Awards & Press

Professor Yongdae Kim, developed anti-drone technology for anti-terrorism
Our department’s laboratory (Prof. Yongdae Kim) has developed an anti-drone technology that can steal other drones by deceiving the location by using the fake GPS signals. This technology can safely guide the drones to the desired location without any sudden change in direction at any emergency situation. Therefore, it can respond effectively to drones with purpose of any terrorism. This technology was published on ‘ACM Transactions on Privacy and Security, TOPS’ in the 9th of April. As the industry of drone has developed, drones are utilized in various areas such as searching, rescuing, disaster prevention, response, delivery, reconnaissance. In contrast, concerns about private property, key facility intrusion, safety and security threats, and privacy invasion are growing. Therefore, industry of detecting and preventing drones penetrating is rapidly growing. Currently, the anti-drone systems built in key facilities such as airports utilize electronic jamming signals, high-power lasers, or nets to neutralize drones. However, drones for terrors, which are armed with explosives or weapons, must be neutralized with securing a safe distance to minimize any damages. At the point where new anti-drone technology is needed, Professor Kim’s research team has developed new anti-drone technology that steals drones by tricking them with fake GPS signals. The research team analyzed the GPS safety mode of the drones made from major drone makers such as DJI and Parrot and made classification system based on this. And they designed a drone abduction technique depending on the type of the drone. This classification system covers almost all the types of drone GPS safety modes, and is universally applicable to any drones that use GPS regardless of model or manufacturer. The research team applied the new technology to four drones and have proven that the drones can be safely guided to the direction of intentional abduction within a small margin of error. Professor Kim said, “Conventional consumer drones seems to be safe from the fake signal GPS attacks due to equipped safety GPS mode, but most of them are able to detour because they detect GPS errors in a rudimentary manner. In particular, the new technology will be able to contribute to reducing the damage to the airline industry and the airport caused by illegal drone flight. The research team plans to commercialize the technology by applying to existing anti-drone technology by technology transfer.   <Anti-drone system developed by Professor Kim's research team>   <Link>  
Professor Munchurl Kim was awarded the President’s Commendation at the ‘54th Invention day’ ceremony
Professor Munchurl Kim was awarded the President’s Commendation at the ‘54th Invention day’ ceremony held on May 27 at COEX. Professor Munchurl Kim has received 51 registered patents (20 international and 31 domestic) and applied 34 patents (18 international and 16 domestic) for video compression technology, artificial intelligent deep learning based image processing technology, and intelligent machine learning technology for the past 5 years (2014.01.01 ~ 2018.12.31). Professor Munchurl Kim has obtained 26 international standard patents for HEVC video compression applied to UHDTV/broadcasting among 51 registered patents. He applied these to overseas institutions and created a lot of patent royalties, so he conducted source technology research in university and gained intellectual property rights. In addition, he linked this to the international standardization (HEVC standardization) activity that high value-added, so presented successful research cases that can lead to high research productivity in university. He also contributed to the enhancement of the competitiveness of the high-quality contents service industry through improving the image quality of the existing video (legacy contents) by developing super high quality image generation and image enhancement technology using artificial intelligence technology that will lead the fourth industry. In particular, “AI Deep Learning based Low Complexity Super Resolution Method and Device” patent proved superiority in the excellent journals of its field as the world’s first deep learning based upscaling hardware technology that converts full HD video into UHD video at 60 frames per second in real time. It was exhibited at CES 2019, the world’s largest consumer electronics show, and received high interest. Therefore, this award is a contribution to the national competitiveness of the contents industry, related equipment/parts industry and to the deriving a high value-added patent which enables acquisition of high value-added image contents through deep learning based super high quality image conversion research.   <Link>



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