a high performance and privacy-preserving query (P2Q) scheme which provides confidentiality and privacy in a semi-trusted environment.
@cite_0 @cite_15 @cite_17
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Abstract With the proliferation of smart grids, traditional utilities are struggling to handle the increasing amount of metering data. Outsourcing the metering data to heterogeneous distributed systems has the potential to provide efficient data access and processing. In an untrusted heterogeneous distributed system environment, employing data encryption prior to outsourcing can be an effective way to preserve user privacy. However, how to efficiently query encrypted multidimensional metering data stored in an untrusted heterogeneous distributed system environment remains a research challenge. In this paper, we propose a high performance and privacy-preserving query (P2Q) scheme over encrypted multidimensional big metering data to address this challenge. In the proposed scheme, encrypted metering data are stored in the server of an untrusted heterogeneous distributed system environment. A Locality Sensitive Hashing (LSH) based similarity search approach is then used to realize the similarity query. To demonstrate utility of the proposed LSH-based search approach, we implement a prototype using MapReduce for the Hadoop distributed environment. More specifically, for a given query, the proxy server will return K top similar data object identifiers. An enhanced Ciphertext-Policy Attribute-based Encryption (CP-ABE) policy is then used to control access to the search results. Therefore, only the requester with an authorized query attribute can obtain the correct secret keys to retrieve the metering data. We then prove that the P2Q scheme achieves data confidentiality and preserves the data owner’s privacy in a semi-trusted cloud. In addition, our evaluations demonstrate that the P2Q scheme can significantly reduce response time and provide high search efficiency without compromising on search quality (i.e. suitable for multidimensional big data search in heterogeneous distributed system, such as cloud storage system). As Cloud Computing becomes prevalent, sensitive information are being increasingly centralized into the cloud. For the protection of data privacy, sensitive data has to be encrypted before outsourcing, which makes effective data utilization a very challenging task. Although traditional searchable encryption schemes allow users to securely search over encrypted data through keywords, these techniques support only boolean search, without capturing any relevance of data files. This approach suffers from two main drawbacks when directly applied in the context of Cloud Computing. On the one hand, users, who do not necessarily have pre-knowledge of the encrypted cloud data, have to post process every retrieved file in order to find ones most matching their interest, On the other hand, invariably retrieving all files containing the queried keyword further incurs unnecessary network traffic, which is absolutely undesirable in today's pay-as-you-use cloud paradigm. In this paper, for the first time we define and solve the problem of effective yet secure ranked keyword search over encrypted cloud data. Ranked search greatly enhances system usability by returning the matching files in a ranked order regarding to certain relevance criteria (e.g., keyword frequency), thus making one step closer towards practical deployment of privacy-preserving data hosting services in Cloud Computing. We first give a straightforward yet ideal construction of ranked keyword search under the state-of-the-art searchable symmetric encryption (SSE) security definition, and demonstrate its inefficiency. To achieve more practical performance, we then propose a definition for ranked searchable symmetric encryption, and give an efficient design by properly utilizing the existing cryptographic primitive, order-preserving symmetric encryption (OPSE). Thorough analysis shows that our proposed solution enjoys as-strong-as-possible" security guarantee compared to previous SSE schemes, while correctly realizing the goal of ranked keyword search. Extensive experimental results demonstrate the efficiency of the proposed solution. In cloud computing, clients usually outsource their data to the cloud storage servers to reduce the management costs. While those data may contain sensitive personal information, the cloud servers cannot be fully trusted in protecting them. Encryption is a promising way to protect the confidentiality of the outsourced data, but it also introduces much difficulty to performing effective searches over encrypted information. Most existing works do not support efficient searches with complex query conditions, and care needs to be taken when using them because of the potential privacy leakages about the data owners to the data users or the cloud server. In this paper, using on line Personal Health Record (PHR) as a case study, we first show the necessity of search capability authorization that reduces the privacy exposure resulting from the search results, and establish a scalable framework for Authorized Private Keyword Search (APKS) over encrypted cloud data. We then propose two novel solutions for APKS based on a recent cryptographic primitive, Hierarchical Predicate Encryption (HPE). Our solutions enable efficient multi-dimensional keyword searches with range query, allow delegation and revocation of search capabilities. Moreover, we enhance the query privacy which hides users' query keywords against the server. We implement our scheme on a modern workstation, and experimental results demonstrate its suitability for practical usage. 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.