Demo Data from VLDB 2026 / reviewers in the wild / expert
Wenze Mao
dblp:352/0706
· DBLP profile ↗
2ranked-venue papers
2as first author
2since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 first-author · 1 since 2021Security and privacy · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Cryptographic primitives and cryptanalysis · 60% Authentication and access control · 40% | |
| Computer networks
1 paper |
Internet of things and sensor networks · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cryptographic primitives and cryptanalysis › public-key cryptography › digital signatures › multiparty signatures
aggregate signatures |
0.8 | 1 | 2024 | Locally Verifiable Batch Authentication in IoMT · IEEE Trans. Inf. Forensics Secur. 2024 |
Authentication and access control › cryptographic authentication
batch authentication |
0.8 | 1 | 2024 | Locally Verifiable Batch Authentication in IoMT · IEEE Trans. Inf. Forensics Secur. 2024 |
Cryptographic primitives and cryptanalysis › public-key cryptography
digital signatures |
0.8 | 1 | 2024 | Locally Verifiable Batch Authentication in IoMT · IEEE Trans. Inf. Forensics Secur. 2024 |
Authentication and access control › cryptographic authentication
identity-based authentication |
0.8 | 1 | 2024 | Locally Verifiable Batch Authentication in IoMT · IEEE Trans. Inf. Forensics Secur. 2024 |
Cryptographic primitives and cryptanalysis › public-key cryptography › digital signatures
locally verifiable signature |
0.8 | 1 | 2024 | Locally Verifiable Batch Authentication in IoMT · IEEE Trans. Inf. Forensics Secur. 2024 |
Internet of things and sensor networks › iot applications
internet of medical things |
0.2 | 1 | 2024 | Locally Verifiable Batch Authentication in IoMT · IEEE Trans. Inf. Forensics Secur. 2024 |
Methods — techniques the papers use, named apart from their topics
signcryption · 1.5inverse framework · 1.5hybrid hash · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Locally Verifiable Batch Authentication in IoMTabstractInternet of Medical Things (IoMT) technology has gained a lot of attention. In the IoMT system, IoT devices collect and upload patient data through sensors, and doctors treat them remotely. In this process, doctors need to verify the correctness of the patient’s body data in bulk, a function that requires aggregated signature technology to achieve. However, due to the limitation that traditional verification of aggregated signatures requires access to all messages, doctors cannot efficiently verify the correctness of a particular piece of data. This will result in a significant additional verification overhead. Therefore, the efficiency problem of data batch authentication remains unsolved but imperative. In this paper, we propose an identity-based locally verifiable aggregated signature, (ID-LVEAS), that enables efficient local verification of patient data in IoMT. Building on top of both hybrid hash and inverse framework, we instantiate an ID-LVEAS scheme and prove its security in the EU-CMA security model. Based on ID-LVEAS, we further propose ID-based locally verifiable signcryption (ID-LVASC) that supports both confidentiality and integrity. We also present an instantiation and an application into IoMT from the proposed ID-LVASC. We conduct extensive experiments on the ID-LVEAS and ID-LVASC design. The results show that both cost constantly 0.01s for the verification, independent of the number of messages, which means our research has great promise for application in IoMT. Wenze Mao, Peng Jiang 0007, Liehuang Zhu |
IEEE Trans. Inf. Forensics Secur. | 1 |
| 2023 | BTAA: Blockchain and TEE-Assisted Authentication for IoT SystemsabstractIn recent years, Internet of Things (IoT) technology has gained a lot of attention. With the development of IoT technology, it comes the need for devices with different trust domains to interact and collaborate. In order to protect the security and reliability of the communication between devices in different trust domains, it raises the concerns about the technology of cross-domain authentication. Traditional cross-domain authentication methods may lead to heavy key management overhead or depend on trusted third parties, while existing blockchain-based cross-domain authentication schemes do not prevent the possibility of mischief by malicious domain managers. In this article, we design an efficient Blockchain and trusted execution environment (TEE)-assisted secure device authentication scheme for cross-domain IoT system, called blockchain and TEE-assisted authentication. Our solution solves the problem that managers are not fully trusted, which in turns protect the security and reliability in the blockchain-based cross-domain communication. Specifically, blockchain is introduced to build trust between different domains, the identity-based signatures are used to verify the identity information of devices and the TEE is introduced to prevent the possibility of mischief by domain managers. Finally, our experiments show that the introduction of TEE has greatly improved system security with a low-efficiency reduction, which proves that our scheme can achieve highly secure distributed IoT authentication. Wenze Mao, Peng Jiang 0007, Liehuang Zhu |
IEEE Internet Things J. | 1 |