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Yuanhao Wang 0002

dblp:178/5079-2 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2021
0000-0003-2632-2326ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 2 · 2 first-author · 2 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 protocols and secure computation · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cryptographic protocols and secure computation
private set intersection
0.512021
Private Set Intersection With Authorization Over Outsourced Encrypted Datasets · IEEE Trans. Inf. Forensics Secur. 2021
Cryptographic protocols and secure computation
secure outsourcing
0.512021
Private Set Intersection With Authorization Over Outsourced Encrypted Datasets · IEEE Trans. Inf. Forensics Secur. 2021
Cloud and datacenter computing
encrypted data
0.112021
Private Set Intersection With Authorization Over Outsourced Encrypted Datasets · IEEE Trans. Inf. Forensics Secur. 2021

Methods — techniques the papers use, named apart from their topics

random oracle model · 1.0number-theoretic assumptions · 1.0
YearPublicationVenuePosition
2021 Public Key Encryption with Fuzzy Matching
Yuanhao Wang 0002, Qiong Huang 0001, Hongbo Li 0004, Meiyan Xiao, Jianye Huang 0001, Guomin Yang
ProvSec1
2021 Private Set Intersection With Authorization Over Outsourced Encrypted Datasets
abstract
Thanks to its convenience and cost-savings feature, cloud computing ushers a new era. Yet its security and privacy issues must not be neglected. Private set intersection (PSI) is useful and important in many cloud computing applications, such as document similarity, genetic paternity and data mining. The cloud server performs intersection operations on two outsourced encrypted datasets of data owners. In the existing protocols, however, data owners cannot decide whether to use all or part of their encrypted data to compute the intersection, nor can they specify whom to compare with. In this paper, we introduce an enhanced notion of outsourced PSI, called authorized PSI (APSI), which supports flexible authorization and cross-type authorized comparison of datasets. To demonstrate this notion, we propose a concrete APSI protocol, and prove it to be secure in the random oracle model based on simple number-theoretic assumptions. Experimental results show that our APSI protocol has performance comparable with existing related outsourced PSI protocols.
Yuanhao Wang 0002, Qiong Huang 0001, Hongbo Li 0004, Meiyan Xiao, Sha Ma, Willy Susilo
IEEE Trans. Inf. Forensics Secur.1