Secure Communications in the Smart Grid

University of Nevada, Reno Secure Communications in the Smart Grid A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering by Hayreddin Ceker Dr. Mehmet H. Gunes/Thesis Advisor Aug 2013 Copyright by Hayreddin Ceker 2013 UNIVERSITY OF NEVADA RENO THE GRADUATE SCHOOL We recommend that the thesis prepared under our supervision by HAYREDDIN CEKER entitled Secure Communications in the Smart Grid be accepted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Mehmet H Gunes, Ph.D., Advisor Murat Yuksel, Ph.D., Committee Member Yantao Shen, Ph.D., Graduate School Representative Marsha H. Read, Ph.D., Dean, Graduate School August, 2013 i Secure Communications in the Smart Grid Hayreddin Ceker University of Nevada, Reno, 2013 Supervisor: Mehmet Hadi Gunes Abstract Smart grid has diverse stake holders that often require varying levels of access to grid state and measurements. At the distribution level (i.e., MAN), smart grid provides two way communication between households and utilities. At the transmission level (i.e., WAN), multiple organizations need to share the transmission lines and cooperate with participants in their region. Efficient and reliable operation of the grid depends on accurate state measurements and secure data transfer to operation centers. These tasks are complicated by the vast amount of data from diverse sources that are owned by multiple entities that impose physical, economic, market, and political constraints on the data sharing. However, to protect against grid-wide failures and defend against coordinated attacks, power grid operators need to increase data sharing. In this thesis, we propose secure communication and computation services for smart grid to transform the current \closed communication channel" to an \open communication channel". In order to ensure the privacy and integrity of communi- ii cating parties at the distribution level, we propose to utilize the smart meters as a gateway between intra-network (i.e., HAN) and inter-network (i.e., WAN) communications, and manage incoming and outgoing traffic and mediate household devices based on the instructions from the electric utility or contracted service providers. Moreover, third parties such as service providers can monitor and manage the contracted customers by using the existing communication infrastructure. To enhance data sharing between operators at the transmission level, we propose an open communication architecture that utilizes blind processing service, which allows information exchange between dedicated system components with protection mechanisms against everyone else. Traditionally, security mechanisms are deployed to protect the transmission channel and the computation environment from third parties based on security requirements of the data. Our goal with blind processing is to estab- lish a secure communication channel between trusted processes, which are concealed from the rest of the system including the root processes (and hence system administrators). Blind processing particularly tries to eliminate interference from the root processes, the system administrators, and careless/malicious users internal or exter- nal to the system at all stages of the communication and computation. Shielding the information prevents competitors from accessing the sensitive data while providing a complete picture of the whole grid in computations at operation centers. iii Acknowledgments I would like to express my sincere gratitude for my adviser Dr. Mehmet H. Gunes, whose guidance, inspiration, understanding, patience, and encouragement contributed considerably to my graduate experience. I would like to thank Dr. Murat Yuksel and Dr. Yantao Shen for agreeing to be on my thesis committee despite their extremely busy schedule. I would like to thank my colleagues and friends at the Computer Networking Laboratory for brightening my days and making my time as a graduate student en- joyable. I would also like to thank my family for the support they provided me through my entire life. Hayreddin Ceker University of Nevada, Reno Aug 2013 iv Contents Abstract i Acknowledgments iii List of Figures vii Chapter 1 Introduction 1 1.1 Objective . .4 1.2 Contributions . .6 Chapter 2 Background 8 2.1 Transmission Level . .8 2.2 Distribution Level . 13 2.2.1 Smart Meter . 14 2.2.2 Electric Utility . 16 2.2.3 Service Providers . 16 2.2.4 Electrical Household Devices . 17 2.3 Cryptography . 17 2.3.1 Public Key Infrastructure (PKI) . 18 2.3.2 Symmetric Key Encryption . 19 v 2.3.3 Hash Functions . 20 2.4 Trusted Computing . 20 Chapter 3 Power Grid Communications 23 3.1 Wide Area Network (WAN) Communications . 23 3.1.1 Inter-ISO . 24 3.2 Metropolitan Area Network (MAN) Communications . 26 3.2.1 Electric Utility{Smart Meter . 27 3.2.2 Service Provider{Smart Meter . 29 3.3 Home Area Network (HAN) Communications . 29 3.3.1 Smart Meter{Device . 30 3.3.2 Owner{Device . 31 Chapter 4 Blind Processing for Open Communications 32 4.1 Prototype . 33 4.2 System Sub-Structures . 34 4.3 Trusted Platform Module . 36 4.4 Security Kernel . 38 4.5 Chain of Trust . 41 4.6 Trusted Software Stack: System Domain . 42 4.7 Virtualization . 45 4.8 Trusted Software Stack: User Domain . 48 4.9 Trusted Platform Module Dependencies . 51 4.10 Privacy Assurance . 52 4.11 Remote System Authentication . 56 4.12 Communication Protocol . 57 vi 4.13 Integrity Assurance . 58 Chapter 5 Evaluations of Performance Impact 62 Chapter 6 Attack Vectors and Vulnerabilities 65 6.1 Man-in-the-Middle . 66 6.2 Session Injection . 67 6.3 Cold Boot, Physical and Side Channel Attacks . 68 Chapter 7 Related Work 70 7.1 Transmission Level . 70 7.2 Distribution Level . 72 Chapter 8 Conclusions and Future Work 75 Bibliography 77 vii List of Figures 1.1 Smart Grid Conceptual Model for Data Communication by NIST (mod- ified from [16]) . .2 2.1 US Electric Power Markets (courtesy of Federal Energy Regulatory Commission). .9 2.2 Current structure with communication links . 11 2.3 Public Key Infrastructure . 19 3.1 Metropolitan Area Network (Distribution Level) . 27 3.2 Home Area Network . 30 4.1 Intra- vs Inter-domain communication . 35 4.2 A Trusted Platform Module (TPM) chip . 37 4.3 TPM memory hirearchy . 38 4.4 Secure system model . 43 4.5 Chain of trusted boot process with corresponding PCRs [70]. 44 4.6 TPM dependencies. 51 4.7 Dependencies . 54 4.8 CA Hierarchy . 59 viii 5.1 Timing Overhead . 63 5.2 Data Seal Timing . 64 1 Chapter 1 Introduction Automated management of large-scale infrastructure systems is a challenging problem faced by scientists and engineers in a wide variety of applications including: power grids, transportation networks, and telecommunication networks. The problem re- quires (i) data collection, (ii) secure data transfer to processing centers, (iii) efficient data processing, and (iv) timely decision making and control actions. These tasks are complicated by the vast amount of data, the distributed sources, and the need for efficient data communication. Such large-scale systems are often subdivided into separately owned subsystems which impose physical, economic, market, and political constraints on data transfer. These challenges are emphasized for large-scale infrastructure systems where seamless operation is crucial. In addition, potential coordinated attacks on these systems require the infrastructures to be more automated and self-healing [63]. Power grid is one of the infrastructures crucial for public health, safety and welfare. Proliferation of renewable energy-based electric power production, increased use of electric vehicles and upgrading the aging electricity infrastructure for more 2 Operations Marketsrkets Service Provider Bulk Generation Customer DistributionDistri Transmission Electric Flows Secure Communication Domain Figure 1.1: Smart Grid Conceptual Model for Data Communication by NIST (mod- ified from [16]) efficient grid operations are only viable with smarter monitoring, control and consumption of the electrical energy. It is not possible to achieve the nationwide visions for a smarter grid, if the current control, monitoring and consumption practices are not significantly changed in high voltage transmission and medium/low voltage distribution level. A smarter grid equipped with intelligent electronic devices cannot survive if its communications infrastructure is insecure and vulnerable to cyber attacks [10, 46]. Smart grid consists of multiple entities in different domains as shown in Figure 1.1. A key factor of the power infrastructure is its multi-owner property at the transmission level of high-voltage interconnected grids. The power transmission networks 3 are physically inter-connected; however, the electrical and financial energy markets are governed by Independent System Operators (ISOs) in different markets. Each ISO monitors (i.e., operations domain) and controls (i.e., service provider domain) its own region and only provides power flow information on tie-lines between other transmission regions. The existing cyber-architecture in the power grid provides lim- ited information exchange among domain owners and ISOs due to energy market constraints and trust boundaries. This \closed" communication architecture leave the power grid vulnerable to cascading events and makes it difficult to detect potential problems and can lead to catastrophic failures [69]. As emphasized in the North American Electric Reliability Council (NERC) report [31], one of the primary weak- nesses in need of attention is \communications within the ISO and with its neighboring control areas and reliability coordinators". However, such inter- and intra-ISO communication capabilities necessitate mechanisms to securely and efficiently exchange sensitive data for system modeling and monitoring. The implementation of smart grid applications is much more prevalent at the distribution level of medium/low voltage. Distribution applications deal with the utilities and the customers (e.g., residential, industrial, and governmental entities) at a local level. Research at the distribution level primarily focuses on the use of smart meters that can have two-way communications with the utility.

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