Bo Li
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Bo Li has a total of 225 co-authors. Here are the top co-authors by number of shared publications:
- Weiping Wang
Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China
17 shared publications - Tara N. Sainath
Google LLC
15 shared publications - Jinchao Zhang
Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China and State Key Laboratory of Cyberspace Security Defense, Beijing, China
12 shared publications - Haihui Fan
State Key Laboratory of Cyberspace Security Defense, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China
11 shared publications - Hui Ma
Chinese Academy of Sciences
9 shared publications - Xiaoyan Gu
Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China
9 shared publications
Latest Publications
- Open Access
- 9 November 2026
- Published by Association for Computing Machinery (ACM)
- p. 4671-4680
Disentangled Embedding Optimization for Diffusion-Based Dataset Distillation
- 9 November 2026
- Published by Association for Computing Machinery (ACM)
- p. 4671-4680
Open AccessDisentangled Embedding Optimization for Diffusion-Based Dataset Distillation
- Open Access
- 9 November 2026
- Published by Association for Computing Machinery (ACM)
- p. 4000-4009
Dual-stream Soft Prompt Attacks on VLMs: Coordinated Visual and Textual Prompt Injection for Stealthy Backdoors
- 9 November 2026
- Published by Association for Computing Machinery (ACM)
- p. 4000-4009
Open AccessDual-stream Soft Prompt Attacks on VLMs: Coordinated Visual and Textual Prompt Injection for Stealthy Backdoors
- Open Access
- 9 November 2026
- Published by Association for Computing Machinery (ACM)
- p. 8675-8683
Mitigating Hallucinations in Large Vision-Language Models via Visual Consistency-Guided Intervention
- 9 November 2026
- Published by Association for Computing Machinery (ACM)
- p. 8675-8683
Open AccessMitigating Hallucinations in Large Vision-Language Models via Visual Consistency-Guided Intervention
- 1 November 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Dependable and Secure Computing
- Vol. 23 (6) , 12508-12522
ThemisRB: Revocation-Aware Redactable Blockchain With Asynchronous Resilience
- 1 November 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Dependable and Secure Computing
- Vol. 23 (6) , 12508-12522
ThemisRB: Revocation-Aware Redactable Blockchain With Asynchronous Resilience
- 1 November 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Mobile Computing
- Vol. 25 (11) , 21936-21952
MarvelMail: An Encrypted Email System With Marvel Revocation Across Mobile Devices
- 1 November 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Mobile Computing
- Vol. 25 (11) , 21936-21952
MarvelMail: An Encrypted Email System With Marvel Revocation Across Mobile Devices
- Open Access
- 19 July 2026
- Published by Association for Computing Machinery (ACM)
- p. 246-256
Incentivizing Retrieval-Augmented Generation via Inner Adaptive Context Selection
- 19 July 2026
- Published by Association for Computing Machinery (ACM)
- p. 246-256
Open AccessIncentivizing Retrieval-Augmented Generation via Inner Adaptive Context Selection
- Open Access
- 19 July 2026
- Published by Association for Computing Machinery (ACM)
- p. 2611-2621
Denoise and Align: Diffusion-Driven Foreground Knowledge Prompting for Open-Vocabulary Temporal Action Detection
- 19 July 2026
- Published by Association for Computing Machinery (ACM)
- p. 2611-2621
Open AccessDenoise and Align: Diffusion-Driven Foreground Knowledge Prompting for Open-Vocabulary Temporal Action Detection
- 30 April 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Computers
- Vol. 75 (8) , 2842-2856
A Practical Dynamic Searchable Symmetric Encryption Scheme With Trusted Hardware-Assisted
Searchable Symmetric Encryption (SSE) has emerged as a practical technology to address the low-cost data outsourcing solution accompanying the growing data privacy concerns. In the pursuit of real-world deployment, researchers have emphasized the importance of supporting Boolean queries in SSE schemes. However, existing schemes struggle to handle large-scale data due to high storage overhead and poor locality in I/O. In response to this challenge, we design a two-level block index construction for locality optimization and propose an efficient Dynamic SSE scheme with trusted hardware support, satisfying locality-based backward security that are first introduced in this paper. We evaluate its performance on datasets up to billion-scale. Our encrypted index occupies only 16.1% of the size of plaintext dataset, which is 27.0×, 21.9×, and 11.4× smaller than conventional OXT and SGX-based BISEN, POSUP schemes, respectively, while index generation is 1612.7×, 22.5×, and 7.3× faster. Most queries achieve subsecond latency, incurring no more than 25% additional overhead compared to the full-text search engine ElasticSearch. To our best knowledge, it is the first practical SSE scheme which has achieved sub-second response time on disk-based index with minimal storage overhead.
- 30 April 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Computers
- Vol. 75 (8) , 2842-2856
A Practical Dynamic Searchable Symmetric Encryption Scheme With Trusted Hardware-Assisted
Searchable Symmetric Encryption (SSE) has emerged as a practical technology to address the low-cost data outsourcing solution accompanying the growing data privacy concerns. In the pursuit of real-world deployment, researchers have emphasized the importance of supporting Boolean queries in SSE schemes. However, existing schemes struggle to handle large-scale data due to high storage overhead and poor locality in I/O. In response to this challenge, we design a two-level block index construction for locality optimization and propose an efficient Dynamic SSE scheme with trusted hardware support, satisfying locality-based backward security that are first introduced in this paper. We evaluate its performance on datasets up to billion-scale. Our encrypted index occupies only 16.1% of the size of plaintext dataset, which is 27.0×, 21.9×, and 11.4× smaller than conventional OXT and SGX-based BISEN, POSUP schemes, respectively, while index generation is 1612.7×, 22.5×, and 7.3× faster. Most queries achieve subsecond latency, incurring no more than 25% additional overhead compared to the full-text search engine ElasticSearch. To our best knowledge, it is the first practical SSE scheme which has achieved sub-second response time on disk-based index with minimal storage overhead.
- 5 March 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Information Forensics and Security
- Vol. 21 (15566013) , 2698-2712
MithrilRB: Resource-Efficient Redactable Blockchain With Single-Use Authorization
Redactable blockchains preserve the integrity of hash links while enabling authorized redactions to comply with regulatory requirements. However, existing permissioned solutions suffer from three severe issues. First, fine-grained privilege control incurs significant storage overhead, especially in the case of single-use authorization. Second, the reliance on bilinear pairings in chameleon hash leads to significant performance degradation when handling large-scale redaction requests. Finally, multiple incorporated components often unconsciously introduce centralized entities, undermining the decentralized nature. In this paper, we propose MithrilRB, a resource-efficient and decentralized redactable blockchain with single-use authorization. Specifically, we introduce a privilege control mechanism with our proposed multi-authority attribute-based signature (MA-ABS) and the threshold BLS signature, achieving fine-grained single-use authorization and direct user revocation without extra ciphertext storage. We also design a pairing-free non-interactive threshold chameleon hash (PNITCH), which enhances efficiency and is better suited for large-scale redaction requests. Moreover, MithrilRB eliminates centralized trust points that hold secret information, ensuring fully decentralization-compatible functional integration in redactable blockchains. Finally, we implement MithrilRB, and the experimental results demonstrate that MithrilRB significantly outperforms existing solutions in both computational efficiency and storage requirements.
- 5 March 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Information Forensics and Security
- Vol. 21 (15566013) , 2698-2712
MithrilRB: Resource-Efficient Redactable Blockchain With Single-Use Authorization
Redactable blockchains preserve the integrity of hash links while enabling authorized redactions to comply with regulatory requirements. However, existing permissioned solutions suffer from three severe issues. First, fine-grained privilege control incurs significant storage overhead, especially in the case of single-use authorization. Second, the reliance on bilinear pairings in chameleon hash leads to significant performance degradation when handling large-scale redaction requests. Finally, multiple incorporated components often unconsciously introduce centralized entities, undermining the decentralized nature. In this paper, we propose MithrilRB, a resource-efficient and decentralized redactable blockchain with single-use authorization. Specifically, we introduce a privilege control mechanism with our proposed multi-authority attribute-based signature (MA-ABS) and the threshold BLS signature, achieving fine-grained single-use authorization and direct user revocation without extra ciphertext storage. We also design a pairing-free non-interactive threshold chameleon hash (PNITCH), which enhances efficiency and is better suited for large-scale redaction requests. Moreover, MithrilRB eliminates centralized trust points that hold secret information, ensuring fully decentralization-compatible functional integration in redactable blockchains. Finally, we implement MithrilRB, and the experimental results demonstrate that MithrilRB significantly outperforms existing solutions in both computational efficiency and storage requirements.
- 9 February 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Computers
- Vol. 75 (5) , 1922-1936
Reducing Write Amplification in LSM-Trees Through Orchestrated Fine-Grained Compaction and Persistent Memory
This paper investigates how to leverage emerging non-volatile memory (NVM) to enhance the performance of Log-Structure Merge (LSM) tree based key-value (KV) stores. We propose KVFG-DB, which efficiently integrates fine-block granularity and single-NVM-level compaction, to deliver high write and read performance with minimal write amplification and reduced write stalls. KVFG-DB leverages a streamlined SSTable layout called CSSTable to manage data blocks (each containing ordered KV pairs) and their indexes (i.e., the minimal and maximal keys of every block), optimizing both storage costs and compaction performance. It organizes the LSM-tree data as CSSTables into a single level on NVM, with the left area serving as a buffer to receive flushed data with substantially greater capacity, and the right area storing compacted data in a global order among CSSTables. A fine-grained compaction is then performed under various conditions to select the most relevant data blocks with intersecting keys from CSSTables in both areas, facilitating byte-addressable, fast parallel execution across multiple threads. As a result, KVFG-DB adaptively compacts data and quickly moves them from the left area to the right area to enhance performance efficiency, significantly reducing write amplification and further mitigating write stalls. Our extensive experimental studies demonstrate that KVFG-DB achieves$1.2{\boldsymbol{\times}}$ and$2{\boldsymbol{\times}}$ lower write amplification, compared with state-of-the-art KV stores MioDB and SLM-DB. Accordingly, KVFG-DB shows a$1.1{\boldsymbol{\times}}$ and$7.1{\boldsymbol{\times}}$ improvement in random write performance compared to them, with tail latency reduced by$1.1{\boldsymbol{\times}}$ and$7{\boldsymbol{\times}}$ , respectively.- 9 February 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Computers
- Vol. 75 (5) , 1922-1936
Reducing Write Amplification in LSM-Trees Through Orchestrated Fine-Grained Compaction and Persistent Memory
This paper investigates how to leverage emerging non-volatile memory (NVM) to enhance the performance of Log-Structure Merge (LSM) tree based key-value (KV) stores. We propose KVFG-DB, which efficiently integrates fine-block granularity and single-NVM-level compaction, to deliver high write and read performance with minimal write amplification and reduced write stalls. KVFG-DB leverages a streamlined SSTable layout called CSSTable to manage data blocks (each containing ordered KV pairs) and their indexes (i.e., the minimal and maximal keys of every block), optimizing both storage costs and compaction performance. It organizes the LSM-tree data as CSSTables into a single level on NVM, with the left area serving as a buffer to receive flushed data with substantially greater capacity, and the right area storing compacted data in a global order among CSSTables. A fine-grained compaction is then performed under various conditions to select the most relevant data blocks with intersecting keys from CSSTables in both areas, facilitating byte-addressable, fast parallel execution across multiple threads. As a result, KVFG-DB adaptively compacts data and quickly moves them from the left area to the right area to enhance performance efficiency, significantly reducing write amplification and further mitigating write stalls. Our extensive experimental studies demonstrate that KVFG-DB achieves$1.2{\boldsymbol{\times}}$ and$2{\boldsymbol{\times}}$ lower write amplification, compared with state-of-the-art KV stores MioDB and SLM-DB. Accordingly, KVFG-DB shows a$1.1{\boldsymbol{\times}}$ and$7.1{\boldsymbol{\times}}$ improvement in random write performance compared to them, with tail latency reduced by$1.1{\boldsymbol{\times}}$ and$7{\boldsymbol{\times}}$ , respectively.