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Balancing security and privacy with data usefulness and efficiency in wireless sensor networks

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  • Full or part time
    Dr Zhang
  • Application Deadline
    Applications accepted all year round
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

A Wireless Sensor Network (WSN) refers to a collection of low-power wireless devices connected through radio communication facilities. These devices have limited processing speed, storage capacity, and communication bandwidth. They can be deployed in a distributed environment sensing, monitoring or collecting data, processing and communicating the data and coordinating actions with other peers or nodes at a higher hierarchy in an infrastructural setting. Such WSNs have a wide range of potential applications including utilities, transportation system automation, and patients? medical condition monitoring, etc. Some of these application areas impose stringent privacy and security requirements on data transmissions, processing and management.

Assuming reliable cryptographic techniques can be used to provide communication security, it is not clear how data privacy could be
preserved in such a context. In addition, cryptographic techniques are computationally expensive, and inappropriate use of these techniques could lead to excessive computing power and energy consumption. The aim of this Ph.D. project is to investigate and research efficient and cost-effective measures to achieve security and preserve privacy in a WSN environment.

Funding Notes

Candidates who have been offered a place for PhD study in the School of Computer Science may be considered for funding by the School. Further details on School funding can be found at: http://www.cs.manchester.ac.uk/study/postgraduate-research/programmes/phd/funding/school-studentships/.


The minimum requirements to get a place in our PhD programme are available from:

Related Subjects

How good is research at University of Manchester in Computer Science and Informatics?

FTE Category A staff submitted: 44.86

Research output data provided by the Research Excellence Framework (REF)

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