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Publication# Cybersecurity Solutions for Active Power Distribution Networks

Abstract

An active distribution network (ADN) is an electrical-power distribution network that implements a real-time monitoring and control of the electrical resources and the grid. Effective monitoring and control is realised by deploying a large number of sensing and actuating devices and a communication network to facilitates the two-way transfer of data. The reliance of ADN operations on a large number of electronic devices and on communication networks poses a challenge in protecting the system against cyber-attacks. Identifying these challenges and commissioning appropriate solutions is of utmost importance to realize the full potential of a smart grid that seamlessly integrates distributed generation, such as renewable energy sources. As a first step, we perform a thorough threat analysis of a typical ADN. We identify potential threats against field devices, the communication infrastructure and servers at control centers. We also propose a check-list of security solutions and best practices that guarantee a distribution network's resilient operation in the presence of malicious attackers, natural disasters, and other unintended failures that could potentially lead to islanded communication zone. For the next step, we investigate the security of MPLS-TP, a technology that is mainly used for long-distance inter-domain communication in smart grid. We find that an MPLS-TP implementation in Cisco IOS has serious security vulnerabilities in two of its protocols, BFD and PSC. These two protocols control protection-switching features in MPLS-TP. In our test-bed, we demonstrate that an attacker who has physical access to the network can exploit the vulnerabilities in order to inject forged BFD or PSC messages that affect the network's availability. Third, we consider multicast source authentication for synchrophasor data communication in grid monitoring systems (GMS). Ensuring source authentication without violating the stringent real-time requirement of GMS is challenging. Through an extensive review of existing schemes, we identified a set of schemes that satisfy some desirable requirements for GMS. The identified schemes are ECDSA, TV-HORS and Incomplete- key-set. We experimentally compared these schemes using computation, communication and key management overheads as performance metrics. A tweak in ECDSA's implementation to make it use pre-generated tokens to generate signatures significantly improves the computation overhead of ECDSA, making it the preferred scheme for GMS. This finding is contrary to the generally accepted view that asymmetric cryptography is inapplicable for real-time systems. Finally, we studied a planning problem that arises when a utility wants to roll out a software patch that requires rebooting to all PMUs while maintaining system observability. The problem we address is how to find a partitioning of the set of the deployed PMUs into as few subsets as possible such that all the PMUs in one subset can be patched in one round while all the PMUs in the other subsets provide full observability. We show that the problem is NP-complete in the general case and and formulated it as binary integer linear programming (BILP) problem. We have also provided an heuristic algorithm to find an approximate solution. Furthermore, we have identified a special case of the problem where the grid is a tree and provided a polynomial-time algorithm that finds an optimal patching plan that requires only two rounds to patch the PMUs.

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A smart grid is an electrical grid which includes a variety of operation and energy measures including:
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This thesis is concerned with problems in decentralized communication in large networks. Namely, we address the problems of joint rate allocation and transmission of data sources measured at nodes, and of controlling the multiple access of sources to a shared medium. In our study, we consider in particular the important case of a sensor network measuring correlated data. In the first part of this thesis, we consider the problem of correlated data gathering by a network with a sink node and a tree communication structure, where the goal is to minimize the total transmission cost of transporting the information collected by the nodes, to the sink node. Two coding strategies are analyzed: a Slepian-Wolf model where optimal coding is complex and transmission optimization is simple, and a joint entropy coding model with explicit communication where coding is simple and transmission optimization is difficult. This problem requires a joint optimization of the rate allocation at the nodes and of the transmission structure. For the Slepian-Wolf setting, we derive a closed form solution and an efficient distributed approximation algorithm with a good performance. We generalize our results to the case of multiple sinks. For the explicit communication case, we prove that building an optimal data gathering tree is NP-complete and we propose various distributed approximation algorithms. We compare asymptotically, for dense networks, the total costs associated with Slepian-Wolf coding and explicit communication, by finding their corresponding scaling laws and analyzing the ratio of their respective costs. We argue that, for large networks and under certain conditions on the correlation structure, "intelligent", but more complex Slepian-Wolf coding provides unbounded gains over the widely used straightforward approach of opportunistic aggregation and compression by explicit communication. In the second part of this thesis, we consider a queuing problem in which the service rate of a queue is a function of a partially observed Markov chain, and in which the arrivals are controlled based on those partial observations so as to keep the system in a desirable mildly unstable regime. The optimal controller for this problem satisfies a separation property: we first compute a probability measure on the state space of the chain, namely the information state, then use this measure as the new state based on which to make control decisions. We give a formal description of the system considered and of its dynamics, we formalize and solve an optimal control problem, and we show numerical simulations to illustrate with concrete examples properties of the optimal control law. We show how the ergodic behavior of our queuing model is characterized by an invariant measure over all possible information states, and we construct that measure. Our results may be applied for designing efficient and stable algorithms for medium access control in multiple accessed systems, in particular for sensor networks.

Our main motivation is to design more user-friendly security protocols. Indeed, if the use of the protocol is tedious, most users will not behave correctly and, consequently, security issues occur. An example is the actual behavior of a user in front of an SSH certificate validation: while this task is of utmost importance, about 99% of SSH users accept the received certificate without checking it. Designing more user-friendly protocols may be difficult since the security should not decrease at the same time. Interestingly, insecure channels coexist with channels ensuring authentication. In practice, these latters may be used for a string comparison or a string copy, e.g., by voice over IP spelling. The shorter the authenticated string is, the less human interaction the protocol requires, and the more user-friendly the protocol is. This leads to the notion of SAS-based cryptography, where SAS stands for Short Authenticated String. In the first part of this thesis, we analyze and propose optimal SAS-based message authentication protocols. By using these protocols, we show how to construct optimal SAS-based authenticated key agreements. Such a protocol enables any group of users to agree on a shared secret key. SAS-based cryptography requires no pre-shared key, no trusted third party, and no public-key infrastructure. However, it requires the user to exchange a short SAS, e.g., five decimal digits. By using the just agreed secret key, the group can now achieve a secure communication based on symmetric cryptography. SAS-based authentication protocols are often used to authenticate the protocol messages of a key agreement. Hence, each new secure communication requires the interaction of the users to agree on the SAS. A solution to reduce the user interaction is to use digital signature schemes. Indeed, in a setup phase, the users can use a SAS-based authentication protocol to exchange long-term verification keys. Then, using digital signatures, users are able to run several key agreements and the authentication of protocol messages is done by digital signatures. In the case where no authenticated channel is available, but a public-key infrastructure is in place, the SAS-based setup phase is avoided since verification keys are already authenticated by the infrastructure. In the second part of this thesis, we also study two problems related to digital signatures: (1) the insecurity of digital signature schemes which use weak hash functions and (2) the privacy issues from signed documents. Digital signatures are often proven to be secure in the random oracle model. The role of random oracles is to model ideal hash functions. However, real hash functions deviate more and more from this idealization. Indeed, weaknesses on hash functions have already been discovered and we are expecting new ones. A question is how to fix the existing signature constructions based on these weak hash functions. In this thesis, we first try to find a better way to model weak hash function. Then, we propose a (randomized) pre-processing to the input message which transforms any weak signature implementation into a strong signature scheme. There remains one drawback due to the randomization. Indeed, the random coins must be sent and thus the signature enlarges. We also propose a method to avoid the increase in signature length by reusing signing coins. Digital signatures may also lead to privacy issues. Indeed, given a message and its signature, anyone can publish the pair which will confirm the authenticity of the message. In certain applications, like in electronic passports (e-passports), publishing the authenticated data leads to serious privacy issues. In this thesis, we define the required security properties in order to protect the data privacy, especially in the case of e-passport verification. The main idea consists for the e-passport to keep the signature secret. The e-passport should only prove that it knows a valid signature instead of revealing it. We propose a new primitive, called Offline Non-Transferable Authentication Protocol (ONTAP), as well as efficient implementations that are compatible with the e-passport standard signature schemes.

Marguerite Marie Nathalie Delcourt

This work focuses on the security of critical infrastructures against time-synchronization attacks (TSA). A TSA can impact any network that relies on the dynamic analysis of data, by altering the time synchronization between its nodes. Such attacked networks can start failing. Some TSAs are thwarted by cyber-security tools such as authentication and confidentiality algorithms. However, such tools cannot counter TSAs that are implemented physically. Such TSAs are undetectable but they may be detected if they lead to non-plausible observations. The identification of TSAs requires in-depth knowledge of the system's operation.We focus on TSAs in two settings. First, we consider smart grids. Their control and operation require the timely knowledge of the system state, which is inferred from an estimate computed from measurements. We consider phasor measurements taken from phasor measurement units (PMUs). However, they require a precise time synchronization, which is a weakness as existing synchronization methods are vulnerable to attacks. We aim to assess the vulnerability of the synchrophasor-based state estimation of a system, by exploring the feasibility and detectability of TSAs on PMUs. A widespread technique to make the state estimation more robust is to couple it with a bad-data detection (BDD) scheme. However, it is known that false data injection attacks and TSAs can impact the state estimation without being detected by the BDD algorithms. We present practical attack strategies for undetectable TSAs and novel vulnerability conditions. One of them is a static condition that does not depend on the measurement values. We propose a security requirement that prevents it and a greedy offline algorithm that enforces it. If this requirement is satisfied, the grid may still be attacked, although we reason that it is unlikely. We identify two sufficient and necessary vulnerability conditions which depend on the measurement values. For each, we provide a metric that shows the distance between the observed and vulnerability conditions. Enforcing our requirement requires increasing the amount of measurement points of the grid. We investigate the benefits of utilizing the three-phase model instead of the direct-sequence model for security. We show that if the power system is unbalanced, then the use of the three-phase model enables to detect attacks that are undetectable if the direct-sequence model is used. Numerical results from simulations with real load profiles from the Lausanne grid, confirm our findings. Second, we consider sensor networks for passive-source localization. We focus on the localization of a passive source from time difference of arrival (TDOA) measurements. Such measurements are highly sensitive to time-synchronization offsets. We first illustrate that TSAs can affect the localization and we show that residual analysis does not enable the detection and identification of TSAs. Second, we propose a two-step TDOA-localization technique that is robust against TSAs. It uses a known source to define a weight for each pair of sensors, reflecting the confidence in their synchronization. We then use the weighted least-squares estimator with the new weights and the TDOA measurements received from the unknown source. Our method either identifies the network as being too corrupt, or gives a corrected estimate of the unknown position along with a confidence metric. Numerical results illustrate the performance of our technique.