In 1993, the U.S. Department of Transportation’s Volpe National Transportation Systems Center (the Volpe Center) began a multiyear research effort to propose an improved process for assessing motor carrier safety fitness for the Federal Highway Administration’s Office of Motor Carriers (OMC). At the time, OMC’s primary method of determining safety fitness came from ratings based on the results of onsite safety compliance reviews. The intent of OMC was to take advantage of improved safety data reporting, information systems technologies, and the Volpe Center’s experience in safety measurement methodology, as well as to address the weaknesses of the rating process. The Volpe Center proposed using an automated safety performance monitoring system and subsequently developed SafeStat (Motor Carrier Safety Status Measurement System) as part of a federal-state pilot program. Since then, SafeStat has been implemented nationally by OMC to rank individual motor carriers for compliance reviews. SafeStat is designed to incorporate current on-road safety performance information and enforcement history with the compliance review information to measure the overall relative safety fitness of interstate carriers. In arriving at this overall assessment, SafeStat evaluates carriers in four safety evaluation areas: accident, driver, vehicle, and safety management. SafeStat enables OMC to quantify and monitor the safety status of carriers continually, thereby allowing OMC enforcement and education programs to efficiently allocate resources to carriers that pose a high risk of crashes. The methodology and the current and proposed uses of SafeStat are described.

Cyber attacks are greatly expanding in both size and complexity. To handle this issue, research has been focused on collaborative intrusion detection networks (CIDNs), which can improve the detection accuracy of a single IDS by allowing various nodes to communicate with each other. While such collaborative system or network is vulnerable to insider attacks, which can significantly reduce the advantages of a detector. To protect CIDNs against insider attacks, one potential way is to enhance the trust evaluation among IDS nodes, i.e., by emphasizing the impact of expert nodes. In this work, we adopt the notion of intrusion sensitivity that assigns different values of detection capability relating to particular attacks, and evaluate its impact on defending against a special On-Off attack (SOOA). In the evaluation, we investigate the impact of intrusion sensitivity in a simulated CIDN environment, and experimental results demonstrate that the use of intrusion sensitivity can help enhance the security of CIDNs under adversarial scenarios, like SOOA.

SafeStat (Safety Status Measurement System) is an automated analysis system developed for FHWA’s Office of Motor Carriers (OMC) that combines current and historical safety data to measure the relative safety fitness of interstate motor carriers. SafeStat enables OMC to quantify and monitor the safety status of motor carriers and guides the deployment of resources to focus on carriers posing the greatest safety risk. SafeStat resulted from research performed by the U.S. Department of Transportation’s Volpe Center for OMC to improve motor carrier safety fitness assessment and prescribe actions for correcting safety deficiencies. SafeStat initially was developed and implemented as part of a federalstate pilot program. It has been implemented nationally by OMC to identify and rank individual motor carriers for on-site safety compliance reviews. An effectiveness study was devised to confirm that SafeStat-identified carriers were high-safety-risk carriers. Postidentification carrier crash experience was examined and SafeStat’s effectiveness was tested by comparing the crash rates of identified and nonidentified carriers. The effectiveness study shows that SafeStat identifies carriers likely to have significantly higher crash rates than carriers not identified. Specifically, the carriers designated in the highest “at risk” category by SafeStat had a much higher crash rate (169% percent higher) following their identification than carriers not identified as safety risks. In addition to confirming SafeStat’s effectiveness, the results of the study enable SafeStat developers and OMC to assess the relative strengths of SafeStat’s components and to continue enhancing its efficiency.