Sujan Chowdhury

September 29, 2020 | Tuesday | 5 PM

ABSTRACT

Due to the widespread functional benefits, such as connectivity between sensors, high visibility, and internet connectivity, the Internet of Things (IoT) devices have been widely used in many applications, such as smart cities, smart health, smart home, and smart vehicle. These IoT based systems contribute to daily life and business, including sensitive and emergency cases. Usually, the IoT devices have very limited computational power, storage, and communication capabilities, but generate a large amount of data, and control the devices connected with them. Since most of the IoT devices have no physical security, and often widely open to everyone via radio communication and via the internet, they are highly vulnerable to existing and new security attacks. Furthermore, the IoT devices are usually integrated with the corporate networks; in this case, the impact of attacks will be much more significant than operating in isolation. Due to the constraints of the IoT devices, and the nature of their operation, existing security mechanisms are less effective to counter the attacks that are specific to the non-IoT based systems. The evaluation reveals that the impact of the attack consistently grows as the IoT network scales. This presentation will highlight some IoT applications, different security attacks on IoT, and how machine learning can help to tackle the security risk.

BIOGRAPHY

Dr. Sujan Chowdhury currently working as a Data Scientist at TechConnect IT Solutions Pty Ltd, Gold Coast, Australia. He also works as a casual lecturer at Central Queensland University (CQU) and recently worked on a research project named “Attack detection and mitigation on IoT” with Deakin University. Prior to joining as a data scientist, he worked as a postdoctoral research fellow in a collaboration project with CQU and ARRB (Australian Road Research Board) to find the Impact of Wide Centre Line Treatment (WCLT) on the Pavement Performance using Image Processing. Sujan did his Ph.D. in the following topic “Smart Information Processing Techniques for Roadside Data Analysis and Fire Risk Assessment” which was supported under Australian Research Council’s Linkage Projects. Sujan achieved the Amazon Web Services Certified Solutions Architect – Associate certification in 2018 and is thoroughly enjoying working with Amazon Web Services and Azure. His interests include Deep Learning, Image Processing, Big Data, IoT, and Data Analytics to solve business problems.

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