SCC-LSR: from technology to humans: protecting users of neural and medical implant technologies through resilience and safety engineering

The National Science Foundation's Division of Computer and Network Systems awarded Northeastern University a $2.62M project grant (CFDA 47.070: Computer and Information Science and Engineering) effective September 1, 2025 through August 31, 2030 to develop hardware and software solutions protecting users of neural and medical implant devices from security threats. The research team—comprising computer scientists, electrical engineers, physicians, neuroscientists, implant manufacturers, and patient advocacy groups—will deliver integrated chip-level security mechanisms, resilient control system designs, and low-resource chip manufacturing techniques. Core deliverables include on-chip anomaly detection sensors monitoring voltage, electromagnetic fields, temperature, and motion to identify intrusions and system malfunctions; graceful degradation protocols that transition devices into higher-security, lower-utility modes when threats are detected; and hardware/software co-design solutions enabling safe adoption of emerging neural implant technologies. Research outcomes will establish defense mechanisms applicable broadly to other chip-based smart healthcare devices.

Northeastern University partnered with University of Massachusetts (hardware-enabled intrusion detection and security-utility trade-off modeling), University of Illinois (institutional review board development and community engagement through focus groups), and Massachusetts General Hospital (two sub-awards for clinical use-case modeling, testbed development, standards conformance testing, and chip validation). These collaborations integrate fundamental security research with clinical validation, community input from patients and caregivers, and manufacturer partnership to address real-world adoption barriers and confirm research hypotheses through rigorous evaluation protocols.

Abstract

This research will advance community priorities in the areas of safety, security, and human health and wellness pertaining to existing and future neural implant devices. The team includes computer scientists, electrical engineers, MDS, neuroscientists, neural implant community groups, and manufacturers. The partner community groups include patients and their supporting families and caregivers from whom the team will understand the personal impact of neural implant technologies. Expanding engagement with partnered companies who manufacture and medical doctors who use neural implants, the team will address these community challenges and collaboratively deliver a neural implant hardware/software CO-design solution that empowers the use and facilitates the safe adoption of emerging neural implant technologies. The research techniques developed for chip security will have applicability to other security related chip-based devices. This project will advance the scientific and technical security and chip hardware design by modeling the operations from a secure and dependable control perspective and developing innovative defense mechanisms that can be applied to emerging smart healthcare devices. Finally, by adding low-resource chip design, the team will advance manufacturing techniques for chip-based devices adding additional security features without impact to overall performance or lifetime. Researchers have demonstrated the impact of ?brain-jacking? In mouse models but have not provided solutions. This team?s multipronged project resolves these challenges by leveraging expertise in computer security, sensing, microelectronic design, and strong affiliations with clinical settings. The approaches include the design of (1) verifiably resilient control system and simulations and design upgrades that build upon models of neural sensing and stimulation and explainable AI techniques, (2) automated cybersecurity and resilience testbeds that host physical neural implant devices for fault-injection, side-channel information leakage, and remote connection security analysis, and (3) low-resource (i.e., computational time, power, footprint) intrusion detection with on-chip sensing to continuously monitor anomalies and deter adversarial manipulations. The team will improve the resilience and security of neural implants by protecting system hardware and AI-in-the-loop control software from malicious information injection, disruption in operation, and privacy leakage. A test bed will be developed to validate and test physical devices, see the results from modeling and microelectronic design changes, with real world data collected in lab and translated back to the model for updating and control of realistic interactions. Testing the insertion of malicious intent or unintended interference will allow the team to discern impact and identify potential design changes on the device hardware to prevent future incidents. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are planned for this award.