Related papers: BeDivFuzz: Integrating Behavioral Diversity into G…
Gene regulatory networks (GRNs) are complex systems in which many genes regulate mutually to adapt the cell state to environmental conditions. In addition to function, the GRNs possess several kinds of robustness. This robustness means that…
To ensure the reliability of DNN systems and address the test generation problem for neural networks, this paper proposes a fuzzing test generation technique based on many-objective optimization algorithms. Traditional fuzz testing employs…
Generative modeling offers new opportunities for bioacoustics, enabling the synthesis of realistic animal vocalizations that could support biomonitoring efforts and supplement scarce data for endangered species. However, directly generating…
Mutation-based fuzzing typically uses an initial set of non-crashing seed inputs (a corpus) from which to generate new inputs by mutation. A corpus of potential seeds will often contain thousands of similar inputs. This lack of diversity…
Measuring the similarity of two files is an important task in malware analysis, with fuzzy hash functions being a popular approach. Traditional fuzzy hash functions are data agnostic: they do not learn from a particular dataset how to…
Fuzzy systems may be considered as knowledge-based systems that incorporates human knowledge into their knowledge base through fuzzy rules and fuzzy membership functions. The intent of this study is to present a fuzzy knowledge integration…
Objective: Machine learning (ML) models are increasingly used to generate electrical stimulation patterns in neuroprosthetic devices such as visual prostheses. While these models promise precise and personalized control, they also introduce…
BACKGROUND: Software engineers must be vigilant in preventing and correcting vulnerabilities and other critical bugs. In servicing this need, numerous tools and techniques have been developed to assist developers. Fuzzers, by autonomously…
As one of the most successful generative models, diffusion models have demonstrated remarkable efficacy in synthesizing high-quality images. These models learn the underlying high-dimensional data distribution in an unsupervised manner.…
Directed fuzzing performs best for targeted program testing via estimating the impact of each input in reaching predefined program points. But due to insufficient analysis of the program structure and lack of flexibility and configurability…
Deep generative models have achieved tremendous success in structure-based drug design in recent years, especially for generating 3D ligand molecules that bind to specific protein pocket. Notably, diffusion models have transformed ligand…
Climate change is reshaping species interactions and movement across fragmented landscapes. Despite this, most mathematical models assume random diffusion, overlooking the influence of directed movement. Here, we develop a graph based…
Directed Grey-box Fuzzing (DGF) has emerged as a widely adopted technique for crash reproduction and patch testing, leveraging its capability to precisely navigate toward target locations and exploit vulnerabilities. However, current DGF…
Visual design instructors often provide multi-modal feedback, mixing annotations with text. Prior theory emphasizes the importance of actionable feedback, where "actionability" lies on a spectrum--from surfacing relevant design concepts to…
Mutation-based fuzzing is popular and effective in discovering unseen code and exposing bugs. However, only a few studies have concentrated on quantifying the importance of input bytes, which refers to the degree to which a byte contributes…
In recent years, following tremendous achievements in Reinforcement Learning, a great deal of interest has been devoted to ML models for sequential decision-making. Together with these scientific breakthroughs/advances, research has been…
Evolving software is challenging, even more when it exists in many different variants. Such software evolves not only in time, but also in space--another dimension of complexity. While evolution in space is supported by a variety of…
Many modern software systems are enabled by deep learning libraries such as TensorFlow and PyTorch. As deep learning is now prevalent, the security of deep learning libraries is a key concern. Fuzzing deep learning libraries presents two…
Given the audio-visual clip of the speaker, facial reaction generation aims to predict the listener's facial reactions. The challenge lies in capturing the relevance between video and audio while balancing appropriateness, realism, and…
Extensive research shows that more species-rich assemblages are generally more productive and efficient in resource use than comparable assemblages with fewer species. But the question of how diversity simultaneously affects the wide…