C2PS is organized into four research themes that are not independent, separately managed areas, but interacting research lines that correspond to the main components (device, networks, and edge/cloud- based intelligence) of the future CPS environments.
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Project Title |
Towards a Holistic Network Visual Sensing for Identification Management Scenarios in Cyber-Physical Environment |
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Funding Type |
Internal |
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Principal Investigator |
Dr. Naoufel Werghi |
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Project Co-Investigators |
Prof. Ernesto Damiani , Dr. Youssef Iraqi |
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Summary |
Automatic real-time identification in the wild is a complex process that requires top-down analysis and the fusion of events/information from system monitors and information systems so that an accurate decision can be made. Centralized machine learning can help meeting this requirement to some extent, partly due to the availability of a large data and computation resources such as distributed cloud systems. However, this paradigm faces issues of data transfer latency, security and privacy. Supervised learning approaches assume that the samples presented in the learning data are comprehensive enough to learn and respond to all new inputs which is hard to verify. |
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Project Title |
Machine Learning FPGA Acceleration as a Cloud Microservice |
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Funding Type |
Internal |
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Principal Investigator |
Prof. Ibrahim (Abe) M. Elfadel |
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Project Co-Investigators |
Prof. Ernesto Damiani, and Prof. Thanos Stouraitis |
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Summary |
The cloud computing industry has been steadily moving into the direction of providing reconfigurable hardware acceleration as a service to their customers, but the industrial solutions tend to be proprietary and costly, especially for large-scale computing loads. The goal of this project is to use recently released open-source tools of cloud computing, such as Dockers, Kubernete, and Istio for the design and implementation of reconfigurable hardware accelerators based on Field Programmable Gate Array (FPGA) echnologies. The project will put particular emphasis on the design, implementation, and testing of such accelerators for cloud workflows with intensive AI workloads, including deep-learning training and inference. |
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Project Title |
Trust, Authenticity and Reputation Management in CPS |
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Funding Type |
Internal |
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Principal Investigator |
Dr. Youssef Iraqi |
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Project Co-Investigators |
Prof. Ernesto Damiani and Dr. Nawaf Almoosa |
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Summary |
CPSs interconnected “things” will sense, monitor and collect all kinds of data, which will be aggregated, fused, processed, analyzed and mined via AI models to extract useful information for applications. In this context, trust is of paramount importance. Service consumers need to be able to reason about trust to reduce the risk of using stale or harmful data or services. Trust depends on the nature of the CPS object; those including sensors generate pieces of information at a particular frequency; hence time and volume of data play a crucial role in assessing their trustworthiness. Trust also depends on the associations between the objects and the environment where they operate. In a CPS scenario, different objects should have a way to quantify trust in each other’s supplied data. Reputation has been used to assess the level of trust service consumers put into a service provider based on past interactions. This project aims to redefine trust and reputation management in CPS environment, starting from the idea that trust in CPS objects (and in the data they generate) should be established in a holistic way across the IoE stack. The goal is to design and implement a computational trust management framework to be used as a service by other CPS applications. |
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Project Title |
User authentication and Identification in CPS systems |
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Funding Type |
Internal |
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Principal Investigator |
Dr. Chan Yeob Yeun |
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Project Co-Investigators |
Prof. Ernesto Damiani and Prof. Man Sung Yim |
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Summary |
The main motivation for this research project is to use robust biometrics to monitor any individual with access to, knowledge of, and authority over critical facilities who might attempt unauthorized removal or sabotages, or who could aid outsiders to do so. Traditionally much research effort has been done on securing critical CPSs like energy production and distribution facilities against outsiders, which are a less difficult menace to detect than insiders. Insiders can bypass many security safeguards by nature of their access authorization in NCI. Recently, Electroencephalograms (EEGs) are becoming increasingly important measurements of brain activity and they are routinely used for the diagnosis and treatment of mental and brain diseases and abnormalities. Understanding and developing novel signal processing techniques for the analysis of EEG signals specifically targeted to detecting perturbed states of mind is an open problem in CPS security research. EEG analysis may help to satisfy the increasing global demand for affordable and effective security monitoring services for personnel and visitors accessing NCI environment. |
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Project Title |
Trust and Privacy in Multi- Source Data Collection: Case of Mobile crowd-sensing and IoT |
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Funding Type |
Internal |
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Principal Investigator |
Dr. Rabeb Mizouni |
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Project Co-Investigators |
Dr. Hadi Otrok and Dr. Shakti Singh |
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Summary |
Smart cities and connected communities are well-established examples of CPSs. Recently, with the notable advances in crowd sensing and mobile phone sensing, an intelligent combination between CPS based and crowd sensed data has become appealing. The mobility of the users and the high computational capabilities of their devices, combined with the network infrastructure, open the door to more advanced applications. In these settings, we envision a “multi-source” data collection. Such combination of information is suitable for feeding multi-view AI models and is expected to allow faster, more intelligent, and more efficient control of the environment. While appealing, the integration of crowdsourced and sensed data within CPSs is challenging. Due to heterogeneity, the combination requires new boosting techniques to end-up with a trustworthy result. |
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Project Title |
Autonomous Nodes for IoT: Design and Implementation for Deployment over 5G Networks |
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Funding Type |
Internal |
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Principal Investigator |
Dr. Arafat Al-Dweik |
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Project Co-Investigators |
Dr. Youssef Iraqi and Dr. Sami Muhaidat |
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Summary |
The main goal of this project is the design of autonomous communications nodes over WANs, which are managed by a standardized communication protocol. The nodes’ autonomy will aim at optimizing the network resources, quality of service (QoS), and quality of experience (QoE) of the end user. The autonomy process at the nodes’ should be seamless with respect to the management protocol, which implies that no changes should be required at the protocol level. Therefore, various standardized communications protocols, relevant to IoT, will be anatomized to identify the opportunities to integrate autonomy seamlessly. Then, system modeling, simulation and analysis will be performed to evaluate the performance of the autonomous node itself, and the impact on other nodes in the network, i.e., network wide performance. Building a testbed to evaluate the proposed autonomy rules will be considered as well.
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Project Title |
Energy and Cost Management of CPS over Wireless Networks |
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Funding Type |
Internal |
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Principal Investigator |
Dr. Sami Muhaidat |
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Project Co-Investigators |
Dr. Paschalis Sofotasios, Dr. Arafat Al-Dweik, Dr. Youssef Iraqi |
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Summary |
The increased proliferation of user devices and the increasing overall cost of managing mobile networks represent major challenges for mobile operators. Therefore, there is a strong need for innovative solutions which will leverage recent advances in wireless networking and cloud-aware mobile fog computing. In this regard, our goals can be summarized as follows: 1) Identify content popularity in huge mobile traffic datasets using real-life data; 2) Develop non-orthogonal multiple access (NOMA) assisted caching strategies; 3) Develop centralized proactive caching schemes to offload data at the BS during peak-off hours; 4) Develop heuristic caching schemes, that will be executed locally at the BS. |
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Project Title |
Enhancing Cyber-Physical Systems with Quantum |
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Funding Type |
Internal |
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Principal Investigator |
Dr. Faisal Shah Khan |
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Project Co-Investigators |
Dr. Samuel Feng |
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Summary |
Technologies that process quantum information and exploit the advantages it offers, such as provably- secure communication, and computations much faster than those performed on conventional computers, are beginning to disrupt the status quo of the current generation of ICT. Companies such as IBM, Google, and Amazon are investing in communications networks that can link these quantum technologies together in the form of the “quantum cloud”. This project proposes a proto-type of quantum CPS, i.e. a network of linked devices where both the network and the devices are capable of processing quantum information. |
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Project Title |
Integrating safe UAV operation in CPS architectures |
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Funding Type |
Internal |
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Principal Investigator |
Dr. Abdulhadi Shoufan |
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Project Co-Investigators |
Dr. Chan Yeob Yeun and Prof. Ernesto Damiani |
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Summary |
Due to their high mobility and versatile connectivity, Unmanned Aerial Vehicles (UAVs) or drones are considered as CPS facilitators with unique abilities. A wide range of light-weight sensors can be installed onboard to collect distinct types of data in real time and from different points in space. Drones can benefit from their integration into the CPS toward safer operation by providing a real-time overview of cooperative drone operations. Among others, such information is essential for civil aviation authorities to assure that drones are operated in compliance with regulations. This integration will also allow civil aviation authorities to grant location-based authorization to specific drones for specific purposes such as law enforcement missions in no-fly zones. |
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Project Title |
Highly Scalable, Secure, and Trusted Decentralized Applications (DApps) for the Internet of Things (IoT) |
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Funding Type |
Internal |
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Principal Investigator |
Dr. Davor |
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Project Co-Investigators |
Prof. Khaled Salah and Prof. Ernesto Damiani |
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Summary |
This project is focused on the development of the security and privacy improvements to the blockchain frameworks. The project will produce concrete improvements to the framework of choice that will allow us to develop a set of decentralized applications with significant local and regional impact. |
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Project Title |
Prevention and detection of poisoning and adversarial Attacks on Machine Learning Models (PALM) |
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Funding Type |
External |
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Principal Investigator |
Dr. Chan Yeob Yeun |
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Project Co-Investigators |
Prof. Ernesto Damiani, Dr. Hussam Al Hamadi |
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Project Title |
ML-based Exfiltration Detection on Android Smartphones |
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Funding Type |
External |
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Principal Investigator |
Prof. Ernesto Damiani, |
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Project Co-Investigators |
Dr. Hussam Al Hamadi |
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Project Title |
PHY Layer Security for Heterogeneous UAV-Ground Wireless Networks |
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Funding Type |
External |
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Principal Investigator |
Dr. Arafat Al-Dweik |
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Project Co-Investigators |
Dr. Baker Mohammed, Dr. Yousuf Alsalami |
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Project Title |
Neural Networks for Signal Processing in Secure IoT Mesh Networks |
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Funding Type |
External |
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Principal Investigator |
Dr. Sami Muhaidat |
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Project Co-Investigators |
Dr. Paschalis Sofotasios, Prof. Ernesto Damiani |
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Project Title |
Secure Communications for Power Constrained Wireless Mesh Networks |
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Funding Type |
External |
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Principal Investigator |
Dr. Sami Muhaidat |
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Project Co-Investigators |
Dr. Paschalis Sofotasios, Prof. Ernesto Damiani |
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Project Title |
Advanced System-on-Chip for Secure UAV Operation |
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Funding Type |
External |
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Principal Investigator |
Dr. Abdulhadi Shoufan |
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Project Co-Investigators |
Dr. Hussam Al Hamadi, Prof. Ernesto Damiani |
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Project Title |
An Enhanced μTESLA protocol for IoT Environment |
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Funding Type |
External |
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Principal Investigator |
Dr. Chan Yeob Yeun |
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Project Co-Investigators |
Dr. Yousof Al Hammadi, Prof. Ernesto Damiani |
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Project Title |
Secure FPGA as a Cloud Micro Service |
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Funding Type |
External |
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Principal Investigator |
Dr. Ibrahim Elfadel |
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Project Co-Investigators |
Dr. Abdulhadi Shoufan, Prof. Ernesto Damiani |
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Project Title |
A Secure and Resilient Chat/VoIP Application over Private Mesh Network |
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Funding Type |
External |
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Principal Investigator |
Dr. Hadi Otrok |
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Project Co-Investigators |
Dr. Rabeb Mizouni, Dr. Shakti Singh, Prof. Ernesto Damiani |
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Project Title |
A learned framework for detecting suspicious item in X-ray security imagery |
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Funding Type |
External |
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Principal Investigator |
Dr. Naoufel Werghi |
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Project Co-Investigators |
Prof. Ernesto Damiani, External collaborator: Prof. Mohammed Bennamoun |
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Project Title |
Advanced machine learning systems for the early detection of prostate cancer in multi-modal MRI images |
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Funding Type |
External |
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Principal Investigator |
Dr. Naoufel Werghi |
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Project Co-Investigators |
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