Stéphane Bressan and Christian Miniatura grew up in rival neighbourhoods of the naval garrison town of Toulon in southern France. They went to the same high school and the same college only a few years apart, but never were acquainted until 2006 when they were both working halfway across the world, at the National University of Singapore. Miniatura and Bressan became fast friends, meeting regularly to “put the world to rights” over French food and wine.

“One of our favourite debates was whether artificial intelligence can be useful to quantum physics,” says Bressan, an associate professor at the School of Computing. He was convinced that AI could lend a helping hand in solving some of physics’ longstanding problems. But Miniatura, a quantum physicist by training and the director of the Franco-Singaporean physics laboratory MajuLab, remained perplexed albeit intrigued at the possibility.

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National University of Singapore (NUS) researchers have developed a tool to safeguard against a new form of cyber attack that can recreate the data sets containing personal information used to train artificial intelligence (AI) machines.

The tool, called the Machine Learning (ML) Privacy Meter, has been incorporated into the developer toolkit that Google uses to test the privacy protection features of AI algorithms.

In recent years, hackers have figured out how to reverse-engineer and reconstruct database sets used to train AI systems through an increasingly common kind of attack called a membership inference (MI) attack.

Assistant Professor Reza Shokri, who heads the research team behind ML Privacy Meter, said such attacks involve hackers repeatedly asking the AI system for information, analysing the data for a pattern, and then using the pattern to guess if a data record was used to train the AI system.

Prof Shokri likened MI attacks to thieves probing for weak spots in a house's walls and doors with a needle before breaking in. "But the thief is not going to break in with the needle. Now that he knows (where the weak spots are), he is going to come with a hammer and break the wall," he said.

ML Privacy Meter helps AI developers through a scorecard showing how accurately attackers could recreate the original data sets and suggests techniques to guard against actual MI attacks. The Privacy Meter is the result of three years of work to create an easy-to-use tool which helps programmers see where the weak spots in their algorithms are.

Google started using the tool earlier this year. The tool is open-source, meaning that it can be used for free by other researchers or companies around the world.

"Our main focus was to build an easy-to-use interface for anybody who knows machine learning, but might not know anything about privacy and cyber attacks," said Prof Shokri, who is Iranian by birth and moved to Singapore in 2017. 

The NUS research team that developed the Machine Learning Privacy Meter also consists of master's student Mihir Khandekar, 24, doctoral student Chang Hongyan, 24, research assistant Aadyaa Maddi, 22, and doctoral student Rishav Chourasia, 24.

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5 November 2020 – Several NUS Computing professors were recently awarded funding from the MOE Academic Research Funding (AcRF) Tier 2 scheme. Among the grant recipients were Professor Dong Jin Song, Professor Wing-Kin Sung and Assistant Professor Lee Gim Hee, all from the Department of Computer Science.

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3 November 2020 – Professor Chua Tat Seng, Kwan Im Thong Hood Cho Temple Chair Professor at NUS Computing and Director of the NUS-Tsinghua Extreme Search Center (NExT++), won the Best Paper award at the ACM Multimedia Conference. The conference was held online from 12 – 16 October 2020, and is a leading international forum for researchers focusing on advancing the research and applications of multiple media such as images, text, audio, speech, music, sensor and social data.

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28 October 2020 – NUS Computing Assistant Professor Brian Y. Lim won the ACM IMWUT Distinguished Paper Award at the UbiComp 2020 Conference, held online from 12 to 17 September 2020.

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These days, we live and buy by online reviews. Looking for a pair of headphones? Wondering what movie to stream or if you should splash out for the new PlayStation 5? Or perhaps you need a hotel to stay in and suggestions for the best baby back ribs in town? Well look no further than the Internet, for someone somewhere will surely have a recommendation to offer about the product, service or facility you are thinking of.

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19 October 2020 – Members from Meel Group (Sung Kah Kay Assistant Professor Kuldeep S. Meel’s research lab) emerged champions at the 1st International Competition on Model Counting (MC 2020). A total of 17 entries were submitted to this year’s competition, which aimed to evaluate the performance of model counting tools.

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7 October 2020 – The NUS team comprising Sung Kah Kay Assistant Professor Kuldeep S. Meel, Visiting Senior Research Fellow Mate Soos, and research intern Arijit Shaw took home the top prizes at the SAT Competition 2020.

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Three NUS researchers have developed wearable devices that help perform gait analysis. The four sensors installed at the toe and heel of the shoes can detect the speed, rotation and step length of the user's movement. The data is reflected in the app in real time for analysis by the therapist.

Dr Boyd Anderson, a lecturer from NUS Computing's Department of Computer Science, said: “If you are an elderly person, you may be more frail when walking, and being able to quantify that is very important. If you’re a sprinter, seeing how every step hits the track is also very important for say, optimising your performance. Traditionally, you would use a clinical gait mat which is pressure sensitive."

Medical gait mats take up space and are expensive, costing upwards of $10,000. The cost of this device however, is expected to be under $500. In addition to relying on an inertial measurement instrument to measure acceleration and rotation during movement, the device also combines ultra-wideband radio technology to collect step lengths and step widths that are difficult to measure. Its accuracy rate is 97%.

The four sensors mounted on the shoes run on lithium batteries and has a battery life of 18 hours per charge. The research team has already applied for a technology patent. They are working to bring this technology to professional athletes who are looking to improve their skills.

The team is also looking at ways to incorporate the sensors for use in various running shoes.

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Life has a funny way of leading people down paths they least expect. Just ask NUS Computing lecturer Boyd Anderson. Two years ago, Anderson, then a PhD student, found himself at Mustafa Centre, a 24-hour mall in the heart of Singapore’s Little India district. It was 3 a.m., and Anderson was throwing what seemed to be a random assortment of things into a shopping cart: a hot glue gun, Velcro tape, disposable socks, and 12 pairs of sneakers, each a different size.

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In March 2011, the New York Times introduced a policy that would later be recognised as a milestone in media history. The newspaper, deemed one of the best in the world, declared that its online content would no longer be completely free — after the first 20 articles, readers would have to pay a small fee.

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25 September 2020 – Have you ever heard of the ‘cappuccino effect’? It is not the latest trend in foam art among aficionado baristas, but a common malpractice committed in the shipping industry through negligence.

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23 September 2020 – Four NUS Computing professors and seven alumni were named in the inaugural Singapore 100 Women in Technology List. The list is a collaboration between the Singapore Computer Society, Infocomm Media Development Authority, SG Women in Tech and Mediacorp.

Provost’s Chair Professor Wynne Hsu, Professor Janice Lee Mong Li, Professor Tulika Mitra and Adjunct Professor Kwong Yuk Wah were named in the list, which was unveiled in early September this year.

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NUS and ST Engineering are collaborating on a S$9 million, multi-year advanced digital technologies research programme to further their common goals of building a people-centric, smart future for Singapore and beyond.

Research efforts of this new programme will focus on technologies related to Smart City as well as Smart Maintenance, Repairs and Overhaul (MRO), covering five areas: resource optimisation and scheduling; prescriptive analytics; decision and sense-making; reasoning engine and machine learning; as well as digital twin. These research areas support ST Engineering’s focus on developing differentiated and people-centric, smart city solutions that meet the present and future needs of cities around the world. The interdisciplinary research areas are also aligned with NUS’ endeavours as a driving force behind smart city innovations, leveraging its deep expertise that spans multiple domains and faculties.

Professor Chen Tsuhan, NUS Deputy President (Research & Technology), said, “As Singapore advances its position as a Smart Nation, having the right enterprise architecture to support those goals will determine if true digital transformation can be achieved. Over the years, NUS and ST Engineering have enjoyed a close and productive relationship. This new collaboration will combine NUS’ expertise in the science of cities with ST Engineering's industry knowledge to co-create people-centric Smart City solutions that will form the foundational systems to bring about not just impactful, but radical, change to the lives of people in Singapore and the world.”

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Just two months ago, Mr Na Yi Rong had little to no knowledge of Financial Technology (FinTech). The Engineering Science graduate from the National University of Singapore (NUS) is now working full time as a product management lead at a local FinTech start-up, after receiving the job offer when he was participating in the NUS-FinTechSG Programme.

Jointly developed by the NUS FinTech Lab and Strategic Technology Management Institute (STMI), the programme was launched on 6 July 2020 to nurture Singapore’s next generation of FinTech talents and full stack developers. The pioneer batch of 25 students graduated on 10 September in a virtual ceremony after undergoing a structured two-month intensive full-time course on the fundamentals of financial services technology and business.

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Your heartbeat quickens as you watch your video game avatar run through the twisting corridors of the castle. There is still treasure to be found and a hostage to be rescued, and time is running out. Suddenly, a large shadow looms on the dim candlelit stone walls, followed by a low roar that sounds awfully close. You take a deep breath, clutch your mace a bit tighter, and ready yourself to attack. You swing around the corner, weapon raised, and…

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28 August 2020 – Six NUS Computing final-year students and alumni received the NUS Outstanding Undergraduate Researcher Prize (OURP) for Academic Year 2019/2020.

The annual, university-wide competition encourages undergraduates to pursue research projects and recognises exceptional undergraduate researchers for their work.

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27 August 2020 – Six former and current NUS Computing students, along with NUS Computing Associate Professor Ben Leong, developed a fully operational national contact tracing workflow management web application with the Singapore Armed Forces (SAF), in 3 months.

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A group of security researchers from the department of computer science at the National University of Singapore has created an attack model they call SpiKey to determine the key shape that will open any tumbler lock.

Soundarya Ramesh, Harini Ramprasad and Jun Han are the talented hackers behind SpiKey, which they say "significantly lowers the bar for an attacker," when compared to a more traditional lock-picking attack. The theoretical methodology is deceptively simple, listening for the sound of the key as it moves past tumbler pins in turn when the key is inserted in the lock.

The Singapore hackers use a simple smartphone to record the sound of the key being inserted, and withdrawn, with a smartphone and then observe the time between each tumbler pin click using their custom key reverse-engineering application. This forms the secret of the key, the fine-grained bitting depths which, the researchers report, can differ by as little as 15 milli-inches, or 0.381 millimeters.

"As SpiKey infers the shape of the key, it is inherently robust against anti-picking features in modern locks," the research paper states, "and grants multiple entries without leaving any traces."

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19 August 2020 – The Asian Institute of Digital Finance (AIDF) will be funding three research projects by NUS Computing Associate Professors He Bingsheng, Huang Ke-Wei and Liang Zhenkai.

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