Read about latest updates related to ROXANNE project

Highlights from ROXANNE's first Field Test

last modified 2020-10-23T09:25:42+02:00

On the 30th of September 2020, we successfully conducted the first field test of ROXANNE. This field test was first of a three series Field Test events which will be held during the three-year lifetime of the project spanning from September 2019 to August 2022. This event was attended by more than 90 individuals, bringing together representatives from the law enforcement, technology experts, policymakers, and research community from all over Europe.

Read More…

ROXANNE's first field test sheduled for 30th September 2020

last modified 2020-09-08T12:40:07+02:00

ROXANNE’s first field test will take place on 30th of September, where a wide group of end users, namely Law Enforcement Agencies (LEAs), Stakeholder Board members, Ethics Board members as well as DG Home experts, will provide input and feedback on the platform. This field test will focus on Speech and Text Analytics with preliminary Network Analysis. During this test, training activities as well as evaluation sessions will be conducted to ensure a well-rounded assessment for further analysis and development of ROXANNE platform.

Read More…

ROXANNE’s clustering with other security projects

last modified 2020-09-07T08:35:08+02:00

As part of an initiative led by Trilateral Research, ROXANNE has joined a cluster of security projects along with CC-DRIVER, COPKIT, DARLENE, INSPECTr, PREVISION, PROTAX, and RAYUELA. The coordinators of these projects are collaborating on shared issues and topics of interest. This allows the projects to help each other in achieving greater impact and knowledge dissemination both within the projects themselves and through their networks.   This cluster also intends for the project partners to invite each other to their events in order to share ideas and results looking forward to future research collaboration. These collaborations will enable the projects to work together and collect different perspectives on tackling common issues in order to collaborate on joint solutions. This collaboration could span research on technical, ethical, legal, and data protection issues, amongst others.

Read More…

Consortium Meeting on 24-25 Aug 2020

last modified 2020-09-04T10:59:56+02:00

The ROXANNE consortium meeting held virtually on 24-25 August 2020 and attended by the 24 partners including LEAs and SMEs from 16 countries. The two days consortium meeting started with a short presentation by each of the partners about their contribution to the ROXANNE project in the last 4 months and the plan for the next 6 months. Apart from the technical presentation by each of the work package leaders for their respective packages, project board meeting, the consortium meeting discussed the planning for the upcoming ROXANNE field test event schedule by the on 30th September 2020 (Please email us if you would be interested in attending the same).

Read More…

Robust link prediction in criminal networks: A case study of the Sicilian Mafia

last modified 2020-07-16T16:18:33+02:00

Roxanne will include link prediction algorithms to enhance criminal network analysis by law enforcement agencies. A recently published study has explored the robustness of different link prediction strategies across different types of network data.

Read More…

ROXANNE Project at Nicosia Risk Forum 2020

last modified 2021-02-22T11:00:04+01:00

Nicosia Risk Forum is an innovative event for the area of South-Eastern Europe, which brings together academic, industrial, governmental, policy, and other societal stakeholders with a significant interest in societal safety. Nicosia Risk Forum 2020 was organized under the auspices of HE the Minister of Foreign Affairs of the Republic of Cyprus Dr. Nikos Christodoulides. Understandably, due to Co-Vid19 restrictions, #NRF2020 took place virtually on the 26th of November 2020. This year’s theme of #NRF2020 focused on “Regional Collaboration in Societal Safety”.

Read More…

Establishing collaboration with LOCARD project

last modified 2021-02-22T11:21:59+01:00

ROXANNE is in touch with LOCARD H2020 EU project, a lot of similar requirements and challenges are targeted by both the consortia. Specifically, ROXANNE aims to learn more about recent work published by the LOCARD project on “Large-scale analysis of grooming in modern social networks”.

Read More…

ROXANNE's second field test is coming in October!

last modified 2021-07-27T10:18:36+02:00

When? Friday, October 8, 2021, from 9 AM to 5 PM CET | Where? Netherlands Forensic Institute (NFI), The Hague, The Netherlands | How? Hybrid - you will be able to attend the meeting online as well as on-site (subject to the COVID-19 restrictions).

Read More…



Read more about different aspects and implications of this project
Ηow organized crime and cybercrime altered during the COVID-19 period
by Garg, Shivam — last modified Jul 28, 2021 10:07 AM

The COVID-19 pandemic is expected to have a multifaceted impact on serious organized crime, particularly cybercrime. Lifestyle changes that arose in response to the restrictions during the epidemic, such as extended teleworking, widespread internet purchasing, and other behaviors, are unlikely to fade once the lockdown is lifted. As a result, cybercriminals will continue to seek ways to exploit these behaviors, either by modifying existing attacks or developing new ones.

Dissemination & exploitation efforts in project ROXANNE
by Garg, Shivam — last modified May 31, 2021 10:43 AM

ROXANNE project has completed about half of its journey until now. We are happy to share that with the support, feedback, and comments of our readers, stakeholders, end-users, and partners, we have achieved to create a preliminary version of this unique platform. We are certain that this platform will be used ethically for the betterment of society and we are ensuring checks for the same at various steps as well. In this blog, we will discuss some of the recent project updates and explore our efforts and objectives with respect to exploitation.

NLP technologies against online crime
by Garg, Shivam — last modified Apr 27, 2021 09:41 AM

Big Data in Artificial Intelligence (AI) and Machine Learning (ML) technologies offer new opportunities. The principle is that an extensive amount of data is required for the best result of the scenario of fighting crime ML models. In the ROXANNE project, the technical development targets to significantly enhance the criminal network analysis based on text, speech, language, and video technologies.

ROXANNE Stakeholder Board
by Garg, Shivam — last modified Apr 01, 2021 11:00 AM

As an EU-funded collaborative research and innovative project, ROXANNE has been accompanied since its launch by a Stakeholder Board (SB) for independent and methodological advice, counseling the consortium on the practical implementation of its goals, as well as on encountered issues regarding its progress, direction, and outcomes. This external project advisory group is formed of 16 interdisciplinary experts coming from diverse backgrounds, including law enforcement, academia, EU entities, international organisations, fellow research projects, and industry.

Multimodal networks integration improves the criminal entity network construction with the help of deep neural networks
by Garg, Shivam — last modified Mar 01, 2021 09:12 AM

The network integration fuses information from ROXANNE platform component technologies for network analysis. In previous workloads, crime-related networks from different data sources are constructed. We propose a multilayer and cross-network structural analysis to provide methods for integrating information from several investigation cases and linking the data records across these.

Making Natural Language Processing work for Little Training Data
by Garg, Shivam — last modified Feb 22, 2021 11:07 AM

In the ROXANNE project we are solving real-world problems which often do not have a large labelled training set. To overcome such data scarcity problems, we use the combination of distant supervision and noise-robust learning algorithms. Distant supervision serves as a way of obtaining a large amount of labelled data in an automatic manner. Such data is however often noisy so that feeding them directly to DNN models will hinder the learning process. Nonetheless, noise-robust learning algorithms will help the models to focus on the correct instances in the training set so that the models will not be affected much by the noise.

The Benefits of Using Automatic Speaker Recognition in LEAs’ Investigative Processes
by Garg, Shivam — last modified Feb 22, 2021 10:46 AM

Traditional manually performed forensic analyses are language-dependent and time-consuming, while automatic speaker recognition systems are fast and language-independent (nevertheless, the role of a forensic expert is still irreplaceable for the presentation of the results). There is also other voice biometric information that can be automatically extracted from a person’s voice, such as the gender of a speaker. The bottom line is that current automatic speaker recognition systems, such as the one currently built by the ROXANNE consortium, can greatly improve the analytical work efficiency, enabling law enforcement agencies of any size to investigate faster.

Probabilistic modelling for speaker recognition in criminal networks
by Garg, Shivam — last modified Feb 05, 2021 04:01 PM

Speaker recognition is a technology that uses computer algorithms to analyze speech patterns and determine the identity of the speaker in a recording. Speaker recognition is an integral part of the ROXANNE platform because the identities of speakers in recordings from criminal investigations are usually not known. However, the speaker recognition scenario in criminal investigations differs from the most other speaker recognition scenarios because in addition to the audio of the recordings, we also have access to information about how the recordings are related. In particular, information about who has talked to whom is important. This information forms a network structure between the recordings. Naturally, it is important for the investigation to accurately uncover the network structure. Interestingly, using prior knowledge about the expected network structure in criminal networks may also improve the accuracy of speaker recognition.

Technology to enhance forensic speaker analysis
by Garg, Shivam — last modified Feb 05, 2021 04:01 PM

Law enforcement agencies investigate criminal networks to find participants, understand their role in the network and, eventually, collect evidence for prosecution. Opportunities to identify criminals often lie in the traces that their communication leaves behind. A cell phone leaves many different traces, but the availability and usability of these modalities may vary. Therefore, it is worthwhile to invest in multiple modalities, increasing the chance of a useful result.

Ethics Oversight in ROXANNE
by Garg, Shivam — last modified Feb 05, 2021 04:02 PM

Ethics oversight in ROXANNE exists across four levels: the European Commission Ethics Checks; the External Ethics Board; the Internal Ethics Board; ethics-focussed work within the project. Overall, the ROXANNE project is in a positive position in terms of meeting the strict ethical requirements from the Commission. So far, the project is also fulfilling the recommendations generated within the project to ensure compliance with ethical, societal, and legal standards. The strict oversight that the ROXANNE project is subject to ensures that none of these standards are violated in the work of the project. The ROXANNE consortium is committed to ensuring that the ROXANNE project is carried out in a responsible way, and that the technologies developed are used in an ethical and lawful manner.

Link prediction algorithms to enhance criminal network analysis
by Garg, Shivam — last modified Feb 05, 2021 04:02 PM

Roxanne project will include link prediction algorithms to enhance criminal network analysis by law enforcement agencies. A recent study shows that link prediction can predict links among criminals, although the effectiveness and accuracy of the prediction may be affected by the amount of unknown information and the specific type of relational data under analysis

Ethically developed technologies for safer societies – The ROXANNE project case study
by Garg, Shivam — last modified Feb 05, 2021 04:02 PM

In order to implement an approach that incorporates ethical and legal concerns in ROXANNE, there are two research focuses that specifically deal with ethical and legal concerns which are led by Trilateral. The first area of focus ensures that the research carried out during the ROXANNE project abides by the standards of research ethics and that data protection legislation is applied to training algorithmic models used in the platform. A second research focus considers the issues which ROXANNE could raise in terms of ethics, societal values, fundamental rights, and applicable law if it is used in real investigations.

Overview of LTEC Voice Databases & ASR System Training
by Garg, Shivam — last modified Feb 05, 2021 04:02 PM

The main problem in the application of ASR systems in forensics is the accuracy and reliability of the results of such system. The accuracy of identification methods depends on a number of factors that cannot always be assessed. Since it is very difficult to assess the impact of all the factors encountered in forensic speaker examinations, the performance of such systems can best be determined using voice databases developed on the basis of audio recordings submitted for examinations. Despite the variety of created voice databases that attempt to record voices under a variety of conditions, forensic investigations still encounter factors, whose impact on an automated speaker recognition system, is often unknown. ROXANNE BLOG briefly presents characteristics of voice databases - BALSAS_LTv1.1 and BALSAS-200LT of the Forensic Centre of Lithuania (LTEC), also describes ASR VOICE training performance using BALSAS_LTv1.1. In the ROXANNE project, LTEC will use the described voice databases (BALSAS_LT200 and BALSAS_LTv1.1) to assess the recognition accuracy of the existing ASR systems VOICE and BATVOX, as well as the ones developed internally.

Forensic Automatic Speaker Recognition (FASR) : Problems and prospects
by Garg, Shivam — last modified Feb 05, 2021 04:02 PM

At present speaker identification by voice in forensics, criminalistics and other applications receive a great deal of attention and huge financial resources. In many cases, this is due to the increasing use of sound recording devices, and in particular, the widespread use of mobile technologies in criminal activities and their recordings, and accordingly, the use of various latest trending technologies in the fight against organised crime and international terrorism. In the ROXANNE project, speaker recognition is one of the main and most important elements of the system. However, direct application of automatic speaker recognition (ASR) systems in forensics raises a number of issues. In general, ASR methods work well only under controlled conditions, sufficiently good signal quality and relatively long duration. The main problem in the application of ASR systems in forensics is the accuracy and reliability of the results of such system. This blog briefly describes problems arising using this systems in forensic speaker identification, and prospects of effective using ASR system with traditional auditory-instrumental methods.

Automatic Speech Recognition: Setting, Benefits and Limitations
by Garg, Shivam — last modified Feb 05, 2021 04:02 PM

Audio is an important modality for criminal investigations. This is true for different kinds of audio and in particular for spoken content. Be it a part of files, streams or posts which are accessible on the web and social media, a recording collected from mobile devices for investigations and interviews, or a conversation recorded via intercepted telephone calls - speech can be encountered in many environments. Audio data by itself, however, presents unstructured information. Without having access to the spoken content, no further analysis and processing is possible. Enter Automatic Speech Recognition (ASR).

Legally compliant state-of-the-art capabilities to fight and prevent transnational crimes
by Garg, Shivam — last modified Feb 05, 2021 04:02 PM

With the increased reliance on new and rapidly evolving technologies to commit and facilitate crime, law enforcement agencies (LEA) must keep pace with the constant technological developments to stay ahead of criminals and maintain a safe environment. The ROXANNE advanced technical platform aims to enhance the quality of investigative work in tracking and identifying criminals by developing an innovative solution that combines speech, text and video data analysis with the analysis of organized crime networks. To be effective and lawfully implemented, such innovative police technologies must be part of an appropriate legal framework based on the principle of law, fundamental human rights and other applicable legislation ( Often innovative fields, such as data analysis for law enforcement purposes and the use of novel analytical methods, are subject to legal uncertainty due to outdated legal texts or insufficient guidance from legislators, be it domestic or regional)

Forensics Visualizations as a catalyst for fighting organized crime
by Garg, Shivam — last modified Feb 05, 2021 04:03 PM

Criminals often employ sophisticated technologies in planning and executing their illegal activities, as well as concealing the revenues stemming from them. Suppressing organized crime remains an important but challenging task for Law Enforcement Agencies (LEAs) for several reasons. In this context, visualisation plays a key role in augmenting the human analysis and providing context to the analyst.

ROXANNE platform & network analysis
by Garg, Shivam — last modified Feb 05, 2021 04:03 PM

Maximizing the speed of investigations is one of the key factors in the presence of dynamically changing and technologically savvy organized criminals. A number of automated network analysis methods were developed in the past that can be borrowed to help investigators to identify key players, paths and relations within the resulting networks in order to analyse the development of the network, find effective strategies toward its destabilisation or disruption and overall to increase investigation effectiveness.

Combination of Speech and Text Technologies with Criminal Network Analysis: Steps Toward First Field-Test Event of ROXANNE Project
by Garg, Shivam — last modified May 11, 2020 01:41 PM

For law enforcement agencies (LEAs) to keep up in this new environment, they must change their approach to criminal investigations as relying mainly on physical evidence and witness statements is no longer sufficient in many cases. Training in research-based investigative procedures and access to related tools and resources can help law enforcement officers carry out successful investigations. It can help LEAs solve cases more swiftly and even prevent crimes in some cases.

Artificial Intelligence Adoption in Law enforcement
by Garg, Shivam — last modified Apr 28, 2021 09:10 AM

The ROXANNE project has a principal objective to enhance the LEAs’ efforts to discover criminal networks and identify their members. It has capitalised on certain aspects of AI technologies. Speech and language technologies (SLTs), visual analysis (VA) and network analysis (NA) will become the basis of ROXANNE platform, which will enhance criminal network analysis capabilities by providing a framework for extracting evidence and actionable intelligence.

A Generic and Flexible Platform for ROXANNE Systems Development
by Garg, Shivam — last modified Jan 15, 2020 07:14 AM

Airbus has designed its Multi-source and Multi-media analysis solution through the Concept of Generic Architecture which enables the regrouping of multimedia processing software products and presenting them in different possible configurations, based on one common and generic architecture.

Project kick-off meeting
by admin — last modified Nov 13, 2019 08:46 AM

The project kick-off meeting was held at Idiap Research Institute, in Martigny Switzerland, on 3-4 September 2019.