Intrusion Detection Systems in SDN-based Self-Healing PMU Networks

Nowadays, Power grids are critical infrastructures on which everything else relies, and their correct behavior is of the highest priority. New smart devices are being deployed to be able to manage and control power grids more efficiently and avoid instability. However, the deployment of such smart devices like Phasor Measurement Units (PMU) and Phasor Data Concentrators (PDC), open new opportunities for cyber attackers to exploit network vulnerabilities. If a PDC is compromised, all data coming from PMUs to that PDC is lost, reducing network observability. Our approach to solve this problem is to develop an Intrusion detection System (IDS) in a Software-defined network (SDN). allowing the IDS system to detect compromised devices and use that information as an input for a self-healing SDN controller, which redirects the data of the PMUs to a new, uncompromised PDC, maintaining the maximum possible network observability at every moment. During this research, we have successfully implemented Self-healing in an example network with an SDN controller based on Ryu controller. We have also assessed intrinsic vulnerabilities of Wide Area Management Systems (WAMS) and SCADA networks, and developed some rules for the Intrusion Detection system which specifically protect vulnerabilities of these networks. The integration of the IDS and the SDN controller was also successful. \\To achieve this goal, the first steps will be to implement an existing Self-healing SDN controller and assess intrinsic vulnerabilities of Wide Area Measurement Systems (WAMS) and SCADA networks. After that, we will integrate the Ryu controller with Snort, and create the Snort rules that are specific for SCADA or WAMS systems and protocols.

A note on collusion sustainability with optimal punishments and detection lags

In this note we characterize optimal punishments with detection lags when the market consists of n oligopolistic firms. We extend a previous note by Colombo and Labrecciosa (2006) [Colombo, L., and Labrecciosa, P., 2006. Optimal punishments with detection lags. Economic Letters 92, 198-201] to show how in the presence of detection lags optimal punish- ments fail to restore cooperation also in markets with a low number of firms.

Dynamics of pneumococcal nasopharyngeal carriage in healthy children attending a day care center in northern Spain. Influence of detection techniques on the results

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Detection of Atomic Scale Changes in the Free Volume Void Size of Three-Dimensional Colorectal Cancer Cell Culture Using Positron Annihilation Lifetime Spectroscopy

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Proof of Concept of Impact Detection in Composites Using Fiber Bragg Grating Arrays

Impact detection in aeronautical structures allows predicting their future reliability and performance. An impact can produce microscopic fissures that could evolve into fractures or even the total collapse of the structure, so it is important to know the location and severity of each impact. For this purpose, optical fibers with Bragg gratings are used to analyze each impact and the vibrations generated by them. In this paper it is proven that optical fibers with Bragg gratings can be used to detect impacts, and also that a high-frequency interrogator is necessary to collect valuable information about the impacts. The use of two interrogators constitutes the main novelty of this paper.

Molecular Techniques for Dicistrovirus Detection without RNA Extraction or Purification

Dicistroviridae is a new family of small, nonenveloped, and +ssRNA viruses pathogenic to both beneficial arthropods and insect pests as well. Triatoma virus (TrV), a dicistrovirus, is a pathogen of Triatoma infestans (Hemiptera: Reduviidae), one of the main vectors of Chagas disease. In this work, we report a single-step method to identify TrV, a dicistrovirus, isolated from fecal samples of triatomines. The identification method proved to be quite sensitive, even without the extraction and purification of RNA virus.

Query-by-Example Spoken Term Detection ALBAYZIN 2012 evaluation: overview, systems, results, and discussion

Query-by-Example Spoken Term Detection (QbE STD) aims at retrieving data from a speech data repository given an acoustic query containing the term of interest as input. Nowadays, it has been receiving much interest due to the high volume of information stored in audio or audiovisual format. QbE STD differs from automatic speech recognition (ASR) and keyword spotting (KWS)/spoken term detection (STD) since ASR is interested in all the terms/words that appear in the speech signal and KWS/STD relies on a textual transcription of the search term to retrieve the speech data. This paper presents the systems submitted to the ALBAYZIN 2012 QbE STD evaluation held as a part of ALBAYZIN 2012 evaluation campaign within the context of the IberSPEECH 2012 Conference(a). The evaluation consists of retrieving the speech files that contain the input queries, indicating their start and end timestamps within the appropriate speech file. Evaluation is conducted on a Spanish spontaneous speech database containing a set of talks from MAVIR workshops(b), which amount at about 7 h of speech in total. We present the database metric systems submitted along with all results and some discussion. Four different research groups took part in the evaluation. Evaluation results show the difficulty of this task and the limited performance indicates there is still a lot of room for improvement. The best result is achieved by a dynamic time warping-based search over Gaussian posteriorgrams/posterior phoneme probabilities. This paper also compares the systems aiming at establishing the best technique dealing with that difficult task and looking for defining promising directions for this relatively novel task.

A Self-Referencing Intensity Based Polymer Optical Fiber Sensor for Liquid Detection

A novel self-referencing fiber optic intensity sensor based on bending losses of a partially polished polymer optical fiber (POF) coupler is presented. The coupling ratio (K) depends on the external liquid in which the sensor is immersed. It is possible to distinguish between different liquids and to detect their presence. Experimental results for the most usual liquids found in industry, like water and oil, are given. K value increases up to 10% from the nominal value depending on the liquid. Sensor temperature dependence has also been studied for a range from 25 degrees C (environmental condition) to 50 degrees C. Any sector requiring liquid level measurements in flammable atmospheres can benefit from this intrinsically safe technology.