no code implementations • 1 Nov 2023 • Mounika Vanamala, Keith Bryant, Alex Caravella
In today's rapidly evolving technological landscape and advanced software development, the rise in cyber security attacks has become a pressing concern.
no code implementations • 24 Apr 2023 • Brendan Pelto, Mounika Vanamala, Rushit Dave
The results of the research showed that all three algorithms were able to effectively classify users based on their individual touch dynamics, with accuracy ranging from 80% to 95%.
no code implementations • 4 Apr 2023 • Aniruddha Tiwari, Rushit Dave, Mounika Vanamala
Conspicuous progression in the field of machine learning and deep learning have led the jump of highly realistic fake media, these media oftentimes referred as deepfakes.
no code implementations • 10 Feb 2023 • Nicholas Lasky, Benjamin Hallis, Mounika Vanamala, Rushit Dave, Jim Seliya
In this paper, we use machine learning algorithms to map requirements to the MITRE ATT&CK database and determine the accuracy of each mapping depending on the data split.
no code implementations • 27 Jan 2023 • Jacob mallet, Laura Pryor, Rushit Dave, Mounika Vanamala
Social media is currently being used by many individuals online as a major source of information.
no code implementations • 27 Jul 2022 • Jacob mallet, Rushit Dave, Naeem Seliya, Mounika Vanamala
This study looks at various deepfake detection models that use deep learning algorithms to combat this looming threat.
1 code implementation • 26 May 2022 • Nyle Siddiqui, Rushit Dave, Naeem Seliya, Mounika Vanamala
Static authentication methods, like passwords, grow increasingly weak with advancements in technology and attack strategies.
no code implementations • 7 May 2022 • Laura Pryor, Jacob mallet, Rushit Dave, Naeem Seliya, Mounika Vanamala, Evelyn Sowells Boone
In this study, we aim to contribute to the research being done on behavioral biometrics by creating and evaluating a user authentication scheme using behavioral biometrics.
no code implementations • 26 Apr 2022 • Wei Zhong Tee, Rushit Dave, Naeem Seliya, Mounika Vanamala
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 low in costs compared to more traditional machine learning techniques.
no code implementations • 21 Jan 2022 • Rushit Dave, Naeem Seliya, Mounika Vanamala, Wei Tee
Results show promise for models trained strictly using limited sensor data collected from only smartphones and smartwatches coupled with traditional machine learning concepts and algorithms.
no code implementations • 21 Jan 2022 • Rushit Dave, Naeem Seliya, Laura Pryor, Mounika Vanamala, Evelyn Sowells, Jacob mallet
In recent years the amount of secure information being stored on mobile devices has grown exponentially.