“Invisible cloak: A Breakthrough in Stealth Technology with Implications for Security and Privacy”
Introduction Invisible cloak
Invisible cloak, developed by a team at Wuhan University, allows wearers to go unnoticed by surveillance cameras, utilizing a drone-resistant technology that has implications for both the military and civilian sectors. The team emphasizes the current shortcomings in AI and recognition technology, encouraging developers to refine these technologies using their innovative algorithm.
According to the team, Chinese undergraduate students have designed a low-cost coat that appears ordinary but can hide the human body from surveillance cameras equipped with AI. The coat, called InvisiDefense, creates a pattern that confuses the AI algorithms, making it challenging to identify the wearer during both day and night.
The project, led by Professor Wang Zheng at Wuhan University’s School of Computer Science, won the top prize in a creative competition sponsored by Huawei Technologies on November 27. The algorithm behind InvisiDefense received recognition at the AAAI 2023 academic conference.
The coat’s pattern is designed to deceive AI algorithms, particularly those used in surveillance cameras. The team conducted extensive testing over three months to achieve optimal results. The technology is not only effective but also cost-efficient, with the entire set of InvisiDefense costing less than 500 yuan (approximately 70 USD).
Wang highlighted the significance of InvisiDefense in preventing the identification of pedestrians in public spaces without raising suspicion, offering a unique solution to privacy concerns associated with surveillance. Through campus trials, the accuracy of identifying pedestrians can be reduced by up to 57%, with the potential for further improvement in the future.
In conclusion, InvisiDefense emerges as a pioneering product in the industry, addressing the limitations of current artificial intelligence and computer vision technologies. The team believes that their algorithm can contribute to enhancing existing models and envisions applications beyond privacy, including drone-resistant warfare and human-machine interactions on the battlefield.
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