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Caiqun Shi

dblp:389/5025 · DBLP profile ↗
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4ranked-venue papers
1as first author
4since 2021 · last 2026
0009-0002-3666-0863ORCID · corroborated

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

Computer networks · 2 · 2 since 2021Systems, architecture and hardware · 1 · 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
3 papers
Privacy and data protection · 64% Cryptographic primitives and cryptanalysis · 30% Systems and software security · 6%
Computer architecture, parallel and distributed computing, and storage systems
2 papers
Cloud and datacenter computing · 100%

Topics — the 8 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Privacy and data protection
electronic health records
0.912025
Privacy-Preserving and Autonomous-Path Access Delegation for Mobile Cloud Healthcare Systems · IEEE Trans. Mob. Comput. 2025
Privacy and data protection
privacy-preserving data sharing
0.912025
Privacy-Preserving and Autonomous-Path Access Delegation for Mobile Cloud Healthcare Systems · IEEE Trans. Mob. Comput. 2025
Cryptographic primitives and cryptanalysis
proxy re-encryption
0.912025
Privacy-Preserving and Autonomous-Path Access Delegation for Mobile Cloud Healthcare Systems · IEEE Trans. Mob. Comput. 2025
Cryptographic primitives and cryptanalysis › encryption
access control encryption
0.812024
Cross-Domain Inner-Product Access Control Encryption for Secure EMR Flow in Cloud Edge · IEEE Trans. Inf. Forensics Secur. 2024
Privacy and data protection › health data privacy
electronic health record sharing
0.812024
Cross-Domain Inner-Product Access Control Encryption for Secure EMR Flow in Cloud Edge · IEEE Trans. Inf. Forensics Secur. 2024
Systems and software security › cloud security
cloud storage security
0.312026
FSEdit: Privacy-Preserving and Security-Enhanced Controllable Editing Framework for Cloud Storage · IEEE Trans. Computers 2026
Cloud and datacenter computing
mobile cloud computing
0.312025
Privacy-Preserving and Autonomous-Path Access Delegation for Mobile Cloud Healthcare Systems · IEEE Trans. Mob. Comput. 2025
Cloud and datacenter computing › edge and fog computing
cloud-edge computing
0.212024
Cross-Domain Inner-Product Access Control Encryption for Secure EMR Flow in Cloud Edge · IEEE Trans. Inf. Forensics Secur. 2024

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

multi-hop delegation · 1.7inner-product encryption · 1.6inner product encryption · 1.6threshold structure-preserving signature · 1.5non-interactive zero-knowledge proof · 1.5distributed key generation · 1.5
YearPublicationVenuePosition
2026 FSEdit: Privacy-Preserving and Security-Enhanced Controllable Editing Framework for Cloud Storage
Qinlong Huang, Caiqun Shi, Xiyu Liang
IEEE Trans. Computers2
2026 TSFlow: Time-Aware Secure Flow Control for Fine-Grained Data Sharing in Mobile Edge-Cloud
abstract
The rise of edge-cloud computing has accelerated data sharing among mobile users. To resist malicious senders within organizations from leaking sensitive data, access control encryption (ACE) schemes have been employed to secure data f lows, in which each sender obtains an encryption key according to the access control policy to encrypt the data, and a sanitizer (i.e., the edge node) inspects all shared data between the sender and receiver. Although attribute-based ACE schemes have been put forward to support fine-grained data sharing, they lack temporal constraints on write control, which is crucial in mobile data sharing scenarios, and have high sanitization overhead at the edge node. In addition, they only provide selective security and are therefore vulnerable to adaptive adversaries. To this end, we propose TSFlow, a time-aware secure flow control framework in mobile edge-cloud that regulates which senders can transmit data to which receivers during the authorized time interval, preventing malicious sending by expired senders. At its core is TA-ACE, a time-aware attribute-based ACE that issues each sender an encryption key tied to an expressive access structure and a time interval. Encrypted data can be sanitized at the edge only if it is well-formed with a valid encryption key and encrypted within the time interval, and any legitimate receiver satisfying the access structure can decrypt the sanitized ciphertext. We formally prove that TA-ACE satisfies the adaptive no-read and no-write rules, and demonstrate the reasonable efficiency of TSFlow through experiments for secure flow control in mobile edge-cloud.
Qinlong Huang, Caiqun Shi, Yudi Zhang 0001, Willy Susilo
IEEE Trans. Mob. Comput.3
2025 Privacy-Preserving and Autonomous-Path Access Delegation for Mobile Cloud Healthcare Systems
abstract
Mobile cloud healthcare systems are gaining popularity due to their remote data collection through mobile devices and flexible data access through cloud services. The collected electronic health records (EHRs) are generally encrypted on mobile devices before being uploaded to the cloud, and accessed only by specific users. This incurs inconvenience when re-sharing EHRs with new receivers, especially in heterogeneous scenarios. Although cross-domain proxy re-encryption (CD-PRE) schemes have been studied to transform ciphertexts between different cryptosystems, they can neither support EHRs' controlled multi-hop delegation between trusted delegatees chosen by the delegator nor prevent EHRs' privacy inference through delegatees' information. To this end, we present CAP-PRE for mobile cloud healthcare systems, which is a multi-hop CD-PRE scheme that supports lightweight encryption and re-encryption key generation on mobile devices, as well as privacy-preserving and autonomous-path access delegation. In CAP-PRE, the delegator creates a delegation path that includes preferred delegatees, and generates corresponding re-encryption keys which enables the cloud server to convert the collected ciphertext to an inner product ciphertext for privacy-preserving EHR re-sharing and pass the access rights along the delegation path for controlled multi-hop delegation. We finally prove the security of CAP-PRE and show the better performance of CAP-PRE with extensive experiments.
Genghui Chi, Qinlong Huang, Caiqun Shi
IEEE Trans. Mob. Comput.3
2024 Cross-Domain Inner-Product Access Control Encryption for Secure EMR Flow in Cloud Edge
abstract
The quality of medical services is improved by sharing electronic medical records (EMRs) across multiple medical institutions via cloud edge. However, EMRs contain private information about patients, and cloud servers are untrustworthy, thus they cannot be shared arbitrarily among senders and receivers. Access control encryption (ACE) is a preferred technique that produces encrypted EMRs and then restricts the capabilities of both senders and receivers to enforce the EMR flow via sanitizers. However, existing cross-domain ACE schemes employ a single sender authority to issue encryption keys for senders, which suffers from single point of failure and encryption key escrow that the sender authority can public EMRs arbitrarily. Moreover, they only support coarse-grained access structures such as AND gates, which is not suitable for flexible EMR sharing among medical institutions. To this end, we propose a cross-domain inner-product ACE (CD-IPACE) scheme that features decentralized encryption key generation and fine-grained access structures. Specifically, we construct CD-IPACE from inner-product encryption, threshold structure-preserving signature instantiated with a distributed key generation protocol, and non-interactive zero-knowledge proof, which prevents individual sender authorities from sending ciphertexts, and also protects both data and receiver privacy. Then, we design a secure EMR flow system in cloud edge named ESFlow based on CD-IPACE, which employs edge nodes as sanitizers to check encrypted EMRs and discard illegal ones. Finally, we demonstrate the security and practicality of ESFlow via formal security analysis and extensive experiments.
Caiqun Shi, Qinlong Huang, Rui Jian, Genghui Chi
IEEE Trans. Inf. Forensics Secur.1