878 research outputs found
Keystroke Biometrics in Response to Fake News Propagation in a Global Pandemic
This work proposes and analyzes the use of keystroke biometrics for content
de-anonymization. Fake news have become a powerful tool to manipulate public
opinion, especially during major events. In particular, the massive spread of
fake news during the COVID-19 pandemic has forced governments and companies to
fight against missinformation. In this context, the ability to link multiple
accounts or profiles that spread such malicious content on the Internet while
hiding in anonymity would enable proactive identification and blacklisting.
Behavioral biometrics can be powerful tools in this fight. In this work, we
have analyzed how the latest advances in keystroke biometric recognition can
help to link behavioral typing patterns in experiments involving 100,000 users
and more than 1 million typed sequences. Our proposed system is based on
Recurrent Neural Networks adapted to the context of content de-anonymization.
Assuming the challenge to link the typed content of a target user in a pool of
candidate profiles, our results show that keystroke recognition can be used to
reduce the list of candidate profiles by more than 90%. In addition, when
keystroke is combined with auxiliary data (such as location), our system
achieves a Rank-1 identification performance equal to 52.6% and 10.9% for a
background candidate list composed of 1K and 100K profiles, respectively.Comment: arXiv admin note: text overlap with arXiv:2004.0362
BehavePassDB: Public Database for Mobile Behavioral Biometrics and Benchmark Evaluation
Mobile behavioral biometrics have become a popular topic of research,
reaching promising results in terms of authentication, exploiting a multimodal
combination of touchscreen and background sensor data. However, there is no way
of knowing whether state-of-the-art classifiers in the literature can
distinguish between the notion of user and device. In this article, we present
a new database, BehavePassDB, structured into separate acquisition sessions and
tasks to mimic the most common aspects of mobile Human-Computer Interaction
(HCI). BehavePassDB is acquired through a dedicated mobile app installed on the
subjects' devices, also including the case of different users on the same
device for evaluation. We propose a standard experimental protocol and
benchmark for the research community to perform a fair comparison of novel
approaches with the state of the art. We propose and evaluate a system based on
Long-Short Term Memory (LSTM) architecture with triplet loss and modality
fusion at score level.Comment: 11 pages, 3 figure
Chatter mitigation in milling process using discrete time sliding mode control with type 2-fuzzy logic system
In order to achieve a high-quality machining process with superior productivity, it is very important to tackle the phenomenon of chatter in an effective manner. The problems like tool wear and improper surface finish affect the milling process and are caused by self-induced vibration termed as chatter. A strategy to control chatter vibration actively in the milling process is presented. The mathematical modeling of the process is carried out initially. In this paper, an innovative technique of discrete time sliding mode control (DSMC) is blended with the type-2 fuzzy logic system. The proposed active controller results in a significantly high mitigation of vibration. The DSMC is linked to the time-varying gain which is an innovative approach to mitigate chattering. The theorem is laid down which validates that the system states are bounded in the case of DSMC-type-2 fuzzy. Stability analysis is carried out using Lyapunov candidate. The nonlinearities linked with the cutting forces and damper friction are handled effectively by using the type-2 fuzzy logic system. The performance of the DSMC-type-2 fuzzy concept is compared with the discrete time PID (D-PID) and discrete time sliding mode control for validating the effectiveness of the controller. The better performance of DSMC-type-2 fuzzy over D-PID and DSMC-T1 fuzzy in the minimization of milling chatter are validated by a numerical analysis approach
Enseñanza de las secciones cónicas como lugares geométricos en un aula inclusiva de estudiantes invidentes
Este trabajo corresponde a una propuesta dirigida a la enseñanza de las secciones cónicas como lugares geométricos en un aula inclusiva con estudiantes invidentes de grado décimo. Para su desarrollo se consideró el diseño y elaboración de actividades de aprendizaje y de evaluación propuestas por el Grupo DECA (1992), y la propuesta didáctica presentada por Del Río (1996); una revisión teórica tanto del marco histórico, legal, didáctico, matemático y metodológico, como de las formas de evaluación; de igual manera se consideró un marco referente a la limitación visual para reflexionar sobre la inclusión en el aula. Posteriormente, se desarrolló el planteamiento de situaciones problema desde las cuales se orientó al estudiante a identificar las cónicas como lugares geométricos
Formación en valores y responsabilidad social del profesor de matemáticas 
En este trabajo se desarrolla una breve discusión respecto a la promoción de valores democráticos en el aula de matemáticas, y el papel del docente en la consolidación de dichos valores. Adicionalmente se plantean algunas hipótesis, respecto a la responsabilidad social de la asignatura escolar de matemáticas, las cuales serán discutidas a la luz de lo planteado por Bishop (1999) y Ernest (2009)
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