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A deep learning system typically suffers from a lack of reproducibility that is partially rooted in hardware or software implementation details. The irreproducibility leads to skepticism in deep learning technologies and it can hinder them…
Financial fraud is the cause of multi-billion dollar losses annually. Traditionally, fraud detection systems rely on rules due to their transparency and interpretability, key features in domains where decisions need to be explained.…
Like classical software, quantum software systems rely on automated testing. However, their inherently probabilistic outputs make them susceptible to quantum flakiness -- tests that pass or fail inconsistently without code changes. Such…
Privacy-focused cryptoassets like Monero are intentionally difficult to trace. Over the years, several traceability heuristics have been proposed, most of which have been rendered ineffective with subsequent protocol upgrades. Between 2019…
Financial speculators often seek to increase their potential gains with leverage. Debt is a popular form of leverage, and with over 39.88B USD of total value locked (TVL), the Decentralized Finance (DeFi) lending markets are thriving.…
Deep learning has gained substantial popularity in recent years. Developers mainly rely on libraries and tools to add deep learning capabilities to their software. What kinds of bugs are frequently found in such software? What are the root…
Repackaging is a serious threat to the Android ecosystem as it deprives app developers of their benefits, contributes to spreading malware on users' devices, and increases the workload of market maintainers. In the space of six years, the…
Ethereum smart contracts, which are autonomous decentralized applications on the blockchain that manage assets often exceeding millions of dollars, have become primary targets for cyberattacks. In 2023 alone, such vulnerabilities led to…
Blockchain recently became very popular due to its use in cryptocurrencies and potential application in various domains (e.g., retail, healthcare, insurance). The smart contract is a key part of blockchain systems and specifies an agreement…
The decentralized and trustless nature of cryptocurrencies and blockchain technology leads to a shift in the digital world. The possibility to execute small programs, called smart contracts, on cryptocurrencies like Ethereum opened doors to…
Deep Learning (DL) is finding its way into a growing number of mobile software applications. These software applications, named as DL based mobile applications (abbreviated as mobile DL apps) integrate DL models trained using large-scale…
While tool learning significantly enhances the capabilities of large language models (LLMs), it also introduces substantial security risks. Prior research has revealed various vulnerabilities in traditional LLMs during tool learning.…
DeFi investment agents, systems that use AI for autonomous on-chain trading, have attained over USD 3 billion in combined token valuations since late 2024. We survey over 1,900 AI-tagged crypto projects, filter to investment-focused agents,…
This study critically examines the methodological rigor in credit card fraud detection research, revealing how fundamental evaluation flaws can overshadow algorithmic sophistication. Through deliberate experimentation with improper…
As modern software extensively uses free open source packages as dependencies, developers have to regularly pull in new third-party code through frequent updates. However, without a proper review of every incoming change, vulnerable and…
Deep learning (DL) applications, built upon a heterogeneous and complex DL stack (e.g., Nvidia GPU, Linux, CUDA driver, Python runtime, and TensorFlow), are subject to software and hardware dependencies across the DL stack. One challenge in…
Coded blockchains have acquired prominence as a promising solution to reduce storage costs and facilitate scalability. Within this class, Luby Transform (LT) coded blockchains are an appealing choice for scalability owing to the…
With the popularization of smartphones, red packets have been widely used in mobile apps. However, the issues of fraud associated with them have also become increasingly prominent. As reported in user reviews from mobile app markets, many…
Deep Reinforcement Learning (DRL) has achieved remarkable success in domains requiring sequential decision-making, motivating its application to cybersecurity problems. However, transitioning DRL from laboratory simulations to bespoke cyber…
Non-deterministically behaving (i.e., flaky) tests hamper regression testing as they destroy trust and waste computational and human resources. Eradicating flakiness in test suites is therefore an important goal, but automated debugging…