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Smart Grids integrate currently isolated power and communications networks, while introducing several new technologies on the hardware and software sides. One of the most important ingredients is the potential for demand-response programs, which offer the possibility of sending instructions to consumers to adapt their power consumption over a certain period of time. However, high-frequency data collection exposes consumers’ usage behaviors, leading to security and privacy challenges for Smart Grids.
In this thesis, three cryptographic schemes are constructed for different demand-response programs. In the mandatory incentive-based demand-response program, privacy preservation depends on the power consumption of consumers. An anonymous authentication scheme is constructed for overload auditing and privacy preservation. Consumers’ identities are anonymous during normal operation. The operation center defines an acceptable consumption threshold at times of power shortage. Consumers must follow the instruction and curtail their power consumption to meet the threshold. If they do so, the consumers keep their anonymity, while disobedient consumers, whose power consumption exceeds the threshold, can be identified. Security analysis demonstrates that the constructed anonymous authentication scheme is secure in a random oracle model. In the voluntary incentivebased demand-response program, consumers are categorized as either obedient or disobedient consumers according to their consumption curtailment. Consumers utilize a homomorphic encryption algorithm to encrypt their usage and report the ciphertexts to the operation center periodically. At a time of grid instability, the obedient consumers reduce their consumption and prove their curtailment by using a range proof. Both the usage reports and the proofs from obedient consumers concerning their consumption are reported without leaking private information. In order to achieve the real-time requirement, a security model is proposed and a batch verification algorithm is constructed, which is proved to be secure in the defined oracle model. Apart from reward and penalty detection in demand-response programs, theft detection is also an important requirement in Smart Grids. In order to achieve theft detection, this thesis employs the dynamic k-times anonymous authentication and blind signatures to create an efficient theft detection mechanism in the prepaid card system, where consumers pay for their consumption in advance and obtain credentials. A consumer sends the credentials anonymously and obtains corresponding credentials during times of consumption. If a thief tries to send reused credentials to steal electricity, his anonymity will be revoked. Finally, this thesis proves that the proposed mechanism finds the real identities of power thieves, without sacrificing the privacy of honest consumers under the random oracle model.
In smart grids, managing and controlling power operations are supported by information
and communication technology (ICT) and supervisory control and data acquisition (SCADA) systems. The increasing adoption of new ICT assets in smart grids is making smart grids vulnerable to cyber threats, as well as raising numerous concerns about the adequacy of current security approaches.
As a single act of penetration is often not sufficient for an attacker to achieve his/her goal, multistage cyber attacks may occur. Due to the interdependence between the power grid and the communication network, a multistage cyber attack not only affects the cyber system but impacts the physical system. This thesis investigates an application-oriented stochastic game-theoretic cyber threat assessment framework, which is strongly related to the information security risk management process as standardized in ISO/IEC 27005. The proposed cyber threat assessment framework seeks to address the specific challenges (e.g., dynamic changing attack scenarios and understanding cascading effects) when performing threat assessments for multistage cyber attacks in smart grid communication networks.
The thesis looks at the stochastic and dynamic nature of multistage cyber attacks in smart grid use cases and develops a stochastic game-theoretic model to capture the interactions of the attacker and the defender in multistage attack scenarios. To provide a flexible and practical payoff formulation for the designed stochastic game-theoretic model, this thesis presents a mathematical analysis of cascading failure propagation (including both interdependency cascading failure propagation and node overloading cascading failure propagation) in smart grids. In addition, the thesis quantifies the characterizations of disruptive effects of cyber attacks on physical power grids.
Furthermore, this thesis discusses, in detail, the ingredients of the developed stochastic game-theoretic model and presents the implementation steps of the investigated stochastic game-theoretic cyber threat assessment framework. An application of the proposed cyber threat assessment framework for evaluating a demonstrated multistage cyber attack scenario in smart grids is shown. The cyber threat assessment framework can be integrated into an existing risk management process, such as ISO 27000, or applied as a standalone threat assessment process in smart grid use cases.