Zobrazeno 1 - 10
of 38
pro vyhledávání: '"DING, STEVEN H. H."'
Autor:
Song, Leo, Ding, Steven H. H., Tian, Yuan, Li, Li Tao, Charland, Philippe, Walenstein, Andrew
A Software Bill of Materials (SBoM) is a detailed inventory of all components, libraries, and modules in a software artifact, providing traceability throughout the software supply chain. With the increasing popularity of JavaScript in software engine
Externí odkaz:
http://arxiv.org/abs/2408.16198
Software vulnerabilities are a challenge in cybersecurity. Manual security patches are often difficult and slow to be deployed, while new vulnerabilities are created. Binary code vulnerability detection is less studied and more complex compared to so
Externí odkaz:
http://arxiv.org/abs/2404.08562
Autor:
Hao, Huizi, Hasan, Kazi Amit, Qin, Hong, Macedo, Marcos, Tian, Yuan, Ding, Steven H. H., Hassan, Ahmed E.
ChatGPT has significantly impacted software development practices, providing substantial assistance to developers in a variety of tasks, including coding, testing, and debugging. Despite its widespread adoption, the impact of ChatGPT as an assistant
Externí odkaz:
http://arxiv.org/abs/2403.10468
It is becoming increasingly important in the software industry, especially with the growing complexity of software ecosystems and the emphasis on security and compliance for manufacturers to inventory software used on their systems. A Software-Bill-o
Externí odkaz:
http://arxiv.org/abs/2403.08799
The practice of code reuse is crucial in software development for a faster and more efficient development lifecycle. In reality, however, code reuse practices lack proper control, resulting in issues such as vulnerability propagation and intellectual
Externí odkaz:
http://arxiv.org/abs/2307.10631
Malware currently presents a number of serious threats to computer users. Signature-based malware detection methods are limited in detecting new malware samples that are significantly different from known ones. Therefore, machine learning-based metho
Externí odkaz:
http://arxiv.org/abs/1909.06865
Most of privacy protection studies for textual data focus on removing explicit sensitive identifiers. However, personal writing style, as a strong indicator of the authorship, is often neglected. Recent studies, such as SynTF, have shown promising re
Externí odkaz:
http://arxiv.org/abs/1907.08736
Autor:
Ding, Steven H. H.
The Internet provides an ideal anonymous channel for concealing computer-mediated malicious activities, as the network-based origins of critical electronic textual evidence (e.g., emails, blogs, forum posts, chat log etc.) can be easily repudiated. A
Authorship analysis (AA) is the study of unveiling the hidden properties of authors from a body of exponentially exploding textual data. It extracts an author's identity and sociolinguistic characteristics based on the reflected writing styles in the
Externí odkaz:
http://arxiv.org/abs/1606.01219
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