A5103141285- Network Security and Intrusion Detection
- Internet Traffic Analysis and Secure E-voting
- Advanced Malware Detection Techniques
- Anomaly Detection Techniques and Applications
- Business Process Modeling and Analysis
- Big Data and Business Intelligence
- Speech and Audio Processing
- Healthcare Systems and Public Health
- Video Surveillance and Tracking Methods
- IoT-based Smart Home Systems
- Neural Networks and Applications
- Software System Performance and Reliability
- Smart Grid Security and Resilience
- Speech Recognition and Synthesis
- Scientific Research and Technology
- Music and Audio Processing
- Advanced Neural Network Applications
- Human Pose and Action Recognition
- Spam and Phishing Detection
- Emotion and Mood Recognition
Hospital Clínico San Carlos
2022
Universidad Politécnica de Madrid
2020
Centro de Tecnologia da Informação Renato Archer
2006-2008
Universidade Federal do Paraná
2007-2008
Cisco Systems (United States)
2005-2007
National Institute for Space Research
2005
This work presents a network intrusion detection method, created to identify and classify illegitimate information in TCP/IP packet payload based on the Snort signature set that represents possible attacks network. For this development, type of neural named Hamming net was used. The choice is interest investigate its adequacy events real-time, due capability learn faster than other models, such as, multilayer perceptrons with backpropagation Kohonen maps. A does not require exhaustive...
Speech Emotion Recognition (SER) plays an important role in human-computer interface and assistant technologies. In this paper, a new method is proposed using distributed Convolution Neural Networks (CNN) to automatically learn affect-salient features from raw spectral information, then applying Bidirectional Recurrent Network (BRNN) obtain the temporal information output of CNN. end, Attention Mechanism implemented on sequence BRNN focus target emotion-pertinent parts utterance. This...
As the amount and types of remote network services increase, analysis their logs has become a very difficult time consuming task. There are several ways to filter relevant information provide reduced log set for analysis, such as whitelisting intrusion detection tools, but all them require too much fine- tuning work human expertise. Nowadays, researchers evaluating data mining approaches in logs, using techniques genetic algorithms, neural networks, clustering etc. Some those yield good...
This paper presents a comparative analysis of results obtained when applying Hamming Net and LVQ (Learning Vector Quantization) classifiers neural networks to recognize attack signatures in datasets. Strings similar those located on payload field computer packets are inserted these for pattern classification. Since 2004, it was presented the first time, ANNIDA system (Artificial Neural Network Intrusion Detection Application) has been improved. Although very sufficient by application network...
In this work we discuss some new techniques used by intruders to control a group of compromised machines (botnets).It is also shown how honeynets can be identify, monitor and understand current botnets behavior.We outline real case compromise, detailing analysis specially developed for study, including the tools, topology strategies adopted, as well results obtained in use identify botnets.
In this work we discuss some new techniques used by intruders to control a group of compromised machines (botnets).It is also shown how honeynets can be identify, monitor and understand current botnets behavior.We outline real case compromise, detailing analysis specially developed for study, including the tools, topology strategies adopted, as well results obtained in use identify botnets.
Abstract Introduction and purpose Atrial fibrillation (AF) is the most common arrhythmia worldwide, with a considerable prevalence, high morbidity, mortality, finantial cost in Europe. To optimise quality of medical care received patients AF, we need to know investigate their accurate demographic clinical typology actual patient journey, which involves many data review number included. The CHA2DS2Vasc score classifies risk stroke atrial fibrillation, one critical complications this...
As part of an effort to improve honeynet's maintenance process, several procedures and tools automating high-interaction honeypot management tasks have been developed. Among the advantages adoption use these are documentation procedures, standardization collected data structure, elimination errors during honeypots, automatization that executed reduction time between deactivation activation a compromised honeypot.
Abstract Introduction and purpose Atrial fibrillation (AF) is the most common arrhythmia worldwide, with a considerable prevalence, high morbidity, mortality, finantial cost in Europe. To optimise quality of medical care received patients AF, we need to know investigate their accurate demographic clinical typology actual patient journey, which involves many data review number included. The CHA2DS2Vasc score classifies risk stroke atrial fibrillation, one critical complications this...