Sensing parasites: proteomic and advanced bio-detection alternatives

[EN] Parasitic diseases have a great impact in human and animal health. The gold standard for the diagnosis of the majority of parasitic infections is still conventional microscopy, which presents important limitations in terms of sensitivity and specificity and commonly requires highly trained technicians. More accurate molecular-based diagnostic tools are needed for the implementation of early detection, effective treatments and massive screenings with high-throughput capacities. In this respect, sensitive and affordable devices could greatly impact on sustainable control programmes which exist against parasitic diseases, especially in low income settings. Proteomics and nanotechnology approaches are valuable tools for sensing pathogens and host alteration signatures within micro fluidic detection platforms. These new devices might provide novel solutions to fight parasitic diseases. Newly described specific parasite derived products with immune-modulatory properties have been postulated as the best candidates for the early and accurate detection of parasitic infections as well as for the blockage of parasite development. This review provides the most recent methodological and technological advances with great potential for biosensing parasites in their hosts, showing the newest opportunities offered by modern “-omics” and platforms for parasite detection and control.

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.