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Secure 5G Core Network Slicing in Support of IoT Application

The key motivation for this work is that future smart services (e.g. IoT applications) will have competing and perhaps conflicting networking performance requirements. These services will also require flexible and agile deployment. 5G networks, an essential component of future virtualized infrastructures, deal with this issue - in part - by relying on network slicing. To define a network slice, one has to consider the allocation of recourses - both in the radio and core parts - of the 5G network to form a logical entity where a service could be deployed. Network slicing has emerged as a key-enabler for proving heterogeneous services. It takes advantage of the virtualization elements of future networking infrastructures where multiple services can be hosted on the same physical infrastructure.

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Resource augmentation in Mobile Cloud Computing

In this research, we address resourced-constrained mobile devices' ability to get computing support from external sources. This could enhance the performance of their applications and extend their battery life by resource augmentation techniques where more powerful computing sources support the mobile devices. We investigate this in the context of both Cyber Foraging Systems where supporting computing sources exist within the local network and Mobile Cloud environment where these sources exist in the cloud.

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Analysis of Adversarial Attacks in Network Security

This project enables us to demonstrate the effects of adversarial samples on deep learning-based intrusion detection systems within the context of IoT networks. Our experimental results illustrate the vulnerability of deep learning-based intrusion detection systems. It also provides a performance comparison between the feed forward neural networks and the self-normalizing neural networks. Finally, the effect of feature normalization on the adversarial robustness of deep learning based intrusion detection systems is analyzed.

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Location Verification on the Internet

This research aims at verifying location claims of Internet clients. A wide spectrum of location-sensitive Internet applications could benefit from verifying location assertions. To that end, we designed Client Presence Verification (CPV), a delay-based mechanism by which a location assertion could be verified to a certain degree of granularity. When a location is asserted, three verifiers measure round-trip and one-way delays between themselves and the client. The verifiers then corroborate, based on the measured delays, the client's physical presence inside the triangle determined by their geographic locations.

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Adaptive SDN Controllers

In this project, we introduce the use of adaptive controllers into software-defined networking (SDN), and propose the use of adaptive consistency models in the context of distributed SDN controllers. These adaptive controllers can tune their own configurations in real-time in order to enhance the performance of the applications running on top of them.

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SDN Dataplane Simulator

Details to follow.

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Security of 6LoWPAN layer in Internet-of-Things

Details to follow.

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