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Found 20 papers, 1 papers with code
Your device may know you better than you know yourself -- continuous authentication on novel dataset using machine learning
This research aims to further understanding in the field of continuous authentication using behavioral biometrics.
From Clicks to Security: Investigating Continuous Authentication via Mouse Dynamics
This research contributes to the ongoing efforts to enhance computer security and highlights the potential of leveraging user behavior, specifically mouse dynamics, in developing robust authentication systems.
Your Identity is Your Behavior -- Continuous User Authentication based on Machine Learning and Touch Dynamics
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%.
Leveraging Deep Learning Approaches for Deepfake Detection: A Review
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.
Machine Learning Based Approach to Recommend MITRE ATT&CK Framework for Software Requirements and Design Specifications
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.
Deepfake Detection Analyzing Hybrid Dataset Utilizing CNN and SVM
Social media is currently being used by many individuals online as a major source of information.
Using Deep Learning to Detecting Deepfakes
This study looks at various deepfake detection models that use deep learning algorithms to combat this looming threat.
Mitigating Presentation Attack using DCGAN and Deep CNN
For MICHE-I [2] and VISOB [3] datasets, we achieved the test accuracies of 95% and 96% respectively.
Machine and Deep Learning Applications to Mouse Dynamics for Continuous User Authentication
Static authentication methods, like passwords, grow increasingly weak with advancements in technology and attack strategies.
Evaluation of a User Authentication Schema Using Behavioral Biometrics and Machine Learning
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.
A Close Look into Human Activity Recognition Models using Deep Learning
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.
Exploration of Machine Learning Classification Models Used for Behavioral Biometrics Authentication
Mobile devices have been manufactured and enhanced at growing rates in the past decades.
A Robust Framework for Deep Learning Approaches to Facial Emotion Recognition and Evaluation
A lightweight convolutional neural network is trained on the AffectNet dataset a large variable dataset for facial emotion recognition and a web application is developed and deployed with our proposed framework as a proof of concept.
Hold On and Swipe: A Touch-Movement Based Continuous Authentication Schema based on Machine Learning
In recent years the amount of secure information being stored on mobile devices has grown exponentially.
Human Activity Recognition models using Limited Consumer Device Sensors and Machine Learning
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.
Application of Machine Learning-Based Pattern Recognition in IoT Devices: Review
The Internet of things (IoT) is a rapidly advancing area of technology that has quickly become more widespread in recent years.
Continuous Authentication Using Mouse Movements, Machine Learning, and Minecraft
Mouse dynamics has grown in popularity as a novel irreproducible behavioral biometric.
A Modern Analysis of Aging Machine Learning Based IoT Cybersecurity Methods
This study examines the effectiveness of three distinct Internet of Things cyber security algorithms currently used in industry today for malware and intrusion detection: Random Forest (RF), Support-Vector Machine (SVM), and K-Nearest Neighbor (KNN).
Named Entity Recognition in Unstructured Medical Text Documents
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 ailments.
Machine Learning: Challenges, Limitations, and Compatibility for Audio Restoration Processes
In this paper machine learning networks are explored for their use in restoring degraded and compressed speech audio.
BIG-bench Machine Learning
Generative Adversarial Network
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