AIDA presented to PhD students

AIDA presented to PhD students INESC TEC, one of AIDA’s partners, presented AIDA to the Doctoral Program in Computer Science (MAP-I)’S first year students. This visit, which took place on December 6, 2022, happened during a visit to the High-Assurance Software Laboratory from INESC TEC at the University of Minho. This was an opportunity to present the work carried out by the AIDA project and get to know a good example of international collaboration between industry and academia. It is important to mention that the initiative was also an opportunity to share the project’s vision and expected outcomes, while promoting […]

Read More

AIDA Research on Suspicious Behavior and Anomaly Detection

AIDA Research on Suspicious Behavior and Anomaly Detection One of the goals of the AIDA Project is to investigate and identify new ways to help Analysts find Anomalous Behavior (of any kind) in large and complex pools of data. We hope this can ultimately lead to significant improvements in the detection of fraudulent activity occurring on Telecom Networks, especially in the light of new technologies like 5G already expanding on the market. Moreover, we now see over more sophisticated, complex and robust methods being used for committing fraud on Telecomm Networks but also increasingly expanding to the world of Communication […]

Read More

AIDA participated in the CMU Portugal Summit 2022

AIDA participated in the CMU Portugal Summit 2022 Pedro Fidalgo, from our coordinator partner Mobileum, participated in the roundtable “Adaptive, automated, and autonomic computing” at this year’s CMU Portugal Summit, which happened under the motto “New Frontiers in tech”.  During the conference, the AIDA project had a meeting with the CMU Portugal External Review Committee, an advisory board charged with assessing the project’s performance and making recommendations.    The conference aimed at bringing experts to present research progress in various areas, such as Health, Cybersecurity, Forests, Artificial Intelligence, Language Technologies, Machine Learning, among others. The CMU Portugal Summit 2022 took place […]

Read More

Protecting the Security and Privacy of AIDA and its Data

Protecting the Security and Privacy of AIDA and its Data Adapting the RAID platform comes with many security and privacy issues that need to be addressed. These issues appear mainly due to the transition to an edge architecture, which imposes the use of computation resources at the edges of the network, but also due to the need of supporting multiple tenants and network slicing with 5G technology. As mobile phones connect and disconnect, the network is always changing, requiring adaptation and monitorization tools to be used to maximize resources. And since the complexity of the system increases, attackers have more […]

Read More

Fraud detection, micro-clusters and scatterplots

Fraud detection, micro-clusters and scatterplots   Acknowledgements The results and analysis presented here were done with contributions from Mirela Cazzolato (USP, and CMU), Saranya Vijayakumar (CMU), Xinyi (Carol) Zheng (CMU), Meng-Chieh (Jeremy) Lee (CMU), Namyong Park (CMU), Pedro Fidalgo (Mobileum), Bruno Lages (Mobileum), and Agma Traina (USP). Reminders – Problem definition and past insights As we mentioned in the February 2022 blog post, the problem we are focusing on is to spot fraudulent behavior in a who-calls-whom-and-when graph. We distinguished between the supervised case (where we are given a list of fraudulent subscribers (labeled data)), and the un-supervised one, where […]

Read More

AIDA paper presents a mechanism that ensures better performance and reduces costs in IoT devices

AIDA paper presents a mechanism that ensures better performance and reduces costs in IoT devices “Adaptive Database Synchronization for an Online Analytical Cloud-to-Edge Continuum” is the new paper of the AIDA project, which was presented this week at the ACM Dependable, Adaptive, and Secure Distributed Systems (DADS 2022).  Internet of Things devices are generally underpowered, but they exist in large volumes and are located very close to where the data is captured. The use of these devices is increasingly common in the industry, agriculture, running cities, and even at homes. Because of their limitations, the data is traditionally transferred periodically to […]

Read More

Federated Machine Learning

Federated Machine Learning Federated Learning (FL) is a collaboratively decentralized privacy-preserving technology to overcome the challenges of data storage and data sensibility [1]. The last few years have been strongly marked by artificial intelligence, machine learning, smart devices, and deep learning. As a result, two challenges arose in data science, impacting how data can be accessed and used. First, with the creation of the General Data Protection Regulation (GDPR) [2], the data became protected by the regulation. Institutions cannot store or share data without users’ authorization. Another challenge is that in the era of big data, a large volume of […]

Read More

Finding Anomalies in Large Scale Graphs

Finding Anomalies in Large Scale Graphs   Problem definition Given a large, who-calls-whom graph, how can we  nd anomalies and fraud? How can we explain the results of our algorithms? This is exactly the focus of this project. We distinguish two settings: static graphs (no timestamps), and time-evolving graphs (with timestamps for each phone). We further subdivide into two sub-cases each: supervised, and unsupervised. In the supervised case, we have the labels for some of the nodes (‘fraud’/’honest’), while in the unsupervised one, we have no labels at all. Major lessons For the supervised case, the natural assumption is that […]

Read More

A Data Management Architecture for AIDA

A Data Management Architecture for AIDA One of the major challenges in the evolution of the RAID platform during the AIDA project is the need to further distribute the platform components to achieve greater levels of scalability, by leveraging the increasing edge computing capacity made available by the IoT and the imminent large-scale deployment of 5G cellular technology.   The advent of 5G networks and growing adoption of Internet of Things (IoT) devices lead to more opportunities for data collection and processing with hybrid edge-cloud systems.   In this architecture, edge devices — placed near where the data is being […]

Read More