In this paper, we aim to establish a holistic framework that integrates the cyber-physical layers of a cloud-enabled Internet of Controlled Things (IoCT) through the lens of contract theory. At the physical layer, the device uses cloud services to operate the system. The quality of cloud services is unknown to the device, and hence the device designs a menu of contracts to enable a reliable and incentive-compatible service. Based on the received contracts, the cloud service provider (SP) serves the device by determining its optimal cyber defense strategy. A contract-based FlipCloud game is used to assess the security risk and the cloud quality of service (QoS) under advanced persistent threats. The contract design approach creates a pricing mechanism for on-demand security as a service for cloud-enabled IoCT. By focusing on high and low QoS types of cloud SPs, we find that the contract design can be divided into two regimes (regimes I and II) with respect to the provided cloud QoS. Specifically, the physical devices whose optimal contracts are in regime I always request the best possible cloud security service. In contrast, the device only asks for a cloud security level that can stabilize the system when the optimal contracts lie in regime II. We illustrate the obtained results via case studies of a cloud-enabled smart home.
Pietro Danzi, Marko Angjelichinoski, Čedomir Stefanović, Petar Popovski
Residential microgrids (MGs) may host a large number of Distributed Energy Resources (DERs). The strategy that maximizes the revenue for each individual DER is the one in which the DER operates at capacity, injecting all available power into the grid. However, when the DER penetration is high and the consumption low, this strategy may lead to power surplus that causes voltage increase over recommended limits. In order to create incentives for the DER to operate below capacity, we propose a proportional-fairness control strategy in which (i) a subset of DERs decrease their own power output, sacrificing the individual revenue, and (ii) the DERs in the subset are dynamically selected based on the record of their control history. The trustworthy implementation of the scheme is carried out through a custom-designed blockchain mechanism that maintains a distributed database trusted by all DERs. In particular, the blockchain is used to stipulate and store a smart contract that enforces proportional fairness. The simulation results verify the potential of the proposed framework.
Gaoying Cui, Kun Shi, Yuchen Qin, Lin Liu · 6 authors
Based on the preliminary introduction of power demand response, this paper puts forward the problem in multi-level demand response reliable communication. Next, we analysis the principle of block chain technology, and then according to the characteristics of power demand response, the private block chain is chosen to solve the problem of mutual trust between users, load aggregators and power grids in multi-level demand response reliable communication. Smart contracts are used to solve the problem of demand response automation.
Adam Hahn, Rajveer Singh, Chen‐Ching Liu, Sijie Chen
Transactive energy paradigms will enable the exchange of energy from a distributed set of prosumers. While prosumers have access to distributed energy resources, these resources are intermittently available. There is a need for distributed markets to enable the exchange of energy in transactive environments, however, the large number of potential prosumers introduces challenges in the establishment of trust between prosumers. Markets for transactive environments create other challenges, such as establishing clearing prices for energy and exchanging money between prosumers. Blockchains provide a unique technology to address this distributed trust problem through the use of a distributed ledger, cryptocurrencies, and the execution of smart contracts. This paper introduces a smart contract that implements a transactive energy auction that operates without the need for a trusted entitys oversight. The auction mechanism implements a Vickrey second price auction, which guarantees bidders will submit honest bids. The contract is implemented on transactive agents on the WSU campus interacting with a 72kW PV array and the Ethereum blockchain. The contract is then used to execute auctions based on the energy from the the PV array and simulated building loads to demonstrate the auctions operations.
Smart grid enables two-way communications between operation centers and smart meters to collect power consumption and achieve demand response to improve flexibility, reliability, and efficiency of electricity system. However, power consumption data may contain users' privacy, e.g., activities, references, and habits. Many smart metering schemes have been proposed utilizing homomorphic encryption for users' privacy preservation. Unfortunately, some abnormality of smart meter reading, e.g., caused by electricity theft, cannot be discovered since data is encrypted. Meanwhile, operation centers could become curious in reality. To address the above issues, we propose a new privacy-preserving smart metering scheme for smart grid, which supports data aggregation, differential privacy, fault tolerance, and range-based filtering simultaneously. Specifically, we extend lifted ElGamal encryption to aggregate users' consumption reports at the gateway to reduce communication overhead, while supporting fault tolerance of malfunctioning smart meters effectively. We also leverage zero-knowledge range proof to filter abnormal measurements caused by electricity theft or false data injection attacks without exposing individual measurements. In addition, our scheme can resist differential attacks, by which the curious operation center can violate users' privacy through comparing two aggregations of the similar data set. Finally, we discuss the properties of the proposed scheme and evaluate its performance in terms of security and efficiency.
Smart grids equipped with bi-directional communication flow are expected to provide more sophisticated consumption monitoring and energy trading. However, the issues related to the security and privacy of consumption and trading data present serious challenges. In this paper we address the problem of providing transaction security in decentralized smart grid energy trading without reliance on trusted third parties. We have implemented a proof-of-concept for decentralized energy trading system using blockchain technology, multi-signatures, and anonymous encrypted messaging streams, enabling peers to anonymously negotiate energy prices and securely perform trading transactions. We conducted case studies to perform security analysis and performance evaluation within the context of the elicited security and privacy requirements.
Nicolas Gensollen, Vincent Gauthier, Monique Becker, Michel Marot
In the context of the smart grid, we propose in this paper an algorithm that forms coalitions of agents, called prosumers, that both produce and consume. It is designed to be used by aggregators that aim at selling aggregated surplus of production of the prosumers they control. We rely on real weather data sampled across stations of a given territory in order to simulate realistic production and consumption patterns for each prosumer. This enables us to capture geographical correlations among the agents while preserving the diversity due to different behaviors. As aggregators are bound to the market operator by a contract, they seek to maximize their offer while minimizing their risk. The proposed graph-based algorithm takes the underlying correlation structure of the agents into account and outputs coalitions with both high productivity and low variability. We show that the resulting diversified coalitions are able to generate higher benefits on a constrained energy market, and are more resilient to random failures of the agents.
This paper presents a comprehensive framework for the assessment of reliability and risk implications of post-fault Demand Response (DR) to provide capacity release in smart distribution networks. A direct load control (DLC) scheme is presented to efficiently disconnect DR customers with differentiated reliability levels. The cost of interrupted load is used as a proxy for the value of the differentiated reliability contracts for different customers to prioritize the disconnections. The framework tackles current distribution system operator (DSO)’s corrective actions such as network reconfiguration, emergency ratings and load shedding, also considering the physical payback effects from the DR customers’ reconnection. Sequential Monte Carlo simulation (SMCS) is used to quantify the risk borne by the DSO if contracting fewer DR customers than required by deterministic security standards. Numerical results demonstrate the benefits of the proposed DR scheme, when compared to the current DLC scheme applied from the local DSO. In addition, as a key point to boost the commercial implementation of such DR schemes, the results show how the required DR volume could be much lower than initially estimated when properly accounting for the actual risk of interruptions and for the possibility of deploying the asset emergency ratings. The findings of this work support the rationale of moving from the current prescriptive deterministic security standards to a probabilistic reliability assessment and planning approach applied to smart distribution networks, which also involves distributed energy resources such as post-contingency DR for network support.
The evolution of the traditional electricity infrastructure into smart grids promises more reliable and efficient power management, more energy aware consumers and inclusion of renewable sources for power generation. These fruitful promises are attracting initiatives by various nations all over the globe in various fields of academia. However, this evolution relies on the advances in the information technologies and communication technologies and thus is inevitably prone to various risks and threats. Even though many solutions have been proposed in the recent literature to overcome the security threats in smart grid networks, many issues still need to be addressed to make smart grids a reliable and efficient innovation. In this thesis, we first introduce the background, network architecture, security threats and the security requirements of smart grid networks. Our work focuses on the security aspects of Neighborhood Area Network (NAN) subsystems of smart grid. We present some of the prominent threats and attacks, specific to this subsystem, which violate the specific security goals requisite for its reliable operation. The proposed solutions and countermeasures for these security issues presented in the recent literature have been deeply reviewed to identify the promising solutions with respect to the specific security goals. Then we propose an improved VI dynamic key refreshment strategy for mesh security in the NAN and an authentication scheme based on software defined network (SDN) using dynamic one-way accumulators. The proposed dynamic key refreshment scheme can protect the mesh network system based on IEEE 802.11s standard from DoS attacks during the key refreshment whereby the intruder could launch the attack using the information from previous key refreshment cycle as proposed in the original key refreshment scheme. The use of simple hash based operation makes the scheme cost effective for the resource limited network devices. The proposed scheme also adds an enhancement to the sub-protocol of the original key refreshment scheme for enhanced security and reliability. The proposed SDN based authentication scheme employs one-way dynamic accumulators combined with zero-knowledge proofs for easy and cost efficient authentication process. The availability of the cross authentication among different NAN devices enables us to replicate the mesh network architecture. Using SDN as the backbone of the scheme helps us accommodate the advances of the upcoming wireless technologies where we can update the changes in the scheme conveniently. Our analysis shows that the proposed schemes can achieve the requisite authentication while withstanding multiple attacks and the balance between security and system performance is also achieved.
A cyber-physical system (CPS) is a sensing and communication platform that features tight integration and combination of computation, networking, and physical processes. In such a system, embedded computers and networks monitor and control the physical processes through a feedback loop, in which physical processes affect computations and vice versa. In recent years, CPS has caught much attention in many different aspects of research, such as security and privacy. In this dissertation, we focus on supporting security in CPS and its communication networks. First, we investigate the electric power system, which is an important CPS in modern society. as crucial and valuable infrastructure, the electric power system inevitably becomes the target of malicious users and attackers. In our work, we point out that the electric power system is vulnerable to potential cyber attacks, and we introduce a new type of attack model, in which an attack cannot be completely identified, even though its presence may be detected. to defend against such an attack, we present an efficient heuristic algorithm to narrow down the attack region, and then enumerate all feasible attack scenarios. Furthermore, based on the feasible attack scenarios, we design an optimization strategy to minimize the damage caused by the attack. Next, we study cognitive radio networks, which are a typical communication network in CPS in the areas of security and privacy. as for the security of cognitive radio networks, we point out that a prominent existing algorithm in cooperative spectrum sensing works poorly under a certain attack model. In defense of this attack, we present a modified combinatorial optimization algorithm that utilizes the branch-and-bound method in a decision tree to identify all possible false data efficiently. In regard to privacy in cognitive radio networks, we consider incentive-based cognitive radio transactions, where the primary users sell time slices of their licensed spectrum to secondary users in the network. There are two concerns in such a transaction. The first is the primary user's interest, and the second is the secondary user's privacy. to verify that the payment made by a secondary user is trustworthy, the primary user needs detailed spectrum utilization information from the secondary user. However, disclosing this detailed information compromises the secondary user's privacy. to solve this dilemma, we propose a privacy-preserving scheme by repeatedly using a commitment scheme and zero-knowledge proof scheme.
Addition of automated components such as smart meters, embedded microprocessors, and the two-ways communication systems from customers to operators to the power grid makes the power grid “smart”. One enhancement that requires the power grid to be “smart” is dynamic pricing. Implementation of dynamic pricing in the smart grid will require frequent transfer of energy consumption data from the consumers to the utilities. Privacy and security issues in transferring this energy consumption data is a widely studied topic. However, almost all of the studies done so far rely on a trusted third party, such as an electrical utilities or a load aggregator, that will have access to all of consumer data. This thesis proposes a Bitcoin-like decentralized model as a solution for secure information transfer within the smart grid, eliminating the presence of a central entity. Hence, a significant portion of this thesis is describes working principles of the Bitcoin network. This thesis specifically focuses on securing bidirectional data transfer between the gateway devices and the electrical utilities. How the information contained in the data is used is left upto the discretion of the consumers. Along with a proposal for a decentralized model, a broad discussion on security and privacy issues in the smart grid as well as cryptographic protocols required for a decentralized smart grid is also presented; a semi-detailed discussion on cryptographic protocols elliptic curve cryptography (ECC) and zero knowledge proof is included. Code for some of the useful cryptographic tools for a decentralized smart grid can be found in the appendix. A novel Bitcoin-like model developed to address security and privacy concerns of consumer data in the smart grid is the contribution of this thesis
El Hassan Et-Tolba, Mohammed Ouassaid, Mohamed Maâroufi
In this paper we give an adaptation of the standard FIPA Contract net Protocol for a multi-agent based smart home simulation. Smart home appliances are controlled by software agents that can communicate their needs and un/satisfaction to the Home Energy Manager Agent. The problem we encountered with FIPA specification is that each interacting agent is either initiator or participant during his life cycle. We propose a solution that allows agents to change their basic behavior and to be dynamical to their whole environment change depending on their requirements. The proposed solution is suitable to manage flexible household appliances such as advancing, delaying, or suspending their operation. Hence it leads to building energy efficiency and enhancing agents' coordination and collaboration for smart grid demand side management.
Demand Response (DR) is considered a promising approach to cope with the increasing variability in power grids due to the penetration of renewable energy sources. However, it still remains a challenge to manage the aggregation of a large number of heterogeneous loads to achieve a desired response, especially at a fast time scale. In this paper, we present a system-level modeling and control design approach for DR management in smart grids, by following a contract-based methodology. Given a set of flexible DR loads, capable of adapting their power consumption upon external requests, we find a strategy for an aggregator to optimally track a DR requirement by combining the individual contributions of the DR components. In our framework, both the design requirements and the DR components' interfaces are specified by assume-guarantee contracts expressed using mixed-integer linear constraints. Contracts are used to formulate an optimal control problem, which is solved repeatedly over time, in a receding horizon fashion. We illustrate the effectiveness of our methodology for a set of DR components including fans and pumps, showing that it enables modular development of non-disruptive DR control schemes.
Marilena Minou, George D. Stamoulis, George Thanos, Vikas Chandan
Demand Response (DR) programs constitute an efficient way to alleviate the problem of peak demand in smart grids. While the potential impact of DR can be significant, its success essentially depends on the participation and responsiveness of consumers. In this paper, we focus on the design of effective contract-based automated DR programs by energy providers that own supportive generators to meet excess demand and employ DR as a means to avoid their costly activation. We derive a theoretically justified formula for the amount of incentives that should be offered to a consumer to accept such a contract. Based on this, we introduce an algorithm for selecting the optimal set of consumers in terms of total incentives. This algorithm is employed under two different policies for restricting (in a different way) the discomfort caused to consumers. We evaluate these policies using real-world data and present interesting insights about the efficient selection of consumers to be targeted for DR and the total amount of incentives offered to them by the provider.
The editorial board announced this article has been retracted on July 19, 2016. If you have any further question, please contact us at: cis@ccsenet.org
Lillian J. Ratliff, Roy Dong, Henrik Ohlsson, Álvaro A. Cárdenas · 5 authors
In the electricity grid, networked sensors which record and transmit increasingly high-granularity data are being deployed. In such a setting, privacy concerns are a natural consideration. In order to obtain the consumer's valuation of privacy, we design a screening mechanism consisting of a menu of contracts offered to the energy consumer with varying guarantees of privacy. The screening process is a means to segment customers. Finally, we design insurance contracts using the probability of a privacy breach to be offered by third-party insurance companies.
Fine-grained energy usage data made available by recent advancement of smart grid technologies benefit not only electricity utility companies but also customers. Nowadays customers can utilize various services by sharing their own energy usage data. At the same time, such utilization and sharing of electricity usage data with a variety of third party service providers may cause privacy concerns. In this paper, we discuss a privacy preserving mechanism for customers' sharing of energy usage data with third parties using non-interactive zero-knowledge proof systems. Under our scheme, a customer can, for each data sharing and disclosure, add noise to her electricity usage data without entirely losing verifiability of data authenticity, thereby retaining utility of data at third parties even for billing or accounting purposes.
Particularly with the rise of intermittent renewable energy sources, balancing electricity consumption and production is the core challenge of smart grids. The most important drawback of existing approaches is that controlling loads or producers is typically heavily regulated by contracts or laws. These real-world constraints significantly increase the complexity associated with achieving the aforementioned balance. In this paper, we propose a planning algorithm for smart grids that respects contractual or legal constraints while balancing power consumption and production. Additionally, our planning approach manages energy producers as well as consumers. Thus, it achieves the balance in the grid by controlling a combination of producers and consumers.