Model Checking of Software Defined Networks using Header Space Analysis

This thesis investigates the topic of verifying network status validity with a Cyber Security perspective. The fields of interest are dynamic networks like OpenFlow and Software Defined Networks, where these problems may have larger attack surface and greater impact. The framework under study is called Header Space Analysis, a formal model and protocol-agnostic framework that allows to perform static policy checking both in classical TCP/IP networks and modern dynamic SDN. The goal is to analyse some classes of network failure, declaring valid network states and recognizing invalid ones. HSA has evolved in NetPlumber, to face problems caused by high dynamics of SDN networks. The main difference between HSA and NetPlumber is the incremental way that the latter performs checks and keeps state updated, verifying the actual state compliance with the expected state defined in its model, but the concept is the same: declare what's allowed and recognize states violating that model. The second and main contribute of this thesis is to expand existing vision with the purpose of increasing the network security degree, introducing model-checking-based networks through the definition of an abstraction layer that provides a security-focused model-checking service to SDN. The developed system is called MCS (Model Checking Service) and is implemented for an existing SDN solution called ONOS, using NetPlumber as underlying model-checking technology, but it's validity is general, uncoupled with any kind of SDN implementation. Finally, the demo shows how some cases of well-known security attacks in modern networks can be prevented or mitigated using the reactive behavior of MCS

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Differentiation of post harvest date fruit varieties non-destructively using FT-NIR spectroscopy

The world production of dates has more than doubled over the last two decades. Presently, the industrial sorting of dates is a difficult operation, affected by a high level of losses. As a consequence, the objective of this article is to study the variety discrimination capabilities of Fourier Transform-Near Infrared (FT-NIR) reflectance spectroscopy for post-harvest sorting purposes. The same methodology was tested on six commercial date varieties named Estamaran, Kabkab, Mazafati, Piarom, Deglet nour and Zahedi. For each cultivar, 100 fruits were analysed using the FT-NIR spectrometer, subsequently characterised by destructive measurements. A multivariate analysis of the FT-NIR spectra appears a feasible tool for cultivar discrimination and even to estimate the soluble solid content (SSC) and dry matter (DM) of dates at their optimal harvesting conditions. FT-NIR, as a non-destructive techniques, could be a suitable way for on-line screening of different dates varieties