Adverse Events in Robotic Surgery: A Retrospective Study of 14 Years of FDA Data

Understanding the causes and patient impacts of surgical adverse events will help improve systems and operational practices to avoid incidents in the future. We analyzed the adverse events data related to robotic systems and instruments used in minimally invasive surgery, reported to the U.S. FDA MAUDE database from January 2000 to December 2013. We determined the number of events reported per procedure and per surgical specialty, the most common types of device malfunctions and their impact on patients, and the causes for catastrophic events such as major complications, patient injuries, and deaths. During the study period, 144 deaths (1.4% of the 10,624 reports), 1,391 patient injuries (13.1%), and 8,061 device malfunctions (75.9%) were reported. The numbers of injury and death events per procedure have stayed relatively constant since 2007 (mean = 83.4, 95% CI, 74.2-92.7). Surgical specialties, for which robots are extensively used, such as gynecology and urology, had lower number of injuries, deaths, and conversions per procedure than more complex surgeries, such as cardiothoracic and head and neck (106.3 vs. 232.9, Risk Ratio = 2.2, 95% CI, 1.9-2.6). Device and instrument malfunctions, such as falling of burnt/broken pieces of instruments into the patient (14.7%), electrical arcing of instruments (10.5%), unintended operation of instruments (8.6%), system errors (5%), and video/imaging problems (2.6%), constituted a major part of the reports. Device malfunctions impacted patients in terms of injuries or procedure interruptions. In 1,104 (10.4%) of the events, the procedure was interrupted to restart the system (3.1%), to convert the procedure to non-robotic techniques (7.3%), or to reschedule it to a later time (2.5%). Adoption of advanced techniques in design and operation of robotic surgical systems may reduce these preventable incidents in the future.Comment: Presented as the J. Maxwell Chamberlain Memorial Paper for adult cardiac surgery at the 50th Annual Meeting of the Society of Thoracic Surgeons in January. See Appendix for more detailed results, discussions, and related work. Updated the header

Adapting Bro into SCADA: Building Specification-based Intrusion Detection System for DNP3 Protocol

Modern SCADA systems are increasingly adopting Internet technology to control industry processes. With their security vulnerabilities exposed to public networks, an attacker is able to penetrate into these control systems to put remote facilities in danger. To detect such attacks, SCADA systems require an intrusion detection technique that can monitor network traffic based on proprietary network protocols. To achieve this goal, we adapt Bro, a network traffic analyzer widely used for intrusion detection, for use with SCADA systems. A built-in parser in Bro supports DNP3, a network protocol that is widely used in SCADA systems for electrical power grids. By exploiting Bro’s intrusion detection features, we apply a specification-based technique to analyze the parsed traffic. This built-in parser provides high visibility of network events in SCADA systems. Instead of exploiting an attack signature or a statistical normal pattern, SCADA-specific semantics related to each event are analyzed. Such analyses are made in terms of defined security policies which can be included at runtime. Our experiments are carried out in a laboratory-scale SCADA system environment with well-formatted but malicious network traffic. The detection capability and performance of the Bro-adapted intrusion detection system revealed in experiments show its potential applicability in the real SCADA system environment.Department of Energy & Department of Homeland Security/DE-OE0000097Ope

Fast Distributed Simulation for Dependability Analysis of a Cache-based RAID System

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryDARPA/ITO / DABT63-94-C-0045NASA Langley Research Center / NASA NAG 1-613Tandem Computer

AVFI: Fault Injection for Autonomous Vehicles

Autonomous vehicle (AV) technology is rapidly becoming a reality on U.S. roads, offering the promise of improvements in traffic management, safety, and the comfort and efficiency of vehicular travel. With this increasing popularity and ubiquitous deployment, resilience has become a critical requirement for public acceptance and adoption. Recent studies into the resilience of AVs have shown that though the AV systems are improving over time, they have not reached human levels of automation. Prior work in this area has studied the safety and resilience of individual components of the AV system (e.g., testing of neural networks powering the perception function). However, methods for holistic end-to-end resilience assessment of AV systems are still non-existent.Comment: Published in: 2018 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W