Special Issue "Predictive Analytics and Illicit Activities"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Systems".

Deadline for manuscript submissions: 31 May 2021.

Special Issue Editor

Prof. Dr. Josiane Mothe
E-Mail Website
Guest Editor
Institut de Recherche en Informatique de Toulouse, Université de Toulouse, 31400 Toulouse, France
Interests: information retrieval and access; information mining and applied machine learning; weak signal and outlier detection

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the use of advanced techniques to mine and exploit heterogeneous digital data on illicit activities for descriptive or predictive analyses.

Digital technologies as well as digital information and communication networks facilitate illicit activities such as illicit financial flows, illicit art and drug markets, forbidden posts and comments on social media, and recruitment or incitement of illicit activities such as any form of radicalization, etc. New models, methods and tools need to be developed to prevent, detect or warn, and possibly mitigate or hinder these illicit actions.

These methods encompass machine learning or data mining models as well as visualization models to help in detecting or mitigating possible illicit activities.

This Special Issue aims to gather both research papers reporting new scientific results and technical papers reporting project results, demos/prototypes/tools.

This Special Issue invites submissions covering, but not limited to, the following topics:

- Crime detection and investigation;
- Risk analysis;
- Misinformation and misbehavior analysis and detection;
- Trend detection, analysis and tracking;
- Weak signal detection;
- Information / opinion / knowledge spread and modelling;
- Information quality in social network;
- Community detection, expertise and authority discovery;
- Social influence, recommendation and media;
- Behavior analysis in social networks;
- Sentiment analysis;
- Network visualization and modeling;
- Data mining and machine learning;
- Real-world case studies;
- Ongoing projects based on social media and/or social networks;
- Ethics.

Prof. Dr. Josiane Mothe
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • crime detection and investigation
  • risk analysis
  • misinformation and misbehavior analysis and detection
  • trend detection, analysis and tracking
  • weak signal detection
  • information/opinion/knowledge spread and modelling
  • information quality in social network
  • community detection
  • expertise and authority discovery
  • social influence, recommendation and media
  • behavior analysis in social networks
  • sentiment analysis
  • network visualization and modeling
  • data mining and machine learning
  • real-world case studies
  • ongoing projects based on social media and/or social networks
  • ethics

Published Papers (1 paper)

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Research

Open AccessArticle
An Advanced Abnormal Behavior Detection Engine Embedding Autoencoders for the Investigation of Financial Transactions
Information 2021, 12(1), 34; https://doi.org/10.3390/info12010034 - 16 Jan 2021
Viewed by 580
Abstract
Nowadays, (cyber)criminals demonstrate an ever-increasing resolve to exploit new technologies so as to achieve their unlawful purposes. Therefore, Law Enforcement Agencies (LEAs) should keep one step ahead by engaging tools and technology that address existing challenges and enhance policing and crime prevention practices. [...] Read more.
Nowadays, (cyber)criminals demonstrate an ever-increasing resolve to exploit new technologies so as to achieve their unlawful purposes. Therefore, Law Enforcement Agencies (LEAs) should keep one step ahead by engaging tools and technology that address existing challenges and enhance policing and crime prevention practices. The framework presented in this paper combines algorithms and tools that are used to correlate different pieces of data leading to the discovery and recording of forensic evidence. The collected data are, then, combined to handle inconsistencies, whereas machine learning techniques are applied to detect trends and outliers. In this light, the authors of this paper present, in detail, an innovative Abnormal Behavior Detection Engine, which also encompasses a knowledge base visualization functionality focusing on financial transactions investigation. Full article
(This article belongs to the Special Issue Predictive Analytics and Illicit Activities)
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