Tamer R. Omar

Tamer R. Omar

Assistant Professor, Electrical & Computer Engineering Department, College of Engineering

Frontier Technologies cybersecurity Research Lab (FTcsRL)

Lab Activities

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Projects Description

5G Self-Healing Network Simulator (5GSHNsim)

This project aims to model a 5G mobile service providers’ core network, access network, and self-healing controller. This consist of modeling and designing a 5G network environment and creating a management system to oversee and maintain the network autonomously. The project will be designed/implemented using C++ to implement network core classes, C# to implement the network simulator Graphical User Interface (GUI), and MATLAB to implement the access network radio frequency signaling. The simulator will create and configure accurate networking scenarios that to determine the potential self-healing solutions in case of network failures or congestions.

Project 1 Presentaion 2020

Project 2 Presentaion 2020

Remote Pilotless Vehicle Command Center (RPVCC)

This project aims at remotely controlling a vehicle through wireless link using car (VRX) simulator. The VRX racing simulator will use IoV (Internet of Vehicle) technology to support autonomous driving. IoV technologies relying on wireless communication to send car and driving controls from the VRX simulator to an API (Application Program Interface). The API server is connected to the internet and thus transferring the data that is being collected from the simulator to the vehicle. The server will act as a cloud service to communicate the data to the vehicle and return the outdoor driving conditions back to the simulator. The simulator controls the vehicle by using a communication link (modem) attached to the vehicle and operated by Sprint. The modem connects the vehicle to receive controls\send feedback from\to the VRX simulator.

Project News Article

Project 1 Presentation 2020

Project 2 Presentation 2020

Software Defined Networking (SDN) Secured Controller (SDNSC)

This project aims at studying Software-defined networking (SDN) which is a new concept developed to shift the current paradigm of network infrastructures by providing a central control layer, improves network management, and implements programmability for network management flexibility. Students will analyze the effects of different network and host based attacks such as Distributed Denial of Service attacks (DDoS) on an SDN environment.  They will also investigate approaches to detect and mitigate these attacks and use the flexibility of OpenFlow, a common SDN protocol, to secure this new networking trend.

Project Presentation 2020

Disaster Recovery using Software Defined Radios (DRuSDR)

This project aims at presenting a potential solution to the lack of connectivity available for individuals located inside of a disaster-impacted region. The project explores the construction of a mobile base transceiver station that uses SDRs and equipped into an Unmanned Aerial Vehicles (UAVs). WNSL hosts the Universal Software Radio Peripheral (USRP) used to create the virtual interfaces required to create the backup communication systems. Students program the USRPs using lab view software to create the required relay stations for such application to restore the wireless networks in case of disasters.

Project Presentaion 2020

Big Data System (BDS)

This project aims at collecting, organizing, and analysis of data collected in WNSL projects. The Big Data System (BDS) contains a Hadoop Distributed File System (HDFS) cluster of seven nodes and host different big data tools offered in the Cloudra and Amazon Elastic Map Reduce (EMR) distribution to manage and analyze the collected data. The BDS will be utilized to analyze over hundred Giga bytes of unstructured data generated by the self-healing project to provide the network controller with recommendations for healing based on the collected data. Students use the WNSL hosted system to upload the data to the HDFS cluster, organize the unstructured data, and use machine learning algorithms to extract values from the data that can provide insights and recommendations about autonomously heel the network.

Project Presentaion 2020