Jinpeng Han
Biographic Data
| ID | 10055646 |
|---|---|
| NAME | Jinpeng Han |
| GIVEN NAMES | Jinpeng |
| FAMILY NAME | Han |
| SIGNATURE | HAN J |
| AFFILIATIONS | Xi'an Jiaotong University |
| ORCID | 0000-0002-2451-5880 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
ICyberGuard
Social manufacturing has significantly advanced the industrial Internet of Things (IIoT), integrating information technology and operation technology to enhance production efficiency and quality, and to foster new business models. This integration, however, introduces novel risks, including advanced persistent threats, which demand robust security measures to safeguard IIoT systems. This article proposes an iCyberGuard game model, tailored for II…
Multipattern Integrated Networks With Contrastive Pretraining for Graph Anomaly Detection
As a challenge of practical significance, fraud detection has great potential for telecom fraud prevention, economic crime prevention, and personal property preservation. Fraudulent activities are always buried in massive regular transactions, making it hard to find them. Traditional rule-based approaches need multiple domain-specific rules and multistep verification, which limits their transferability and efficiency. Machine learning-based metho…
No prominent works on this page.
ICyberGuard
Social manufacturing has significantly advanced the industrial Internet of Things (IIoT), integrating information technology and operation technology to enhance production efficiency and quality, and to foster new business models. This integration, however, introduces novel risks, including advanced persistent threats, which demand robust security measures to safeguard IIoT systems. This article proposes an iCyberGuard game model, tailored for II…
Multipattern Integrated Networks With Contrastive Pretraining for Graph Anomaly Detection
As a challenge of practical significance, fraud detection has great potential for telecom fraud prevention, economic crime prevention, and personal property preservation. Fraudulent activities are always buried in massive regular transactions, making it hard to find them. Traditional rule-based approaches need multiple domain-specific rules and multistep verification, which limits their transferability and efficiency. Machine learning-based metho…
Computer Science (2 works) · Advanced Graph Neural Networks (1 work) · Anomaly detection (1 work) · Artificial Intelligence (1 work) · Combinatorics (1 work) · Complex Network Analysis Techniques (1 work) · Computer security (1 work) · Critical infrastructure (1 work) · Graph (1 work) · Graph theory (1 work)