Attack Graphs and Scenario Driven Wireless Computer Network Defense

Attack Graphs and Scenario Driven Wireless Computer Network Defense

Peter J. Hawrylak, George Louthan, Jeremy Daily, John Hal, Mauricio Papa
DOI: 10.4018/978-1-4666-0104-8.ch016
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Abstract

This chapter describes how to use attack graphs to evaluate the security vulnerabilities of an embedded computer network and provides example cases of this technique. Attack graphs are powerful tools available to system administrators to identify and manage vulnerabilities. Attack graphs describe the steps an adversary could take to reach a desired goal and can be analyzed to quantify risk. The systems investigated in this chapter are embedded systems that span hardware, software, and network communication. The example cases studied will be (1) radio frequency identification (RFID), (2) vehicle networks, and (3) the Smart Grid (the next generation power and distribution network in the USA).
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Introduction

Embedded systems are systems composed of a microprocessor embedded within a larger product other than a typical desktop or laptop computer and are becoming pervasive. Embedded systems include sensors and actuators, which are controlled and monitored by microprocessors. Some examples of embedded systems are the engine control module found in vehicles, a washing machine, a cell phone, and a thermostat. Often an embedded system includes some form of network connection (e.g. RS-232, USB, CAN, RFID, or Wi-Fi) to connect to other devices. With the proliferation and networking of embedded systems, the security of these systems is of critical concern.

For embedded systems, security is addressed component by component in isolation. The goal is to secure a given component and then to do this for all components in a system. This technique may have worked in the past when most embedded systems were designed entirely from scratch or in-house components. However, today’s embedded systems often incorporate third party intellectual property (IP) blocks that cannot always be verified or modified to fix security issues. The system-on-a-chip (SOC) design philosophy (Keating & Bricaud, 2002), built around reuse of IP blocks, requires a new approach to securing an embedded system.

Many embedded systems blend the physical (or continuous) world and the digital (or discrete) worlds. Such systems are often termed cyber-physical systems. The electronics in an automobile is one example of this blending of physical processes. For example, oxygen sensors provide analog signals to a digital control system that adjusts fuel mixture in a way that reduces hydrocarbon emissions. Because of this cyber-physical linkage, an attack may now be introduced into the system through both physical and cyber (software, hardware, and communications network) components. One example of such an attack is the Stuxnet worm, which targeted nuclear centrifuges using the motor to cause a catastrophic failure (centrifuge will break apart) (Broad & Sanger, 2010). Another example of cyber-physical attack is exploiting the electronic communication bus present on all modern automobiles to take control of physical variables or components (e.g. speed or door locks) (Koscher, et. al., 2010). These kinds of blended attacks force a sea-change in the approach adopted by conventional IT security tools and methods. Security must be evaluated from the software, hardware, network, and physical viewpoints.

Attack graphs are one method to model and describe attacks. This chapter will describe how to use attack graphs to evaluate the security vulnerabilities of an embedded computer network and provide example cases of this technique. The systems investigated in this chapter are embedded systems that span hardware, software, and network communication domains. The example cases studied will be (1) radio frequency identification (RFID), (2) vehicle networking, and (3) the smart grid (the next generation power and distribution network in the USA). First, a definition and explanation of attack graphs will be provided. Then, the methods of using these attack graphs to identify vulnerabilities and improve system security will be presented. Finally, the three example cases will be presented in separate sections. Each example case will be defined and attack graphs will be generated to enumerate vulnerabilities in that system.

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