Pub Date : 2019-04-01DOI: 10.1109/wacowc.2019.8770215
Rajashree Taparia, Samiksha Choyal
network will be in place. And, on top of all this, vital bee population will be encouraged to come back to where they belong. More information about the project here. Challenge-driven cooperation is a crucial shot to provide coherent and continuous cross-border dialogue and process including sustained awareness-raising of public authorities and policy-makers at regional/national level, capacity building, easy access to information and a friendly use of tools for mutual learning. This approach can contribute to mitigating local water crisis, a common challenge in the Mediterranean, through facilitating general access and promotion of best practices including the improvement of treated wastewater reuse as a non-conventional water resource (NCWR). Moreover, indication shows weakness in the multi-level governance and law enforcement, in planning, managerial and operational capacities, further than low-level involvement of the stakeholders in the decision-making process. MEDWAYCAP project will face these issues and address the final beneficiaries, to be equipped with state-of-the-art knowledge on NCWR techniques, management, planning and skills to reuse at territorial level for domestic and agricultural purpose thanks to the well organised capitalization platforms for networking and knowledge transfer and capacity building tool box. The project has been structured to: transfer and “upgrade” knowledge; reinforce newexisting networks & alliances; raise awareness among public authorities, policy- makers and “challenge owners” about NCWR measures and related opportunities for planning policies and related funding measures. More information about the project here. facilitate access and protect Intellectual Property Rights (IPR) to MSMEs will be reinforced. More information about the project here . sustainable hub and the development of win-win business partnerships in the Euro-Mediterranean region. More information about the project here.
{"title":"Table of Content","authors":"Rajashree Taparia, Samiksha Choyal","doi":"10.1109/wacowc.2019.8770215","DOIUrl":"https://doi.org/10.1109/wacowc.2019.8770215","url":null,"abstract":"network will be in place. And, on top of all this, vital bee population will be encouraged to come back to where they belong. More information about the project here. Challenge-driven cooperation is a crucial shot to provide coherent and continuous cross-border dialogue and process including sustained awareness-raising of public authorities and policy-makers at regional/national level, capacity building, easy access to information and a friendly use of tools for mutual learning. This approach can contribute to mitigating local water crisis, a common challenge in the Mediterranean, through facilitating general access and promotion of best practices including the improvement of treated wastewater reuse as a non-conventional water resource (NCWR). Moreover, indication shows weakness in the multi-level governance and law enforcement, in planning, managerial and operational capacities, further than low-level involvement of the stakeholders in the decision-making process. MEDWAYCAP project will face these issues and address the final beneficiaries, to be equipped with state-of-the-art knowledge on NCWR techniques, management, planning and skills to reuse at territorial level for domestic and agricultural purpose thanks to the well organised capitalization platforms for networking and knowledge transfer and capacity building tool box. The project has been structured to: transfer and “upgrade” knowledge; reinforce newexisting networks & alliances; raise awareness among public authorities, policy- makers and “challenge owners” about NCWR measures and related opportunities for planning policies and related funding measures. More information about the project here. facilitate access and protect Intellectual Property Rights (IPR) to MSMEs will be reinforced. More information about the project here . sustainable hub and the development of win-win business partnerships in the Euro-Mediterranean region. More information about the project here.","PeriodicalId":430931,"journal":{"name":"2019 4th International Conference on System Reliability and Safety (ICSRS)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134105499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-11DOI: 10.1109/ICSRS48664.2019.8987703
M. Slawinski, Andy Wortman
We classify .NET files as either benign or malicious by examining directed graphs derived from the set of functions comprising the given file. Each graph is viewed probabilistically as a Markov chain where each node represents a code block of the corresponding function, and by computing the PageRank vector (Perron vector with transport), a probability measure can be defined over the nodes of the given graph. Each graph is vectorized by computing Lebesgue antiderivatives of hand-engineered functions defined on the vertex set of the given graph against the PageRank measure. Files are subsequently vectorized by aggregating the set of vectors corresponding to the set of graphs resulting from decompiling the given file. The result is a fast, intuitive, and easy-to-compute glass-box vectorization scheme, which can be leveraged for training a standalone classifier or to augment an existing feature space. We refer to this vectorization technique as PageRank Measure Integration Vectorization (PMIV). We demonstrate the efficacy of PMIV by training a vanilla random forest on 2.5 million samples of decompiled. NET, evenly split between benign and malicious, from our in-house corpus and compare this model to a baseline model which leverages a text-only feature space. The median time needed for decompilation and scoring was 24ms. 11Code available at https://github.com/gtownrocks/grafuple
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