Search results for " information systems"

A Novel Deep Learning Stack for APT Detection

2019

We present a novel Deep Learning (DL) stack for detecting Advanced Persistent threat (APT) attacks. This model is based on a theoretical approach where an APT is observed as a multi-vector multi-stage attack with a continuous strategic campaign. To capture these attacks, the entire network flow and particularly raw data must be used as an input for the detection process. By combining different types of tailored DL-methods, it is possible to capture certain types of anomalies and behaviour. Our method essentially breaks down a bigger problem into smaller tasks, tries to solve these sequentially and finally returns a conclusive result. This concept paper outlines, for example, the problems an…

Urban growth (1956-1998) in the metropolitan area of Alacant-Elx (Comunitat Valenciana)

2007

18 páginas, 5 figuras, 4 tablas. An abbreviated English version of the paper in the same journal is also attached (Boletín de la AGE 43: 369-374).

A Hardware and Secure Pseudorandom Generator for Constrained Devices

2018

Hardware security for an Internet of Things or cyber physical system drives the need for ubiquitous cryptography to different sensing infrastructures in these fields. In particular, generating strong cryptographic keys on such resource-constrained device depends on a lightweight and cryptographically secure random number generator. In this research work, we have introduced a new hardware chaos-based pseudorandom number generator, which is mainly based on the deletion of an Hamilton cycle within the $N$ -cube (or on the vectorial negation), plus one single permutation. We have rigorously proven the chaotic behavior and cryptographically secure property of the whole proposal: the mid-term eff…

Investigating the Impact of Radiation-Induced Soft Errors on the Reliability of Approximate Computing Systems

2020

International audience; Approximate Computing (AxC) is a well-known paradigm able to reduce the computational and power overheads of a multitude of applications, at the cost of a decreased accuracy. Convolutional Neural Networks (CNNs) have proven to be particularly suited for AxC because of their inherent resilience to errors. However, the implementation of AxC techniques may affect the intrinsic resilience of the application to errors induced by Single Events in a harsh environment. This work introduces an experimental study of the impact of neutron irradiation on approximate computing techniques applied on the data representation of a CNN.

Sequential Mining Classification

2017

Sequential pattern mining is a data mining technique that aims to extract and analyze frequent subsequences from sequences of events or items with time constraint. Sequence data mining was introduced in 1995 with the well-known Apriori algorithm. The algorithm studied the transactions through time, in order to extract frequent patterns from the sequences of products related to a customer. Later, this technique became useful in many applications: DNA researches, medical diagnosis and prevention, telecommunications, etc. GSP, SPAM, SPADE, PrefixSPan and other advanced algorithms followed. View the evolution of data mining techniques based on sequential data, this paper discusses the multiple …

Overview on Sequential Mining Algorithms and Their Extensions

2018

The main purpose of data mining is to extract hidden, important and nontrivial information from a database. Sequential Pattern Mining is a data mining technique that aims to obtain and analyze frequent subsequences from sequences of events or items with or without time constraint. The importance of a sequence can be measured based on different factors such as the frequency of their occurrence, their length and also their profit. The pattern mining or the discovery of important and unexpected patterns and information was first introduced in 1990 with the well-known Apriori algorithm. Then, and after many studies on frequent pattern mining, a new approach appeared: Sequential Pattern Mining. …

Hop: Histogram of patterns for human action representation

2017

This paper presents a novel method for representing actions in terms of multinomial distributions of frequent sequential patterns of different length. Frequent sequential patterns are series of data descriptors that occur many times in the data. This paper proposes to learn a codebook of frequent sequential patterns by means of an apriori-like algorithm, and to represent an action with a Bag-of-Frequent-Sequential-Patterns approach. Preliminary experiments of the proposed method have been conducted for action classification on skeletal data. The method achieves state-of-the-art accuracy value in cross-subject validation.

Videotutoriales para la enseñanza de los Sistemas de Información Geográfica aplicados a la arqueología

2019

La experiencia que presentamos aquí se llevó a cabo durante el curso 2018-2019 en las clases prácticas de la asignatura Metodología Arqueológica (tercer curso del grado de Historia). El objetivo de aprendizaje principal de las clases prácticas de esta asignatura se focaliza en que el alumnado se familiarice con las herramientas básicas de los Sistemas de Información Geográfica (SIG) que le permitan resolver problemas de naturaleza arqueológica. Para ello, durante el curso, decidimos aplicar nuevos recursos (vídeo tutoriales) y nuevas metodologías (Flipped Teaching), con el interés de mejorar los resultados de aprendizaje del alumnado. La metodología implica la inversión de la taxonomía de B…

Asynchronous L1 control of delayed switched positive systems with mode-dependent average dwell time

2014

Abstract This paper investigates the stability and asynchronous L 1 control problems for a class of switched positive linear systems (SPLSs) with time-varying delays by using the mode-dependent average dwell time (MDADT) approach. By allowing the co-positive type Lyapunov–Krasovskii functional to increase during the running time of active subsystems, a new stability criterion for the underlying system with MDADT is first derived. Then, the obtained results are extended to study the issue of asynchronous L 1 control, where “asynchronous” means that the switching of the controllers has a lag with respect to that of system modes. Sufficient conditions are provided to guarantee that the resulti…

2016

Abstract. Particle concentration measurements with underwing probes on aircraft are impacted by air compression upstream of the instrument body as a function of flight velocity. In particular, for fast-flying aircraft the necessity arises to account for compression of the air sample volume. Hence, a correction procedure is needed to invert measured particle number concentrations to ambient conditions that is commonly applicable to different instruments to gain comparable results. In the compression region where the detection of particles occurs (i.e. under factual measurement conditions), pressure and temperature of the air sample are increased compared to ambient (undisturbed) conditions i…