Related papers: HardTaint: Production-Run Dynamic Taint Analysis v…
Dynamic taint analysis (DTA) is widely used by various applications to track information flow during runtime execution. Existing DTA techniques use rule-based taint-propagation, which is neither accurate (i.e., high false positive) nor…
Dynamic taint analysis (DTA) has been widely used in various security-relevant scenarios that need to track the runtime information flow of programs. Dynamic binary instrumentation (DBI) is a prevalent technique in achieving effective…
Information flows are intrinsic properties of an multi-stage manufacturing systems (MMS). In computer security, a basic information flow tracking technique is dynamic taint analysis (DTA). DTA tracks taint propagation from one data variable…
Generic taint analysis is a pivotal technique in software security. However, it suffers from staggeringly high overhead. In this paper, we explore the hypothesis whether just-in-time (JIT) generation of fast paths for tracking taint can…
Memory corruption attacks remain the primary threat for computer security. Information flow tracking or taint analysis has been proven to be effective against most memory corruption attacks. However, there are two shortcomings with current…
Data races are critical issues in multithreaded program, leading to unpredictable, catastrophic and difficult-to-diagnose problems. Despite the extensive in-house testing, data races often escape to deployed software and manifest in…
Dataflow tracking with Dynamic Taint Analysis (DTA) is an important method in systems security with many applications, including exploit analysis, guided fuzzing, and side-channel information leak detection. However, DTA is fundamentally…
Over the years, static taint analysis emerged as the analysis of choice to detect some of the most common web application vulnerabilities, such as SQL injection (SQLi) and cross-site scripting (XSS)~\cite{OWASP}. Furthermore, from an…
Modern software systems have become increasingly complex, which makes them difficult to test and validate. Detecting software partial anomalies in complex systems at runtime can assist with handling unintended software behaviors, avoiding…
Dynamic taint tracking is the process of assigning label to variables in a program and then tracking the flow of the labels as the program executes. Dynamic taint tracking for java applications is achieved by instrumenting the application…
Predicting drug-target binding affinity (DTA) is essential for identifying potential therapeutic candidates in drug discovery. However, most existing models rely heavily on static protein structures, often overlooking the dynamic nature of…
Drug target binding affinity (DTA) is a key criterion for drug screening. Existing experimental methods are time-consuming and rely on limited structural and domain information. While learning-based methods can model sequence and structural…
The increasing complexity of the software/hardware stack of modern supercomputers results in explosion of parameters. The performance analysis becomes a truly experimental science, even more challenging in the presence of massive…
Meta-analysis of diagnostic test accuracy (DTA) is the powerful statistical method for synthesizing and evaluating the diagnostic capacity of the medical tests and has been extensively used by clinical physicians and healthcare…
Modern large-scale scientific discovery requires multidisciplinary collaboration across diverse computing facilities, including High Performance Computing (HPC) machines and the Edge-to-Cloud continuum. Integrated data analysis plays a…
Due to the importance of Android app quality assurance, many automated GUI testing tools have been developed. Although the test algorithms have been improved, the impact of GUI rendering has been overlooked. On the one hand, setting a long…
We present RETA (Relative Timing Analysis), a differential timing analysis technique to verify the impact of an update on the execution time of embedded software. Timing analysis is computationally expensive and labor intensive. Software…
Generating tests that can reveal performance issues in large and complex software systems within a reasonable amount of time is a challenging task. On one hand, there are numerous combinations of input data values to explore. On the other…
We introduce Tuna, a static analysis approach to optimizing deep neural network programs. The optimization of tensor operations such as convolutions and matrix multiplications is the key to improving the performance of deep neural networks.…
The diversity of web configuration interfaces for IoT devices has exacerbated issues such as inadequate permission controls and insecure interfaces, resulting in various vulnerabilities. Owing to the varying interface configurations across…