首页|Purdue University Researchers Provide Details of New Studies and Findings in the Area of Machine Learning (Explaining vulnerabilities of heart rate biometric mo dels securing IoT wearables)
Purdue University Researchers Provide Details of New Studies and Findings in the Area of Machine Learning (Explaining vulnerabilities of heart rate biometric mo dels securing IoT wearables)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting originating from West Lafayet te, Indiana, by NewsRx correspondents, research stated, “In the field of health informatics, extensive research has been conducted to predict diseases and extra ct valuable insights from patient data.” Our news correspondents obtained a quote from the research from Purdue Universit y: “However, a significant gap exists in addressing privacy concerns associated with data collection. Therefore, there is an urgent need to develop a machine-le arning authentication model to secure the patients’ data seamlessly and continuo usly, as well as to find potential explanations when the model may fail. To addr ess this challenge, we propose a unique approach to secure patients’ data using novel eigenheart features calculated from coarse-grained heart rate data. Variou s statistical and visualization techniques are utilized to explain the potential vulnerabilities of the model. Though it is feasible to develop continuous user authentication models from readily available heart rate data with reasonable per formance, they are affected by factors such as age and Body Mass Index (BMI).”
Purdue UniversityWest LafayetteIndia naUnited StatesNorth and Central AmericaMachine Learning
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