Fingerprinting Vulnerabilities in Intelligent Electronic Device Firmware

Modern smart grid deployments heavily rely on the advanced capabilities that Intelligent Electronic Devices (IEDs) provide. Furthermore, these devices firmware often contain critical vulnerabilities that if exploited could cause large impacts on national economic security, and national safety. As such, a scalable domain specific approach is required in order to assess the security of IED firmware. In order to resolve this lack of an appropriate methodology, we present a scalable vulnerable function identification framework. It is specifically designed to analyze IED firmware and binaries that employ the ARM CPU architecture. Its core functionality revolves around a multi-stage detection methodology that is specifically designed to resolve the lack of specialization that limits other general-purpose approaches. This is achieved by compiling an extensive database of IED specific vulnerabilities and domain specific firmware that is evaluated. Its analysis approach is composed of three stages that leverage function syntactic, semantic, structural and statistical features in order to identify vulnerabilities. As such it (i) first filters out dissimilar functions based on a group of heterogeneous features, (ii) it then further filters out dissimilar functions based on their execution paths, and (iii) it finally identifies candidate functions based on fuzzy graph matching . In order to validate our methodologies capabilities, it is implemented as a binary analysis framework entitled BinArm. The resulting algorithm is then put through a rigorous set of evaluations that demonstrate its capabilities. These include the capability to identify vulnerabilities within a given IED firmware image with a total accuracy of 0.92

Network and System Management using IEC 62351-7 in IEC 61850 Substations: Design and Implementation

Substations are a prime target for threat agents aiming to disrupt the power grid’s operation. With the advent of the smart grid, the power infrastructure is increasingly being coupled with an Information and Communication Technologies (ICT) infrastructure needed to manage it, exposing it to potential cyberattacks. In order to secure the smart grid, the IEC 62351 specifies how to provide cybersecurity to such an environment. Among its specifications, IEC 62351-7 states to use Network and System Management (NSM) to monitor and manage the operation of power systems. In this research, we aim to design, implement, and study NSM in a digital substation as per the specifications of IEC 62351-7. The substation is one that conforms to the IEC 61850 standard, which defines how to design a substation leveraging ICT. Our contributions are as follows. We contribute to the design and implementation of NSM in a smart grid security co-simulation testbed. We design a methodology to elaborate cyberattacks targeting IEC 61850 substations specifically. We elaborate detection algorithms that leverage the NSM Data Objects (NSM DOs) of IEC 62351- 7 to detect the attacks designed using our method. We validate these experimentally using our testbed. From this work, we can provide an initial assessment of NSM within the context of digital substations