Project Overview:
This research project is motivated by the author's personal experience of being a victim of rental fraud upon arriving in Sydney for their master's program. Stranded and forced to deplete their savings to find temporary housing, this experience highlighted the pervasive nature of Sydney's rental crisis and the significant psychological and financial impact it can have. This incident served as the catalyst for the research, aiming to address this widespread issue affecting not just Sydney, but other major cities globally.
Objective:
The overarching aim of this project is to create a user interface prototype of an AI-powered platform that addresses the security challenges facing the current housing crisis in Sydney by implementing secured measures to decrease the rate at which fraudsters camouflage as real property owners / realtors.
To develop and implement AI content verification algorithms to analyse virtual tour content, including images and videos, for anomalies and potential signs of manipulation.
Explore integrating blockchain technology to create an immutable record of property listings and transactions, which would increase transparency and prevent fraudulent transactions.
Explore strong authentication methods, such as multi-factor authentication and biometrics, to protect user accounts and prevent unauthorised access.
Increase user awareness and knowledge about fraud.
Challenges:
Vulnerability of Virtual Tours: AI-driven virtual tours, while increasing accessibility, create security vulnerabilities that can be exploited.
Cybersecurity Threats: These include property misrepresentation and identity theft, which undermine user trust and
legal standing.
Fraud in Virtual Tours: Scammers target virtual tours to mislead renters and buyers, leading to financial losses and
eroded trust.
Lack of Robust Verification: Insufficient verification processes for property listings and user identities increase the risk of scams.
Inadequate Data Protection: Weak data protection measures put user information at risk, threatening the integrity of housing platforms.
Erosion of User Confidence: The combination of these security issues leads to a decline in user trust, hindering the adoption of AI-powered housing solutions.
Limited Acceptance of AI Solutions: Security concerns and lack of trust limit the broader acceptance and utilization of AI in affordable housing.
Design Process:
Empathise: User Research, Survey Question
Define: User Persona
Ideate: User Flow, Empathy & Affinity mapping, Wireframes
Prototype: UI Research, Style Guide, Visual Screens
Test: Usability testing (Alpha & Beta Testing)
Feedback & Refinement
Outcome:
Key Achievements:
This project suggests that incorporating AI-based content verification, blockchain technology, and robust authentication methods significantly improves platform security and reduces fraud risks. However, effectively executing these strategies requires careful consideration of ethical issues, user experience, and the changing tactics of fraudsters.
