Filtered by: Department of Computer Science

Beyond the classroom: Innovations that change the world

14 December 2020 Department of Computer Science , Faculty , News Media , Systems & Networking , Security

 

Lettuce, mint and even tomatoes – Singaporeans may soon be able to grow these vegetables and more in their HDB flats.

Having witnessed “a deep psychological fear” when COVID-19 sparked panic buying here, Toby Fong and his team – superFARM – decided to bolster the nation’s food security. Their plan? Encourage green fingers through home-based farming.

“When we think about food security, it’s usually at a national level so it almost feels like the individual (is disconnected) from the entire food security equation,” said Toby, who graduated with a Master’s from NUS Architecture this year.

Under the “Make Our People Better” category, Toby, NUS Computing graduate Lim Hui Qi and NUS Arts and Social Sciences graduate Ong Jun Ren will design modular farming units that can fit into the smallest of homes. These units can also be customised for bigger spaces.

The plan is to transform niche hydroponics systems into functional mini-farms. In the next six months, half of their $50,000 funding will go to research such as field testing and online surveys, while the rest will be used for prototype development.

The team also wants to expand the individual’s role in food security to make sustainability a way of life.

“We want to recalibrate people’s attitude and behaviour to encourage responsible food consumption,” said Toby.

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Associate Professor He Bingsheng wins IEEE TPDS 2019 Best Paper award

09 December 2020 Department of Computer Science , Faculty , Student

9 December 2020 – Associate Professor He Bingsheng and his collaborators have won the IEEE Transactions on Parallel and Distributed Systems 2019 Best Paper award.

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Assistant Professor Jun Han and collaborators win Best Poster Runner-Up Award at SenSys 2020

08 December 2020 Department of Computer Science , Faculty , Research , Systems & Networking , Security

8 December 2020 – Assistant Professor Jun Han, Computer Science PhD student Sriram Sami, and final-year undergraduates Yimin Dai (Computer Science) and Sean Rui Xiang Tan (Computer Engineering), as well as Assistant Professor Nirupam Roy from the University of Maryland, won the Best Poster Runner-Up Award at the 18th ACM Conference on Embedded Networked Sensor Systems (SenSys 2020).

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Robot vacuum cleaners can be used by hackers to 'spy' on private conversations: NUS study

08 December 2020 Department of Computer Science , Faculty , News Media , Systems & Networking , Security

 

When your robot vacuum cleaner does its work around the house, beware that it could pick up private conversations along with the dust and dirt. Computer scientists from NUS have demonstrated that it is indeed possible to spy on private conversations using a common robot vacuum cleaner and its built-in Light Detection and Ranging (Lidar) sensor.

The novel method, called LidarPhone, repurposes the Lidar sensor that a robot vacuum cleaner normally uses for navigating around a home into a laser-based microphone to eavesdrop on private conversations.

The research team, led by Assistant Professor Jun Han from NUS Computer Science, and his doctoral student Mr Sriram Sami, managed to recover speech data with high accuracy. NUS students, Mr Dai Yimin and Mr Sean Tan Rui Xiang, as well as Assistant Professor Nirupam Roy from the University of Maryland, also contributed to this work.

Mr Sami shared, “The proliferation of smart devices – including smart speakers and smart security cameras – has increased the avenues for hackers to snoop on our private moments. Our method shows it is now possible to gather sensitive data just by using something as innocuous as a household robot vacuum cleaner. Our work demonstrates the urgent need to find practical solutions to prevent such malicious attacks.”'

The core of the LidarPhone attack method is the Lidar sensor, a device which fires out an invisible scanning laser, and creates a map of its surroundings. By reflecting lasers off common objects such as a dustbin or a takeaway bag located near a person’s computer speaker or television soundbar, the attacker could obtain information about the original sound that made the objects’ surfaces vibrate. Using applied signal processing and deep learning algorithms, speech could be recovered from the audio data, and sensitive information could potentially be obtained.

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New practices needed to stay safe online in era of working from home

08 December 2020 Department of Computer Science , Faculty , News Media , Systems & Networking , Security

 

Say "no" when your child asks to use your work laptop to do his schoolwork, or set up a different user account on the work laptop for different activities.

There are ways to reset habits and practices for a more digitally secure 2021 as working and e-learning from home become the new normal even after Covid-19, said panellists at The Straits Times Reset 2021 Webinar Series: Digitalisation And Cyber Security on Wednesday.

The panellists comprised of Associate Professor Steven Wong from the Singapore Institute of Technology, Mr David Koh, chief executive of the Cyber Security Agency of Singapore; Associate Professor Chang Ee-Chien from the National University of Singapore School of Computing; and Mr Benjamin Ang, head of the Cyber and Homeland Defence Programme at the Centre of Excellence for National Security, a policy research think-tank.

Prof Chang suggested segregating devices at home by individual or workflow. For example, as far as possible, children should use a different desktop or laptop from the ones their parents use for work.

"If that is not possible, then try to segregate by setting up different user accounts on a laptop. Even if you have your own machine, you can segregate accounts for work, for family, or for playing games," he said.

"Segregation is about setting up security parameters, so that when something happens within that parameter it will not spill over to other (areas)."

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Seven NUS professors lauded for their work and service

08 December 2020 Department of Computer Science , Faculty , News Media , Programming Languages & Software Engineering , Security

 

NUS has honoured seven exceptional educators, researchers and professionals at the NUS University Awards 2020. The annual event recognises individuals for their outstanding contributions in the areas of education, research and service to the University, Singapore and the global community.

Professor Dong Jin Song from the NUS' School of Computing was given the University Research Recognition Award for developing a software verification framework that has more than 4,000 users from over 150 countries.

NUS President Professor Tan Eng Chye lauded the award winners for being role models for the university community. “Each award winner has exemplified the spirit of excellence with an indomitable spirit. They are truly esteemed individuals – beacons and pathfinders who inspire us to better ourselves and to scale new heights even in times of crisis. NUS is proud to celebrate their dedication and distinguished accomplishments,” he said.

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The Department of Computer Science welcomes four new faculty members

02 December 2020 Department of Computer Science , Faculty , Algorithms & Theory , Systems & Networking , Artificial Intelligence

2 December 2020 – Four new faculty members have joined NUS Computing’s Department of Computer Science:

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60 years of facial recognition: The hidden perils behind Singapore’s ‘facial recognition era’

27 November 2020 Department of Computer Science , Faculty , News Media , Security , Media

 

In recent years, the Singapore government has tapped on facial recognition for various purposes as part of its ‘smart nation’ initiative. For instance, Changi Airport’s Terminal 4 uses facial recognition technology for various purposes such as passenger check-in, immigration and boarding, while GovTech launched a launched the "Lamppost-as-a-Platform" project, which outfits some 95,000 traditional lampposts in the country with a network of wireless sensors and cameras to support urban and transportation planning and operations.

Associate Professor Terence Sim from the School of Computing at the National University of Singapore stated in an exclusive interview with China-based news website The Paper that there are trends of facial recognition technology being abused, and that laws protecting such technology could be further strengthened. He also elaborated further on privacy issues regarding such technology.

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Hackers hijacking WhatsApp accounts by asking for security codes

23 November 2020 Department of Computer Science , News Media , Systems & Networking , Security , Media

 

When a secondary school friend contacted him out of the blue a few months ago asking for a verification code on WhatsApp, administrative executive Tan Jun Heng, 25, did not suspect anything was amiss.

His friend simply claimed to have "accidentally" sent the code to his number. But within seconds of sending the code, Mr Tan was automatically locked out of his own WhatsApp account. It had been hijacked.

Mr Tan and his friends are among a growing pool of WhatsApp users who have become victims of social hacking, where scammers use already hijacked social media accounts to contact victims by posing as their friends or family.

National University of Singapore's Associate Professor Chang Ee-Chien, whose research interests include data privacy, said the impersonation tactics used by hackers are "very low-tech, but very effective, as people tend to trust their friends or family".

With full access to their victim's account, hackers may then exploit the victim's personal relationships and ask for money from friends or family. Or, if they glean enough information about their victim's place of employment, they may also target the victim's workplace, added Prof Chang. 

However, experts say, there are preventive measures that users can take to prevent such attacks.

Ms Wong and AiSP executive committee member James Tan said setting up a two-step verification process on your WhatsApp account can prevent others from signing in to it. Users should not click on suspicious looking links, even if they are purportedly from friends or family, they added.

For impersonation scams, however, "the only solution is to not trust people", said Prof Chang. He added: "It is very important that you must presume that whoever is speaking to you on the other end is not your friend."

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NUS Computing professors and PhD students listed in GSMA Mobile Security Hall of Fame

20 November 2020 Department of Computer Science , Faculty , Student

20 November 2020 – Computer Science professors Chan Mun Choon and Han Jun, along with their PhD students Nishant Budhdev and Nitya Lakshmanan, were recently listed in the GSMA Mobile Security Hall of Fame.

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Associate Professor Kan Min-Yen and alumnus Nguyen Van Hoang win Best Paper award at CIKM2020

18 November 2020 Department of Computer Science , Faculty , Student , Alum

18 November 2020 – Associate Professor Kan Min-Yen and Computer Engineering alumnus Nguyen Van Hoang won the Best Paper Full Research Paper Award at the 29th ACM International Conference on Information and Knowledge Management (CIKM2020), held online from 19 to 23 October.

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Quantum Physics Gets a Boost from AI

13 November 2020 Department of Computer Science , Faculty , Research , Feature , Artificial Intelligence

 

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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NUS team develops tool that can assess vulnerability of AI systems to attacks

10 November 2020 Department of Computer Science , Faculty , Research , News Media , Security

 

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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NUS Computing professors awarded grants from MOE Academic Research Fund (AcRF)

05 November 2020 Department of Computer Science , Faculty , Research , Programming Languages & Software Engineering , Artificial Intelligence , Computational Biology

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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Professor Chua Tat Seng wins Best Paper Award at ACM Multimedia Conference 2020

03 November 2020 DCS Research , Department of Computer Science , Faculty , Research , Media , NExT

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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Assistant Professor Brian Lim wins Distinguished Paper Award at UbiComp 2020

28 October 2020 Department of Computer Science , Faculty , Alum

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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Meel Group wins first place at the 1st International Competition on Model Counting

19 October 2020 Department of Computer Science , Faculty

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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NUS Computing students win first place at Facebook Singapore Virtual Hack

12 October 2020 Department of Computer Science , Student

12 October 2020 – A team of NUS Computing students won first place at the Facebook Singapore Virtual Hack, held virtually on 3 October this year.

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Meel Group wins big at the SAT Competition 2020

07 October 2020 Department of Computer Science , Faculty

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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NUS Computing researchers develop wearable device for gait analysis

05 October 2020 Department of Computer Science , Faculty , Research , News Media , Systems & Networking

 

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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