Secure blockchain technologies

In the recent years, blockchain technologies have shown promise as infrastructure for decentralized trustless anonymous digital asset exchange. The technology promises to transform how the data is shared in many areas including financial sector, insurance and gaming industries. Yet several obstacles prevent mainstream adoption of this technology – one of these challenges is security. To […]

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A Realistic Machine Learning-based Model for Failure Prediction and Propagation in Smart Grid Networks

Cyber-Physical Systems (CPS) combine communication and information technology functions to the physical components of a system for purposes of monitoring, controlling, and automation. The power grid is becoming one of the largest CPS, where grid components are controlled based on the synergies in the cyberspace. CPS hold a great promise to improve the efficiency and […]

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Crowdsensing-based Wireless Indoor Localization using an Innovative AI & ML Algorithm

Smartphone based indoor navigation services are desperately needed in an indoor GPS-denied environment, such as in Combat-zone Surveillance, Health Monitoring, Fire Detection, etc. The Receive Signal Strength (RSS) based algorithms are commonly used in indoor localization, which rely on the WiFi fingerprint data built by the Mobile Crowdsensing approach. Conventional statistical and probability techniques are […]

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Ensemble-based Dimensionality Reduction Model for Wireless Time-Series

The new wireless network technology will provide users with a higher communication quality. However, we will face two critical problems: the wireless traffic will increase considerably, and the wireless signals will contain noise. The Wifi signals are represented as time series, but processing and removing noise from such huge-volume, high-dimensional and complex data pose great […]

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AI-Blockchain integration to ensure explainability, accountability, traceability and reproducibility (EATR) in mission critical systems

This project is an effort to integrate two of the emerging technologies of our time, i.e., Artificial Intelligence and Blockchain. The purpose of this integration is to overcome the drawbacks of individual technologies and work in coherence for mutual benefits. Most of the current AI systems currently deployed are black boxes and they do not […]

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Anomaly detection using AI/ML for Network Correction

Anomaly detection or outlier detection is a technique to identify rare items, observations or events which are differing significantly from most of the data or do not conform to the expected behavior of the system. Typically, anomalous data cause numerous problems in the computer networking and communication system. This project aims to develop an advanced […]

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Creative Artificial Intelligence in Interactive Mobile Systems

The large amount of information available today on the web brings many challenges to the information retrieval and artificial Intelligence communities. Moreover, personalization is a key component in today’s successful mobile websites and interactive applications. In order to be effective, these websites are required to provide visitors with the information they need without the complexity […]

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IoT device fingerprinting and anomaly detection using ML

The number of Internet of Things (IoT) devices is expected to reach 50 billion devices by 2020 and the devices are increasingly diverse. They are disrupting traditional security measures. Mobile Network Operators (MNOs) have limited control over customers’ IoT devices, as they are deployed on the customer premises. MNOs need to deploy effective security controls […]

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NetRepAIr: Making networks reliable for next-generation applications using AI/ML techniques

Networks have grown from small topologies connecting a dozen of devices to large, shared infrastructures supporting primary needs of our society. Today, we count on networked services for trading, commuting, monitoring weather conditions, meeting people. In order to provide reliable services, network operators need to cope with the daunting challenge of ensuring millions of flows […]

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Just-In-Time Scaling of Cloud Based Video Games using Machine Learning

Ubisoft’s cloud-based video game ecosystems experience the workload up to 5+ millions players in a typical week. Workloads on game servers are of different scales, ranging from tens of clients per game server to thousands of clients for traditional workloads. To guarantee game player user experience, a pool of servers is launched to react to […]

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Détection de l’état de « flow » en temps réel par électroencéphalographie et apprentissage machine durant une expérience ludique

Les amateurs de jeu vidéo sont bien familiers avec la sensation d’être profondément captivés par un jeu au point de perdre la notion du passage du temps, tout en état capables de hautes performances sans se fatiguer mentalement. Cet état psychologique particulier a été baptisé « flow » par le psychologue hongrois Mihaly Csikszentmilhayi qui […]

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