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Keystroke dynamics, keystroke biometrics, typing dynamics, or typing biometrics refer to the collection of biometric information generated by key-press-related events that occur when a user types on a keyboard. [1] Use of patterns in key operation to identify operators predates modern computing, [2] and has been proposed as an authentication ...
Keystroke logging can be used to research writing, specifically. It can also be integrated into educational domains for second language learning, programming skills, and typing skills. Related features. Software keyloggers may be augmented with features that capture user information without relying on keyboard key presses as the sole input.
The Viola–Jones object detection framework is a machine learning object detection framework proposed in 2001 by Paul Viola and Michael Jones. [1] [2] It was motivated primarily by the problem of face detection, although it can be adapted to the detection of other object classes. The algorithm is efficient for its time, able to detect faces in ...
Machine learningand data mining. Eclipse Deeplearning4j is a programming library written in Java for the Java virtual machine (JVM). [2] [3] It is a framework with wide support for deep learning algorithms. [4] Deeplearning4j includes implementations of the restricted Boltzmann machine, deep belief net, deep autoencoder, stacked denoising ...
Hardware keyloggers are used for keystroke logging, a method of capturing and recording computer users' keystrokes, including sensitive passwords. [1] They can be implemented via BIOS -level firmware, or alternatively, via a device plugged inline between a computer keyboard and a computer. They log all keyboard activity to their internal memory.
A device fingerprint or machine fingerprint is information collected about the software and hardware of a remote computing device for the purpose of identification. The information is usually assimilated into a brief identifier using a fingerprinting algorithm.
Machine learningand data mining. These datasets are used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major advances in this field can result from advances in learning algorithms (such as deep learning ), computer hardware, and, less ...
Aljameel et al. propose an advanced machine learning-based model for detecting minor leaks in oil and gas pipelines, a task traditional methods may miss. Methods. Many anomaly detection techniques have been proposed in literature. The performance of methods usually depend on the data sets. For example, some may be suited to detecting local ...