The Smart Grid, regarded as the next generation power grid, uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. In this article, we survey the literature till 2011 on the enabling technologies for the Smart Grid. We explore three major systems, namely the smart infrastructure system, the smart management system, and the smart protection system. We also propose possible future directions in each system. colorred{Specifically, for the smart infrastructure system, we explore the smart energy subsystem, the smart information subsystem, and the smart communication subsystem.} For the smart management system, we explore various management objectives, such as improving energy efficiency, profiling demand, maximizing utility, reducing cost, and controlling emission. We also explore various management methods to achieve these objectives. For the smart protection system, we explore various failure protection mechanisms which improve the reliability of the Smart Grid, and explore the security and privacy issues in the Smart Grid.

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Smart Grid — The New and Improved Power Grid: A Survey

Smart Grid - The New and Improved Power Grid:

A power grid is a complex system connecting electric power generators to consumers through power transmission and distribution networks across a large geographical area. System monitoring is necessary to ensure the reliable operation of power grids, and state estimation is used in system monitoring to best estimate the power grid state through analysis of meter measurements and power system models. Various techniques have been developed to detect and identify bad measurements, including interacting bad measurements introduced by arbitrary, nonrandom causes. At first glance, it seems that these techniques can also defeat malicious measurements injected by attackers.In this article, we expose an unknown vulnerability of existing bad measurement detection algorithms by presenting and analyzing a new class of attacks, called false data injection attacks, against state estimation in electric power grids. Under the assumption that the attacker can access the current power system configuration information and manipulate the measurements of meters at physically protected locations such as substations, such attacks can introduce arbitrary errors into certain state variables without being detected by existing algorithms. Moreover, we look at two scenarios, where the attacker is either constrained to specific meters or limited in the resources required to compromise meters. We show that the attacker can systematically and efficiently construct attack vectors in both scenarios to change the results of state estimation in arbitrary ways. We also extend these attacks to generalized false data injection attacks, which can further increase the impact by exploiting measurement errors typically tolerated in state estimation. We demonstrate the success of these attacks through simulation using IEEE test systems, and also discuss the practicality of these attacks and the real-world constraints that limit their effectiveness.

False data injection attacks against state estimation in electric power grids

A power grid is a complex system connecting electric power generators to consumers through power transmission and distribution networks across a large geographical area. System monitoring is necessary to ensure the reliable operation of power grids, and state estimation is used in system monitoring to best estimate the power grid state through analysis of meter measurements and power system models. Various techniques have been developed to detect and identify bad measurements, including the interacting bad measurements introduced by arbitrary, non-random causes. At first glance, it seems that these techniques can also defeat malicious measurements injected by attackers.In this paper, we present a new class of attacks, called false data injection attacks, against state estimation in electric power grids. We show that an attacker can exploit the configuration of a power system to launch such attacks to successfully introduce arbitrary errors into certain state variables while bypassing existing techniques for bad measurement detection. Moreover, we look at two realistic attack scenarios, in which the attacker is either constrained to some specific meters (due to the physical protection of the meters), or limited in the resources required to compromise meters. We show that the attacker can systematically and efficiently construct attack vectors in both scenarios, which can not only change the results of state estimation, but also modify the results in arbitrary ways. We demonstrate the success of these attacks through simulation using IEEE test systems. Our results indicate that security protection of the electric power grid must be revisited when there are potentially malicious attacks.

Cyber-physical systems are ubiquitous in power systems, transportation networks, industrial control processes, and critical infrastructures. These systems need to operate reliably in the face of unforeseen failures and external malicious attacks. In this paper: (i) we propose a mathematical framework for cyber-physical systems, attacks, and monitors; (ii) we characterize fundamental monitoring limitations from system-theoretic and graph-theoretic perspectives; and (ii) we design centralized and distributed attack detection and identification monitors. Finally, we validate our findings through compelling examples.

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Attack Detection and Identification in Cyber-Physical Systems

For multimedia traffic like VBR video, knowledge of the average loss probability is not sufficient to determine the impact of loss on the perceived visual quality and on the possible ways of improving it, for example by forward error correction (FEC) and error concealment. In this paper we investigate how the packet size distribution affects the packet loss process, the distribution of the number of packets lost in a block of packets and the related FEC performance. We present an exact mathematical model for the loss process of an MMPP+M/Er /1/K queue and compare the results of the model to simulations performed with various other packet size distributions (PSDs), among others, the measured PSD from an Internet backbone. We conclude that the packet size distribution affects the packet loss process and thus the efficiency of FEC. This conclusion is mainly valid in access networks where a single multimedia stream might affect the multiplexing behavior. The results show that analytical models of the PSD matching the first three moments (mean,variance and skewness) of the empirical PSD can be used to evaluate the performance of FEC in real networks. We also conclude that the exponential PSD, though it is not a worst case scenario, is a good approximation for the PSD of today's Internet to evaluate FEC performance.

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Packet size distribution: an aside?

Power system operators are looking to adopt and migrate to cloud technologies and third-party cloud services for customer facing and enterprise IT applications. Security and reliability are major barriers for adopting cloud technologies and services for power system operational applications. In this work we focus on the use of cloud computing for Contingency Analysis and propose an approach to obfuscate information regarding power flows and the presence of a contingency violation while allowing the operator to analyze contingencies with the needed accuracy in the cloud. Our empirical evaluation shows, that the errors introduced into power flows due to the obfuscation approach are small, and that the RMS errors introduced grow linearly with the magnitude of obfuscation.

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Confidentiality-preserving obfuscation for cloud-based power system contingency analysis

In this paper we have presented FADEC, authentication for dynamic electric vehicle charging. FADEC lets EVs establish symmetric keys with the RSUs and the utility company, and achieves fast signing, fast verification, fast hand-off authentication, and low communication overhead. Our simulations have shown that FADEC obtains very close to 1 report delivery ratio and small delay in both resource rich and constrained scenarios. Compared with ECDSA, FADEC reduces the data delivery delay by at most 97% and improves the delivery ratio by more than an order of magnitude. In the future we will perform a thorough security analysis of FADEC, as well as evaluate its performance under more complex traffic scenarios.

/pdf/fadec-fast-authentication-for-dynamic-electric-vehicle-ymmlqqhl3z.pdf

FADEC: Fast authentication for dynamic electric vehicle charging

We consider the interaction between mobile edge computing (MEC) resource management and wireless devices that offload computationally intensive tasks through shared wireless links to edge cloud servers, so as to minimize their completion times. We model the interaction between the devices and the operator that optimizes the allocation of the wireless and computing resources as a Stackelberg game. We show that a pure strategy Stackelberg equilibrium exists, and we provide an efficient algorithm for computing equilibrium allocations. Our simulation results show that joint optimization of the wireless and computing resources can provide a significant reduction of completion times at little increase in computational complexity compared to a system where resource allocation is not optimized.

https://dl.acm.org/doi/pdf/10.1145/3229556.3229559

Joint Allocation of Computing and Wireless Resources to Autonomous Devices in Mobile Edge Computing

Fixed and mobile network operators increasingly deploy managed content distribution networks (CDNs) with the objective of reducing the traffic on their transit links and to improve their customers’ quality of experience. As network operator managed CDNs (nCDNs) become commonplace, operators will likely provide common interfaces to interconnect their nCDNs for mutual benefit, as they do with peering today. In this paper, we consider the problem of using distributed algorithms for computing a cache allocation for nCDNs. We show that if every network operator aims to minimize its cost and bilateral payments are not allowed, then it may be impossible to compute a cache allocation. For the case when bilateral payments are possible, we propose two distributed algorithms, the aggregate value compensation and the object value compensation algorithms, which differ in terms of the level of parallelism they allow and in terms of the amount of information exchanged between nCDNs. We prove that the algorithms converge, and we propose a scheme to ensure ex-post individual rationality. Simulations performed on a real autonomous system-level network topology and synthetic topologies show that the algorithms have geometric rate of convergence, and scale well with the graphs’ density and the nCDN capacity.

Gyorgy Dan

Papers

Packet size distribution: an aside?

Confidentiality-preserving obfuscation for cloud-based power system contingency analysis

FADEC: Fast authentication for dynamic electric vehicle charging

Joint Allocation of Computing and Wireless Resources to Autonomous Devices in Mobile Edge Computing

Distributed Caching Algorithms for Interconnected Operator CDNs