most citedMachine and Deep Learning Applications to Mouse Dynamics for Continuous User Authentication

54 citations · 72 across the 10 of their papers we have counts for

collaborators

10 papers

cs.AI202254 cited

Machine and Deep Learning Applications to Mouse Dynamics for Continuous User Authentication

Nyle Siddiqui, Rushit Dave, Naeem Seliya +1

Static authentication methods, like passwords, grow increasingly weak with advancements in technology and attack strategies. Continuous authentication has been proposed as a soluti…

cs.CR20224 cited

Evaluation of a User Authentication Schema Using Behavioral Biometrics and Machine Learning

Laura Pryor, Jacob Mallet, Rushit Dave +3

The amount of secure data being stored on mobile devices has grown immensely in recent years. However, the security measures protecting this data have stayed static, with few impro…

cs.CV20223 cited

A Close Look into Human Activity Recognition Models using Deep Learning

Wei Zhong Tee, Rushit Dave, Naeem Seliya +1

Human activity recognition using deep learning techniques has become increasing popular because of its high effectivity with recognizing complex tasks, as well as being relatively…

cs.LG2022

Human Activity Recognition models using Limited Consumer Device Sensors and Machine Learning

Rushit Dave, Naeem Seliya, Mounika Vanamala +1

Human activity recognition has grown in popularity with its increase of applications within daily lifestyles and medical environments. The goal of having efficient and reliable hum…

cs.CR20225 cited

Hold On and Swipe: A Touch-Movement Based Continuous Authentication Schema based on Machine Learning

Rushit Dave, Naeem Seliya, Laura Pryor +3

In recent years the amount of secure information being stored on mobile devices has grown exponentially. However, current security schemas for mobile devices such as physiological…

cs.CL20211 cited

Named Entity Recognition in Unstructured Medical Text Documents

Cole Pearson, Naeem Seliya, Rushit Dave

Physicians provide expert opinion to legal courts on the medical state of patients, including determining if a patient is likely to have permanent or non-permanent injuries or ailm…