Toward Network-based DDoS Detection in Software-defined Networks

To combat susceptibility of modern computing systems to cyberattack, identifying and disrupting malicious traffic without human intervention is essential. To accomplish this, three main tasks for an effective intrusion detection system have been identified: monitor network traffic, categorize and identify anomalous behavior in near real time, and take appropriate action against the identified threat. This system leverages distributed SDN architecture and the principles of Artificial Immune Systems and Self-Organizing Maps to build a network-based intrusion detection system capable of detecting and terminating DDoS attacks in progress

Modelling a layer for real-time management of interactions in web based distance learning

In the last few years, the University of Aveiro, Portugal, has been offering several distance learning courses over the Web, using e-learning platforms. Experience showed that different editions of a same course, using the same contents and structure, and having similar target learners, had different success rates. What would be the reason for that? A hypothesis was considered: The level of success could be directly related with the remote follow-up of the learners’ participation in the courses; the best results usually occur when the follow-up is closer. The existing e-learning platforms offer and the standardization works being developed by organizations and consortiums like IMS (IMS Global Learning Consortium, Inc), ADL SCORM (Advanced Distributed Learning Sherable Content Object Reference Model), IEEE LTSC LOM (Institute of Electrical and Electronic Engineers Learning Technologies Standard Committee Learning Object Metadata), ARIADNE (ARIADNE Foundation for the European Knowledge Pool), AICC CMI (Aviation Industry CBT Committee Computer Managed Instruction), etc, don’t cover the course monitorization concerns mentioned. Those projects were focused on aspects like contents and its delivery in the context of the execution of the courses’ activities. This is even true in the SCORM project that doesn’t include any reference to the management of the e-learning processes. Recently, in the context of the IMS Global Consortium, a new project designated IMS LD (Learning Design) is under development, providing a framework for the description of learning units under a three level model. In the most recently defined level, the C level, some functionalities related to notifications were proposed, expressing similar concerns to the ones that triggered our research. However, the extent at which IMS LD takes the functionalities is, from our point of view, not complete. This article describes a proposal of a reference model and functionalities towards a specification of a layer for real-time management of user interactions on LMSs, and its possible integration with the ADL SCORM standard proposal. The paper includes a discussion of the management metadata model for the LMS sub-system and how the integration of the management module under SCORM may be achieved

BakSIM : an application for control, monitoring and simulation of baker's yeast fermentation process

This paper describes an experience based on the final project work for the Industrial Electronics Engineering undergraduate course. The main goal was the development of an application for the simulation and monitorization of the baker’s yeast fermentation. The BakSIM application simulates a Mini-Bioreactor for the control, monitorization and simulation of the process running in open and closed loop modes. It permits to make the acquisition of the most important system variables: biomass, ethanol, oxygen, glucose and dioxide of carbon, and the writing in files for future analysis and for future contrast with previous experiences. Different modules were considered: simulation, monitorization and simulation and monitorization. The BakSIM application also allows not only the comparison of the experimental data with the simulated data as the study of the effectiveness of several numerical methods. One more advantage of this project was its multidisciplinary work, enclosing several areas covered during the undergraduate course, namely Programming, Process Control and Numerical Methods.Centre ALGORITMI

A machine learning approach with verification of predictions and assisted supervision for a rule-based network intrusion detection system

Network security is a branch of network management in which network intrusion detection systems provide attack detection features by monitorization of traffic data. Rule-based misuse detection systems use a set of rules or signatures to detect attacks that exploit a particular vulnerability. These rules have to be handcoded by experts to properly identify vulnerabilities, which results in misuse detection systems having limited extensibility. This paper proposes a machine learning layer on top of a rule-based misuse detection system that provides automatic generation of detection rules, prediction verification and assisted classification of new data. Our system offers an overall good performance, while adding an heuristic and adaptive approach to existing rule-based misuse detection systems

Asterias: a parallelized web-based suite for the analysis of expression and aCGH data

Asterias (\url{http://www.asterias.info}) is an integrated collection of freely-accessible web tools for the analysis of gene expression and aCGH data. Most of the tools use parallel computing (via MPI). Most of our applications allow the user to obtain additional information for user-selected genes by using clickable links in tables and/or figures. Our tools include: normalization of expression and aCGH data; converting between different types of gene/clone and protein identifiers; filtering and imputation; finding differentially expressed genes related to patient class and survival data; searching for models of class prediction; using random forests to search for minimal models for class prediction or for large subsets of genes with predictive capacity; searching for molecular signatures and predictive genes with survival data; detecting regions of genomic DNA gain or loss. The capability to send results between different applications, access to additional functional information, and parallelized computation make our suite unique and exploit features only available to web-based applications.Comment: web based application; 3 figure

Social issues of power harvesting as key enables of WSN in pervasive computing

Pervasive systems have gained popularity and open the door to new applications that will improve the quality of life of the users. Additionally, the implementation of such systems over an infrastructure of Wireless Sensor Networks has been proven to be very powerful. To deal with the WSN problems related to the battery of the elements or nodes that constitute the WSN, Power Harvesting techniques arise as good candidates. With PH each node can extract the energy from the surrounding environment. However, this energy source could not be constant, affecting the continuity and quality of the services provided. This behavior can have a negative impact on the user's perception about the system, which could be perceived as unreliable or faulty. In the current paper, some related works regarding pervasive systems within the home environment are referenced to extrapolate the conclusions and problems to the paradigm of Power Harvesting Pervasive Systems from the user perspective. Besides, the paper speculates about the approach and methods to overcome these potential problems and presents the design trends that could be followed.<br/

Design and Performance Analysis of a Non-Standard EPICS Fast Controller

The large scientific projects present new technological challenges, such as the distributed control over a communication network. In particular, the middleware EPICS is the most extended communication standard in particle accelerators. The integration of modern control architectures in these EPICS networks is becoming common, as for example for the PXI/PXIe and xTCA hardware alternatives. In this work, a different integration procedure for PXIe real time controllers from National Instruments is proposed, using LabVIEW as the design tool. This methodology is considered and its performance is analyzed by means of a set of laboratory experiments. This control architecture is proposed for achieving the implementation requirements of the fast controllers, which need an important amount of computational power and signal processing capability, with a tight real-time demand. The present work studies the advantages and drawbacks of this methodology and presents its comprehensive evaluation by means of a laboratory test bench, designed for the application of systematic tests. These tests compare the proposed fast controller performance with a similar system implemented using an standard EPICS IOC provided by the CODAC system.Comment: This is the extended version of the Conference Record presented in the IEEE Real-Time Conference 2014, Nara, Japan. This paper has been submitted to the IEEE Transactions on Nuclear Scienc