Opportunities and risks in the application of machine and deep learning to security screening

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Research Topic Description, including Problem Statement:

• Research into the use of machine learning and deep learning as a means of automating aspects of the security screening process is increasing, particularly as applied to automated detection algorithms applied to interpretation of imaging data produced by aviation security screening systems. This brings with it undoubted opportunities to reduce the level of human effort required in the screening process, alongside potential improvements in levels of security. However, there are also risks in the early adoption of a rapidly evolving area of technology without full consideration of potential vulnerabilities, including how the effectiveness of systems can be rigorously quality assured both prior to deployment and throughout their lifecycle.

• An understanding of both the opportunities associated with the operational deployment of automated detection algorithms based on machine learning and deep learning techniques, balanced against the potential drawbacks and costs will be crucial to ensure that the most benefit can be derived from this technology.

Example Approaches:

• A study into potential vulnerabilities from the use of machine learning or deep learning approaches as applied to security screening applications, such as automated threat detection in X-ray images or millimetre-wave people-screening data.
• An evaluation of the best way to integrate automated machine learning and deep learning decision making with human interpretation, and the implications on human performance.
• An exploration of the public perception of the increasing use of automated decision-making in security screening, particularly through machine learning and deep learning.

Key Words:

Deep learning; machine learning; security screening; artificial intelligence

Postdoc Eligibility

• U.S. citizens only
• Ph.D. in a relevant field must be completed before beginning the appointment and within five years of the application deadline
• Proposal must be associated with an accredited U.S. university, college, or U.S. government laboratory
• Eligible candidates may only receive one award from the IC Postdoctoral Research Fellowship Program.

Research Advisor Eligibility

• Must be an employee of an accredited U.S. university, college or U.S. government laboratory
• Are not required to be U.S. citizens

• Citizenship: U.S. Citizen Only
• Degree: Doctoral Degree.
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