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The Digitalization Of Insolvency Proceedings, Aurelio Gurrea-Martinez Apr 2025

The Digitalization Of Insolvency Proceedings, Aurelio Gurrea-Martinez

Research Collection Yong Pung How School Of Law

Despite the international divergences existing in the design of insolvency law, there is a common feature of insolvency proceedings that, to a greater or lesser extent, is somehow universal: insolvency proceedings are generally costly and lengthy processes. For that reason, it is not surprising that a significant body of the literature on insolvency law deals with different mechanisms to make insolvency proceedings more efficient. This article examines how technology can contribute to that goal. To that end, it starts by reviewing how countries are deploying, or can deploy, technology in different aspects and stages of insolvency proceedings and how such …

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Beyond Non-Recognition: U.S.–Taiwan Trade Agreements In Indo-Pacific Dynamics, Pasha L. Hsieh Apr 2025

Beyond Non-Recognition: U.S.–Taiwan Trade Agreements In Indo-Pacific Dynamics, Pasha L. Hsieh

Research Collection Yong Pung How School Of Law

At the core of U.S.-China tensions and the Indo-Pacific strategy, the evolving legal frameworks that govern U.S.-Taiwan relations present legal intricacies under American and international law. The Article provides the first comprehensive analysis of the groundbreaking U.S.-Taiwan Initiative on 21st-Century Trade, the only Congress-approved trade agreement during the Biden administration. It argues that within the space of non-recognition, the United States has accorded Taiwan diverse and incremental forms of legal recognition, which culminated in the Initiative and its Implementation Act. Through an interdisciplinary lens, the Article develops a theoretical framework that bridges recognition theories under international law and international relations. …

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Right-Sizing The Smart City In Southeast Asia, Prerona Das, Orlando Woods, Lily Kong Apr 2025

Right-Sizing The Smart City In Southeast Asia, Prerona Das, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

The idea of right-sizing, or the process of adjusting the size of a city to maximise the efficient use of resources, has traditionally been used in strategic management and the resizing of shrinking cities to promote efficient urban development. Concurrently, in contemporary discourse, the sizing of smart cities has emerged as a critical topic, as size impacts the implementation of smart initiatives. Smaller cities offer the advantage of serving as cost- effective testing grounds for innovative solutions; however, they also need to be sizeable enough to attract private investments and build a robust smart city ecosystem. In this paper we …

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Decarbonising Digital Infrastructure And Urban Sustainability In The Case Of Data Centres, Felicia H. M. Liu, Karen P. Y. Lai, Bertrand Seah, Winston T. L. Chow Apr 2025

Decarbonising Digital Infrastructure And Urban Sustainability In The Case Of Data Centres, Felicia H. M. Liu, Karen P. Y. Lai, Bertrand Seah, Winston T. L. Chow

Research Collection College of Integrative Studies

This paper critically assesses the complex interplay between urban transitions of digitisation and sustainability. Building on a mixed-method research design, we unpack the challenges of decarbonising digital infrastructure while attending to urban sustainability goals in a land- and water-scarce country facing significant physical climate risks. We identify transferrable lessons on the economic, technological, and environmental synergies and trade-offs behind data centre development and argue that stewarding the global data centre sector towards sustainability requires an ecosystem-wide approach. We identify implementation gaps across five key dimensions: technological innovation, policy and regulation, finance, infrastructure, and people. We find that the progress and …

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What Is A Digital Twin Anyway? Deriving The Definition For The Built Environment From Over 15,000 Scientific Publications, Abdelrahman Mahmoud, Edgardo Macatulad, Binyu Lei, Matias Quintana, Clayton Miller, Filip Biljecki Apr 2025

What Is A Digital Twin Anyway? Deriving The Definition For The Built Environment From Over 15,000 Scientific Publications, Abdelrahman Mahmoud, Edgardo Macatulad, Binyu Lei, Matias Quintana, Clayton Miller, Filip Biljecki

Research Collection College of Integrative Studies

The concept of Digital Twins (DT) has attracted significant attention across various domains, particularly within the built environment. However, there is a sheer volume of definitions and the terminological consensus remains out of reach. The lack of a universally accepted definition leads to ambiguities in their conceptualization and implementation, and may cause miscommunication for both researchers and practitioners.We employed Natural Language Processing (NLP) techniques to systematically extract and analyze definitions of DTs from a corpus of more than 15,000 full-text articles spanning diverse disciplines. The study compares these findings with insights from an expert survey that included 52 experts. The …

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The Insurgent Smart City: How A Social Movement Created An Alternative Imaginary Of The Smart City, Andrew Stokols Apr 2025

The Insurgent Smart City: How A Social Movement Created An Alternative Imaginary Of The Smart City, Andrew Stokols

Research Collection College of Integrative Studies

Urban scholars have critiqued smart cities for their association with neoliberal governance, narrow focus on quantifiable aspects of urban systems, and failure to incorporate citizens’ needs or aspirations. The “smart city” remains a contested concept and as such is subject to reappropriation. Here, I analyze the case of an urban social movement, the 2019–2020 Hong Kong Anti-ELAB protests, as an alternative, “insurgent smart city.” Following from an earlier network analysis of Telegram channels used during the protests, I show how the communications system underpinning much of the protest action simultaneously enabled coordination while also remaining open to grassroots decision-making and …

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On Generalization Across Environments In Multi-Objective Reinforcement Learning, Jayden Jing Xiang Teoh, Pradeep Varakantham, Peter Vamplew Apr 2025

On Generalization Across Environments In Multi-Objective Reinforcement Learning, Jayden Jing Xiang Teoh, Pradeep Varakantham, Peter Vamplew

Research Collection School Of Computing and Information Systems

No abstract provided.

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Pearl: Towards Permutation-Resilient Llms, Liang Chen, Li Shen, Yang Deng, Xiaoyan Zhao, Bin Liang, Kam-Fai Wong Apr 2025

Pearl: Towards Permutation-Resilient Llms, Liang Chen, Li Shen, Yang Deng, Xiaoyan Zhao, Bin Liang, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

The in-context learning (ICL) capability of large language models (LLMs) enables them to perform challenging tasks using provided demonstrations. However, ICL is highly sensitive to the ordering of demonstrations, leading to instability in predictions. This paper shows that this vulnerability can be exploited to design a natural attack - difficult for model providers to detect - that achieves nearly 80% success rate on LLaMA-3 by simply permuting the demonstrations. Existing mitigation methods primarily rely on post-processing and fail to enhance the model's inherent robustness to input permutations, raising concerns about safety and reliability of LLMs. To address this issue, we …

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Ada-Gen: Iterative And Incremental Generation Of Full-Stack Apps For Learning Agile/Devops Software Development Practices, Nguyen Binh Duong Ta Apr 2025

Ada-Gen: Iterative And Incremental Generation Of Full-Stack Apps For Learning Agile/Devops Software Development Practices, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

To learn Agile/DevOps practices effectively, students need to apply them in an actual software development project. This is challenging if students are mostly from non-computing backgrounds and they do not have time in the curriculum to learn programming and related tools. Therefore, it is important to help students who do not possess programming foundations to develop fully functional software during the process of learning Agile/DevOps concepts. We noted that existing low-code/no-code app development platforms have not been designed to teach Agile/DevOps practices. On the other hand, recent AI-based tools for code generation such as GitHub Copilot have been built mainly …

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Ivyapc: Auditable Generalized Payment Channels, Ming Li, Yuxian Li, Jian Weng, Yingjiu Li, Jiasi Weng, Junzuo Lai, Robert H. Deng Apr 2025

Ivyapc: Auditable Generalized Payment Channels, Ming Li, Yuxian Li, Jian Weng, Yingjiu Li, Jiasi Weng, Junzuo Lai, Robert H. Deng

Research Collection School Of Computing and Information Systems

Payment channels are a cornerstone of a scalable blockchain infrastructure that enables transacting parties to lock assets on the blockchain and perform rapid off-chain updates with minimal latency and overhead. These protocols dramatically reduce on-chain interaction and improve throughput, with blockchain consensus only invoked in the event of disputes or final closure. While widely adopted in single-chain settings—such as in the Lightning Network for Bitcoin—existing constructions have several limitations, in particular they suffer from at least one of the following limitations: 1. No cross-chain. They do not enable fast trading of assets that reside on multiple isolated blockchains. 2. Non-optimal …

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Rethinking Light Decoder-Based Solvers For Vehicle Routing Problems, Ziwei Huang, Jianan Zhou, Zhiguang Cao, Yixin Xu Apr 2025

Rethinking Light Decoder-Based Solvers For Vehicle Routing Problems, Ziwei Huang, Jianan Zhou, Zhiguang Cao, Yixin Xu

Research Collection School Of Computing and Information Systems

Light decoder-based solvers have gained popularity for solving vehicle routing problems (VRPs) due to their efficiency and ease of integration with reinforcement learning algorithms. However, they often struggle with generalization to larger problem instances or different VRP variants. This paper revisits light decoder-based approaches, analyzing the implications of their reliance on static embeddings and the inherent challenges that arise. Specifically, we demonstrate that in the light decoder paradigm, the encoder is implicitly tasked with capturing information for all potential decision scenarios during solution construction within a single set of embeddings, resulting in high information density. Furthermore, our empirical analysis reveals …

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Rethinking Neural Multi-Objective Combinatorial Optimization Via Neat Weight Embedding, Jinbiao Chen, Zhiguang Cao, Jiahai Wang, Yaoxin Wu, Hanzhang Qin, Zizhen Zhang, Yue-Jiao Gong Apr 2025

Rethinking Neural Multi-Objective Combinatorial Optimization Via Neat Weight Embedding, Jinbiao Chen, Zhiguang Cao, Jiahai Wang, Yaoxin Wu, Hanzhang Qin, Zizhen Zhang, Yue-Jiao Gong

Research Collection School Of Computing and Information Systems

Recent decomposition-based neural multi-objective combinatorial optimization (MOCO) methods struggle to achieve desirable performance. Even equipped with complex learning techniques, they often suffer from significant optimality gaps in weight-specific subproblems. To address this challenge, we propose a neat weight embedding method to learn weight-specific representations, which captures weight-instance interaction for the subproblems and was overlooked by most current methods. We demonstrate the potentials of our method in two instantiations. First, we introduce a succinct addition model to learn weight-specific node embeddings, which surpassed most existing neural methods. Second, we design an enhanced conditional attention model to simultaneously learn the weight embedding …

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Dps: Design Pattern Summarisation Using Code Features, Najam Nazar, Sameer Sikka, Christoph Treude Apr 2025

Dps: Design Pattern Summarisation Using Code Features, Najam Nazar, Sameer Sikka, Christoph Treude

Research Collection School Of Computing and Information Systems

Automatic summarisation has been used efficiently in recent years to condense texts, conversations, audio, code, and various other artefacts. A range of methods, from simple template-based summaries to complex machine learning techniques -- and more recently, large language models -- have been employed to generate these summaries. Summarising software design patterns is important because it helps developers quickly understand and reuse complex design concepts, thereby improving software maintainability and development efficiency. However, the generation of summaries for software design patterns has not yet been explored.Our approach utilises code features and JavaParser to parse the code and create a JSON representation. …

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Alphaedit: Null-Space Constrained Knowledge Editing For Language Models, Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Jie Shi, Xiang Wang, Xiangnan He, Tat‑Seng Chua Apr 2025

Alphaedit: Null-Space Constrained Knowledge Editing For Language Models, Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Jie Shi, Xiang Wang, Xiangnan He, Tat‑Seng Chua

Research Collection School Of Computing and Information Systems

Large language models (LLMs) often exhibit hallucinations, producing incorrector outdated knowledge. Hence, model editing methods have emerged to enabletargeted knowledge updates. To achieve this, a prevailing paradigm is the locatingthen-editing approach, which first locates influential parameters and then edits themby introducing a perturbation. While effective, current studies have demonstrated that this perturbation inevitably disrupt the originally preserved knowledge within LLMs, especially in sequential editing scenarios. To address this, we introduce AlphaEdit, a novel solution that projects perturbation onto the null space of the preserved knowledge before applying it to the parameters. We theoretically prove that this projection ensures the output …

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Open-Set Graph Anomaly Detection Via Normal Structure Regularisation, Qizhou Wang, Guansong Pang, Mahsa Salehi, Xiaokun Xia, Christopher Leckie Apr 2025

Open-Set Graph Anomaly Detection Via Normal Structure Regularisation, Qizhou Wang, Guansong Pang, Mahsa Salehi, Xiaokun Xia, Christopher Leckie

Research Collection School Of Computing and Information Systems

This paper considers an important Graph Anomaly Detection (GAD) task, namely open-set GAD, which aims to train a detection model using a small number of normal and anomaly nodes (referred to as *seen anomalies*) to detect both seen anomalies and *unseen anomalies* (*i.e*., anomalies that cannot be illustrated the training anomalies). Those labelled training data provide crucial prior knowledge about abnormalities for GAD models, enabling substantially reduced detection errors. However, current supervised GAD methods tend to over-emphasise fitting the seen anomalies, leading to many errors of detecting the unseen anomalies as normal nodes. Further, existing open-set AD models were introduced …

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Covid-19 And Investors' Trading Behavior: Evidence From The New Zealand Equity Market, Finn West Wilkinson, Marinela Adriana Finta, Olena Onishchenko Apr 2025

Covid-19 And Investors' Trading Behavior: Evidence From The New Zealand Equity Market, Finn West Wilkinson, Marinela Adriana Finta, Olena Onishchenko

Research Collection Lee Kong Chian School Of Business

This paper examines the trading behavior of retail and institutional investors during the COVID-19 pandemic in New Zealand. Using transaction-level data, it compares how retail and institutional investors trade over the government announcements, lockdown, and reopening periods. Retail and institutional investors' trading intensifies around government announcements, which facilitates attenuating illiquidity during the lockdown. Nevertheless, while retail trading is substantially more prominent during the lockdown than over the control and reopening periods, institutional investors do not trade significantly more per se or on announcements during the lockdown but trade less during the reopening. Their trading also relates to contemporaneous returns, and …

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Can Industrial Agriculture Be Resilient To External Shocks? Industrial Agriculture In Diversified Clusters In Rural China, Qian Forrest Zhang, Zhanping Hu Apr 2025

Can Industrial Agriculture Be Resilient To External Shocks? Industrial Agriculture In Diversified Clusters In Rural China, Qian Forrest Zhang, Zhanping Hu

Research Collection School of Social Sciences

We propose a new model – “industrial agriculture of smallholders” – to conceptualize the agri-food system in China. These smallholders are embedded in “diversified clusters” in rural China, which also include rural industries and extensive rural-urban linkages. Their relationships with markets are more complex and dynamic than what is often portrayed under the linear framework of “commodity chains”. As an alternative to the globalized model of industrial agriculture, we argue that “industrial agriculture of smallholders” has greater resilience to external shocks. Using a village in northern China during the COVID-19 pandemic, we illustrate how economic diversity within this “diversified cluster” …

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Registered Replication Report: Study 3 From Trafimow And Hughes (2012), Sean C. Rife, Et Al Apr 2025

Registered Replication Report: Study 3 From Trafimow And Hughes (2012), Sean C. Rife, Et Al

Research Collection School of Social Sciences

Terror-management theory (TMT) proposes that when people are made aware of their own death, they are more likely to endorse cultural values. TMT is a staple of social psychology, featured prominently in textbooks and the subject of much research. The implications associated with TMT are significant because its advocates claim it can partially explain cultural conflicts, intergroup antagonisms, and even war. However, considerable ambiguity regarding effect size exists, and no preregistered replication of death-thought-accessibility findings exists. Moreover, there is debate regarding the role of time delay between the manipulation of mortality salience and assessment of key measures. We present results …

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New Policy Tools And Traditional Policy Models: Better Understanding Behavioural, Digital And Collaborative Instruments, Michael Howlett, Sarah Giest, Ishani Mukherjee, Araz Taeihagh Apr 2025

New Policy Tools And Traditional Policy Models: Better Understanding Behavioural, Digital And Collaborative Instruments, Michael Howlett, Sarah Giest, Ishani Mukherjee, Araz Taeihagh

Research Collection School of Social Sciences

The study of policy tools has been undertaken for several decades. This work has isolated and examined many different types of instruments or levers utilized by governments to implement their policies and examined in detail how they are arranged into mixes, packages, or portfolios of tools. However, recent developments in society and technology have highlighted the potential to use new or previously underutilized policy instruments for both traditional tasks and to address new challenges associated with emerging technologies and other contemporary issues. These tools include social media platforms, collaboration, behavioral insights, and data-driven approaches to policy-making and policy design using …

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Context-Aware Representation: Jointly Learning Item Features And Selection From Triplets, Rodrigo Alves, Antoine Ledent Apr 2025

Context-Aware Representation: Jointly Learning Item Features And Selection From Triplets, Rodrigo Alves, Antoine Ledent

Research Collection School Of Computing and Information Systems

In areas of machine learning such as cognitive modeling or recommendation, user feedback is usually context-dependent. For instance, a website might provide a user with a set of recommendations and observe which (if any) of the links were clicked by the user. Similarly, there is growing interest in the so-called “odd-one-out” learning setting, where human participants are provided with a basket of items and asked which is the most dissimilar to the others. In both of those cases, the presence of all the items in the basket can influence the final decision. In this article, we consider a classification task …

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Digital Transformation And The Future Of Work: Closing The Digital Skills Gap, Siu Loon Hoe Apr 2025

Digital Transformation And The Future Of Work: Closing The Digital Skills Gap, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

The purpose of this article is to discuss the near future digital technology landscape and propose several specific in-demand digital skills for organizations and individuals in the next few years. This article reviews some recent publications from representative inter-governmental, governmental, non-governmental, and commercial organizations on the rise of digital technologies and corresponding growth in digital jobs. Within this context, several specific in-demand skills are proposed by the author who has written a book on the topic of digital transformation. Rapid advancements in digital technologies continue to shape organizational practices and the future of work. To take advantage of emerging digital …

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From A Learning To A Smart Nation: The Rise Of The Digitalization Megatrend And Singapore's Development, Siu Loon Hoe Apr 2025

From A Learning To A Smart Nation: The Rise Of The Digitalization Megatrend And Singapore's Development, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

Purpose: The purpose of this article is to discuss the “learning nation” concept and examine the characteristics and implications of using the “learning” premodifier in this nation-building program. Design/methodology/approach: This article reviews how the “learning” aspect is inter-related to a series of national information and communication technology masterplans and includes a comparative analysis of the related premodifier “smart” as Singapore sets forth its ambition to become a “smart nation” as part of the digitalization megatrend. A print media indicator and Google Trends form part of the methodology to ascertain the rise of digital technology over a certain period. The former …

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Characterising Reproducibility Debt In Scientific Software: A Systematic Literature Review, Zara Hassan, Christoph Treude, Michael Norrish, Graham Williams, Alex Potanin Apr 2025

Characterising Reproducibility Debt In Scientific Software: A Systematic Literature Review, Zara Hassan, Christoph Treude, Michael Norrish, Graham Williams, Alex Potanin

Research Collection School Of Computing and Information Systems

Context: In scientific software, the inability to reproduce results is often due to technical issues and challenges in recreating the full computational workflow from the original analysis. We conceptualise this problem as Reproducibility Debt (RpD). Much research has been performed to propose solutions to tackle these issues across various computational science disciplines. It is essential to identify and accumulate existing knowledge on reproducibility issues and state-of-the-art solutions so as to provide researchers and practitioners with information that enables further research activities and RpD management in practice. Objective: In the context of scientific software, we aim to characterise RpD by providing …

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On The Probability Of Necessity And Sufficiency Of Explaining Graph Neural Networks: A Lower Bound Optimization Approach, Ruichu Cai, Yuxuan Zhu, Xuexin Chen, Yuan Fang, Min Wu, Jie Qiao, Zhifeng Hao Apr 2025

On The Probability Of Necessity And Sufficiency Of Explaining Graph Neural Networks: A Lower Bound Optimization Approach, Ruichu Cai, Yuxuan Zhu, Xuexin Chen, Yuan Fang, Min Wu, Jie Qiao, Zhifeng Hao

Research Collection School Of Computing and Information Systems

The explainability of Graph Neural Networks (GNNs) is critical to various GNN applications, yet it remains a significant challenge. A convincing explanation should be both necessary and sufficient simultaneously. However, existing GNN explaining approaches focus on only one of the two aspects, necessity or sufficiency, or a heuristic trade-off between the two. Theoretically, the Probability of Necessity and Sufficiency (PNS) holds the potential to identify the most necessary and sufficient explanation since it can mathematically quantify the necessity and sufficiency of an explanation. Nevertheless, the difficulty of obtaining PNS due to non-monotonicity and the challenge of counterfactual estimation limit its …

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Use Of Search Tools In Software Development: A Study Of Microservice-Based Team Projects, Yi Meng Lau, Christian Michael Koh, Lingxiao Jiang Apr 2025

Use Of Search Tools In Software Development: A Study Of Microservice-Based Team Projects, Yi Meng Lau, Christian Michael Koh, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Universities are increasingly integrating real-world projects into software engineering curricula to preparestudents for careers involving complex concepts like Microservices Architecture (MSA). Students frequentlystruggle with such concepts within limited class time and turn to various search tools and online resources for additional help. Search tools are also widely used in the software development industry. While search engines, like Google and Yahoo!, can provide quick solutions, they pose the risk of information overload. Large Language Models (LLMs) such as ChatGPT, offer the advantage of delivering more precise answers. Studies have shown that LLMs can comprehend codes, assist in system architectural design, and …

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Frame-Voyager: Learning To Query Frames For Video Large Language Models, Sicheng Yu, Chengkai Jin, Huanyu Wang, Zhenghao Chen, Sheng Jin, Zhongrong Zuo, Xiaolei Xu, Zhenbang Sun, Bingni Zhang, Jiawei Wu, Hao Zhang, Qianru Sun Apr 2025

Frame-Voyager: Learning To Query Frames For Video Large Language Models, Sicheng Yu, Chengkai Jin, Huanyu Wang, Zhenghao Chen, Sheng Jin, Zhongrong Zuo, Xiaolei Xu, Zhenbang Sun, Bingni Zhang, Jiawei Wu, Hao Zhang, Qianru Sun

Research Collection School Of Computing and Information Systems

Video Large Language Models (Video-LLMs) have made remarkable progress in video understanding tasks. However, they are constrained by the maximum length of input tokens, making it impractical to input entire videos. Existing frame selection approaches, such as uniform frame sampling and text-frame retrieval, fail to account for the information density variations in the videos or the complex instructions in the tasks, leading to sub-optimal performance. In this paper, we propose Frame-Voyager that learns to query informative frame combinations, based on the given textual queries in the task. To train Frame-Voyager, we introduce a new data collection and labeling pipeline, by …

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Enmob: Unveil The Behavior With Multi-Flow Analysis Of Encrypted App Traffic, Mengmeng Ge, Ruitao Feng, Likun Liu, Xiangzhan Yu, Sachidananda Vinay, Xiaofei Xie, Yang Liu Apr 2025

Enmob: Unveil The Behavior With Multi-Flow Analysis Of Encrypted App Traffic, Mengmeng Ge, Ruitao Feng, Likun Liu, Xiangzhan Yu, Sachidananda Vinay, Xiaofei Xie, Yang Liu

Research Collection School Of Computing and Information Systems

In the contemporary digital landscape, mobile applications have become the predominant conduit for internet connectivity and daily tasks. Simultaneously, the advent of application encryption technology has safeguarded users’ privacy. However, this encryption, while fortifying privacy, introduces challenges to security by hindering the effective management of network applications within encrypted data streams. Conventional detection methods for encrypted application traffic, relying heavily on statistical metrics like payload, packet size, and distribution, are constrained to single traffic flows, often yielding results of limited specificity. To address this limitation, our paper introduces an innovative approach that elucidates the multi-flow nature of application behavior traffic …

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Does Chatgpt-Permitted Assessments Help Students Generate Better Answers And Learn More?, Michelle L. F. Cheong, Yun-Chen Chen Apr 2025

Does Chatgpt-Permitted Assessments Help Students Generate Better Answers And Learn More?, Michelle L. F. Cheong, Yun-Chen Chen

Research Collection School Of Computing and Information Systems

We discuss our methodology and implementation of ChatGPT-permitted assessments for a university-level spreadsheets modelling module. Through our quantitative data analysis, our students rated ChatGPT’s answers to be incorrect on average and thus will not help them generate better answers directly, representing low “Perceived usefulness” (PU), while they rated ChatGPT 3.5 with relatively high “Perceived ease of use” (PE). They gave a good “Behavioural intention” (BI) rating indicating that they were motivated to use it in future as they could still learn more about this module by using ChatGPT 3.5. We found that both PU and PE affected BI positively, with …

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Verification Of Bit-Flip Attacks Against Quantized Neural Networks, Yedi Zhang, Lei Huang, Pengfei Gao, Fu Song, Jun Sun, Jin Song Dong Apr 2025

Verification Of Bit-Flip Attacks Against Quantized Neural Networks, Yedi Zhang, Lei Huang, Pengfei Gao, Fu Song, Jun Sun, Jin Song Dong

Research Collection School Of Computing and Information Systems

In the rapidly evolving landscape of neural network security, the resilience of neural networks against bit-flip attacks (i.e., an attacker maliciously flips an extremely small amount of bits within its parameter storage memory system to induce harmful behavior), has emerged as a relevant area of research. Existing studies suggest that quantization may serve as a viable defense against such attacks. Recognizing the documented susceptibility of real-valued neural networks to such attacks and the comparative robustness of quantized neural networks (QNNs), in this work, we introduce BFAVerifier, the first verification framework designed to formally verify the absence of bit-flip attacks against …

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Democratic Training Against Universal Adversarial Perturbations, Bing Sun, Jun Sun, Wei Zhao Apr 2025

Democratic Training Against Universal Adversarial Perturbations, Bing Sun, Jun Sun, Wei Zhao

Research Collection School Of Computing and Information Systems

Despite their advances and success, real-world deep neural networks are known to be vulnerable to adversarial attacks. Universal adversarial perturbation, an inputagnostic attack, poses a serious threat for them to be deployed in security-sensitive systems. In this case, a single universal adversarial perturbation deceives the model on a range of clean inputs without requiring input-specific optimization, which makes it particularly threatening. In this work, we observe that universal adversarial perturbations usually lead to abnormal entropy spectrum in hidden layers, which suggests that the prediction is dominated by a small number of “feature” in such cases (rather than democratically by many …

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