3rd WORKING GROUPS & MC MEETING
The 3rd Working Groups Meeting will be held on October 23-24, 2019 in La Valleta (Malta), Valleta Campus, St Paul Street. The day after, on October 25th, the 3rd Management Committee (MC) will take place.
Registration for the lunch (Deadline October 15th)
3rd Working Groups Meeting – Call For Abstracts
One of the goals of the 3rd Working Groups Meeting (WGM3) is to present the results of the work with a list of synthetic dataset. These studies will stimulate the creation of synergies among the participants in the Action.
We invite scientific publications up to six pages, which may be submitted in PDF via the Easychair system below:
Authors are requested to follow the formatting instructions for the Springer LNCS style
Deadline: The deadline for submitting the shows of interests and an abstract will be September 2nd.
The study of the challenge that annually DFRWS proposes could be interesting. For that, the constitution of a multidisciplinar research group for solving this challenge can be very interesting for the Action.
Goal: Create multidisciplinar research groups among the participants in the Action in order to apply the mathematical, AI and AR tools in order to find a solution to the challenge of the next year.
Besides this problem, other datasets have been proposed. The goal for the next datasets is the following: Individual research groups with competences to study one or several dataset will select at least one and it will present its results during WGM3.
The IARPA Janus Benchmark-C face challenge (IJB-C) defines eight challenges addressing verification, identification, detection, clustering, and processing of full motion videos. This
is supported by the IJB-C set of 138000 face images, 11000 face videos, and 10000 non-face images. This dataset can be requested at the links below:
A paper about this dataset can be found here.
The aim for this dataset is the malware classification: http://tracker.virusshare.com:6969/
London Crime Data 2008-2016
Crime in major metropolitan areas, such as London, occurs in distinct patterns. This data covers the number of criminal reports by month, LSOA borough, and major/minor category from Jan 2008-Dec 2016. It can be found at the link below:
Kaggle Paysim1 (payment simulator)
Synthetic Financial Datasets For Fraud Detection.
Synthetic datasets generated by the PaySim mobile money simulator. PaySim uses aggregated data from the private dataset to generate a synthetic dataset that resembles the normal operation of transactions and injects malicious behaviour to later evaluate the performance of fraud detection methods. This dataset can be downloaded at the link below: