"DHS Seeks Ideas for Automated Cyberattack Detectors in Annual Notice"

The Department of Homeland Security (DHS) is seeking applications from small businesses to address seven "technology needs" as part of the Science and Technology Directorate Small Business Innovation Research (SBIR) initiative for fiscal year 2023. Proposals to create a hardware-assisted real-time, accurate detector of cyberattacks on networked and edge electronic devices are included. The cybersecurity research topic included in the solicitation issued on December 15 notes that a growing number of network-connected devices and systems are susceptible to various attacks, with current cyber protection efforts limited due to detection efficacy and scalability issues. The Request for Proposal (RFP) is looking for proposals for analyzing hardware-generated data that would enable real-time, precise detection, and proactive protection against cyber threats, given the scale of digital threats and the absence of secure defense approaches. This effort aims to develop a device-embedded solution that delivers engaging automatic protection without human intervention, removing a major variable from the cybersecurity equation. The expectation is that this improved automatic system will have a low performance overhead while providing multi-layer and distributed defense. The three-phase award system of the DHS SBIR program allows US enterprises with less than 500 employees to create innovative new technologies for the department. According to DHS, the SBIR program RFP is published annually and covers different topics that fulfill specific homeland security research and development technological needs. Small firms that submit research proposals relevant to the cybersecurity issue area under phase one of the SBIR program would be expected to determine the technological feasibility of accurate, real-time, and automatic detection of cyber threats using hardware-assisted modalities. This includes determining the major challenges and preliminary evaluation of Machine Learning (ML) algorithms for extracting features of various cyber threats, as well as developing a concept model for anomaly detection that takes into account hardware features and emerging approaches in ML. This article continues to discuss the DHS seeking proposals for automated cyberattack detectors. 

NextGov reports "DHS Seeks Ideas for Automated Cyberattack Detectors in Annual Notice"