Chengdu, China

Jie Liang

This inventor holds 2 USPTO granted patents and 2 published patent applications. Top assignee: Sichuan University. Active years: 2019.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Jie Liang. Retrieved from https://idiyas.com/inventor/jie-liang-onzzwb3d

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 2 

% Patents Active = 100.0

Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2019

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2 patents (USPTO):Explore Patents

Title: Innovations by Jie Liang in Malicious Code Detection

Introduction

Jie Liang is an accomplished inventor based in Chengdu, China. He has made significant contributions to the field of malicious software detection, holding two patents that showcase his innovative approaches. His work primarily focuses on enhancing the security of Android applications through advanced detection methods.

Latest Patents

Jie Liang's latest patents include a "Malicious code detection method based on community structure analysis." This invention presents a novel approach to detecting Android malicious code by analyzing the community structure of the program. The method involves obtaining critical static feature information, creating a function call graph, and performing cycle division and analysis to extract features for machine learning. This allows for rapid internal structure analysis and malicious code detection, especially in the context of numerous Android applications generated by repackaging technology.

Another significant patent is the "Malicious software clustering method expressed based on TLSH feature." This invention utilizes the Cuckoo Sandbox to analyze malicious software and acquire various character string features. The TLSH algorithm compresses these features into manageable groups, while the OPTICS algorithm enables automatic classification of malicious software families. This method employs unsupervised learning, improving clustering speed and efficiency while reducing the influence of input parameters.

Career Highlights

Jie Liang is affiliated with Sichuan University, where he continues to advance research in the field of cybersecurity. His innovative methods have garnered attention for their effectiveness in detecting and classifying malicious software, contributing to the overall safety of digital environments.

Collaborations

Jie Liang has collaborated with notable colleagues, including Junfeng Wang and Xiaosong Zhang. Their combined expertise enhances the research and development of innovative solutions in the realm of malicious software detection.

Conclusion

Jie Liang's contributions to the field of malicious code detection through his innovative patents demonstrate his commitment to improving cybersecurity. His work not only addresses current challenges but also paves the way for future advancements in the industry.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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