For energy providers, pipelines spanning many miles are necessary to transport resources, but having employees drive or walk along pipelines to inspect them is time-consuming, and visual inspection can miss internal defects within pipes. Using networked sensors for remote monitoring can be more effective and efficient, but increased numbers of access points provide more opportunities for network intrusions—including access to control systems. Cyberattack frequency and severity against utilities are rising every year, and U.S. energy is among the most targeted sectors of critical infrastructure [1; 2]. Draper has expertise in a range of technologies that could enable the functionality of a networked energy distribution network while ensuring its security.

To monitor refineries for corrosion remotely, Draper developed WiSense, a low-cost and low-power sensor array. Magnetic-field sensors sit on ferrous metal pipelines to measure local changes indicating missing metal and wirelessly transmit that data to a monitoring facility. To process the sensor data automatically, Draper developed algorithms, which use 3D gradient maps to identify and track corrosion growth. Designed to operate for 10 years on a single battery, WiSense is an extensible model for monitoring interconnected energy distribution network nodes.

Another way to increase efficiency of large-scale connected systems is automation of operations. Draper adapted its Timeliner user interface language and execution environment for use by utilities. Timeliner is a modular, extensible system that allows scripts to be developed and executed in virtually any systems environment and can be applied to control a variety of target systems. Timeliner executes scripted activities on the International Space Station’s real-time command and control and payload control computers.

Draper designed the Timeliner language specifically to allow easy definition of activities, dependencies and constraints that provide monitoring, sequencing and process control of complex systems. The Timeliner sequence control, including multiple parallel automated sequencing, may be preprogrammed, compiled from Timeliner scripts, or it may consist of real-time, interactive inputs from system operators.

To identify and repair vulnerabilities in others’ code in legacy systems or during software development, Draper engineers use artificial intelligence to automate most of the time-consuming process. Deep neural networks and machine-learning algorithms trained on hundreds of billions of lines of open-source training code deliver the speed of a computer and the pattern-recognition abilities of a human programmer. Draper’s engineers develop custom tools employing advanced static and dynamic analysis techniques for detecting vulnerabilities in systems.

To secure communications among networked devices from interception and spoofing, Draper could apply the encryption and authentication approach it used in developing the Secure micro Digital Data Link (SmDDL) to protect communications between aerial drones and ground controllers. Because Draper can include encrypted security as part of the design, it becomes an integrated facet of the whole system—creating more reliable security from the start.

Draper’s range of engineering discipline expertise and system-level approach to designing networks can help utilities maximize the benefits of using networks of remote sensors and autonomous systems while still safeguarding infrastructure from system hijacking.