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学者姓名：公备
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Abstract ：
Dynamic symmetric searchable encryption (DSSE) allows clients to perform keyword searches and updates on encrypted databases outsourced to cloud servers. Ensuring forward privacy is a crucial security property for DSSE schemes to protect data privacy. However, existing forward-private DSSE schemes face significant limitations: they either rely on an honest-but-curious server, assuming it always returns correct search results without providing verification functionality, or they lack support for fine-grained attribute-based searches and access control. As a result, these schemes cannot be directly applied to attribute-based databases. In this paper, we propose the first verifiable forward-private DSSE scheme suitable for attribute-based databases. Specifically, we construct a secure index based on attribute elements to realize fine-grained searches on attribute-value type databases while ensuring the forward privacy of the scheme. We also design a novel verification tag using symmetric homomorphic encryption to verify the correctness of search results. In addition, our scheme achieves access control functionality to ensure that different users can only access authorized files. Experimental evaluations show that our scheme has advantage in the update, search and verification processes. And the security analysis proves our scheme is secure.
Keyword ：
Attribute-value type databases Attribute-value type databases Forward privacy Forward privacy Verification Verification Dynamic symmetric searchable encryption Dynamic symmetric searchable encryption
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| GB/T 7714 | Peng, Tianqi , Gong, Bei , Sun, Pengxuan . Toward privacy-preserving verifiable DSSE for attribute-based cloud computing system [J]. | JOURNAL OF SUPERCOMPUTING , 2025 , 81 (2) . |
| MLA | Peng, Tianqi 等. "Toward privacy-preserving verifiable DSSE for attribute-based cloud computing system" . | JOURNAL OF SUPERCOMPUTING 81 . 2 (2025) . |
| APA | Peng, Tianqi , Gong, Bei , Sun, Pengxuan . Toward privacy-preserving verifiable DSSE for attribute-based cloud computing system . | JOURNAL OF SUPERCOMPUTING , 2025 , 81 (2) . |
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Abstract ：
In the era of data-driven artificial intelligence, the widespread deployment of IoT devices has amplified concerns around privacy and data security. Federated learning (FL) offers a promising solution by enabling local model training without exposing raw data, effectively mitigating privacy risks. However, the inherent heterogeneity of IoT data leads to significant disparities in data distributions across different clients, negatively impacting the global model's performance. Furthermore, conventional fixed differential privacy mechanisms lack the adaptability needed to dynamically adjust to the evolving requirements of different training phases, limiting their effectiveness in privacy-preserving federated learning. To address these challenges, we propose a federated learning framework called AWE-DPFL, which integrates adaptive weight fusion and dynamic privacy budget adjustment mechanisms. AWE-DPFL employs a dynamic privacy budget adjustment strategy to allocate privacy budgets based on the variance in client model updates, thereby improving model performance while ensuring robust privacy protection. Additionally, the adaptive weight fusion mechanism assigns different weights to each client's model, taking into account data heterogeneity and quality, which leads to an enhanced global model that better reflects individual client contributions. Moreover, AWE-DPFL incorporates meta-learning alongside differential privacy techniques during local model training, resulting in an effective balance between data privacy and model performance. This approach not only improves model adaptability and generalization across diverse data distributions but also ensures that privacy requirements are met throughout the training process. Experimental evaluations demonstrate that AWE-DPFL significantly outperforms existing approaches on the MNIST, FashionMNIST, HAR, and Edge-IIoTset datasets, showcasing its effectiveness as a federated learning solution for real-world IoT applications.
Keyword ：
Weight fusion Weight fusion Federated learning Federated learning Internet of things Internet of things Privacy budget adjustment Privacy budget adjustment Differential privacy Differential privacy
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| GB/T 7714 | Zheng, Guiping , Gong, Bei , Guo, Chong et al. AWE-DPFL: Adaptive weighting and dynamic privacy budget federated learning for heterogeneous data in IoT [J]. | COMPUTERS & ELECTRICAL ENGINEERING , 2025 , 123 . |
| MLA | Zheng, Guiping et al. "AWE-DPFL: Adaptive weighting and dynamic privacy budget federated learning for heterogeneous data in IoT" . | COMPUTERS & ELECTRICAL ENGINEERING 123 (2025) . |
| APA | Zheng, Guiping , Gong, Bei , Guo, Chong , Peng, Tianqi , Gong, Mowei . AWE-DPFL: Adaptive weighting and dynamic privacy budget federated learning for heterogeneous data in IoT . | COMPUTERS & ELECTRICAL ENGINEERING , 2025 , 123 . |
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Abstract ：
In the cloud-assisted industrial Internet of Things (IIoT), since the cloud server is not always trusted, the leakage of data privacy becomes a critical problem. Dynamic symmetric searchable encryption (DSSE) allows for the secure retrieval of outsourced data stored on cloud servers while ensuring data privacy. Forward privacy and backward privacy are necessary security requirements for DSSE. However, most existing schemes either trade the server's large storage overhead for forward privacy or trade efficiency/overhead for weak backward privacy. These schemes cannot fully meet the security requirements of cloud-assisted IIoT systems. We propose a fast and firmly secure SSE scheme called Veruna to address these limitations. To this end, we design a new state chain structure, which can not only ensure forward privacy with less storage overhead of the server but also achieve strong backward privacy with only a few cryptographic operations in the server. Security analysis proves that our scheme possesses forward privacy and Type-II backward privacy. Compared with many state-of-the-art schemes, our scheme has an advantage in search and update performance. The high efficiency and robust security make Veruna an ideal scheme for deployment in cloud-assisted IIoT systems.
Keyword ：
state chain structure state chain structure symmetric searchable encryption symmetric searchable encryption forward and backward privacy forward and backward privacy cloud-assisted IIoT cloud-assisted IIoT
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| GB/T 7714 | Peng, Tianqi , Gong, Bei , Tu, Shanshan et al. Forward and Backward Private Searchable Encryption for Cloud-Assisted Industrial IoT [J]. | SENSORS , 2024 , 24 (23) . |
| MLA | Peng, Tianqi et al. "Forward and Backward Private Searchable Encryption for Cloud-Assisted Industrial IoT" . | SENSORS 24 . 23 (2024) . |
| APA | Peng, Tianqi , Gong, Bei , Tu, Shanshan , Namoun, Abdallah , Alshmrany, Sami , Waqas, Muhammad et al. Forward and Backward Private Searchable Encryption for Cloud-Assisted Industrial IoT . | SENSORS , 2024 , 24 (23) . |
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Abstract ：
The Internet of Things (IoT) is a heterogeneous network composed of numerous dynamically connected devices. While it brings convenience, the IoT also faces serious challenges in data security. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptography method that supports fine-grained access control, offering a solution to the IoT's security issues. However, existing CP-ABE schemes are inefficient and unsuitable for IoT devices with limited computing resources. To address this problem, this paper proposes an efficient pairing-free CP-ABE scheme for the IoT. The scheme is based on lightweight elliptic curve scalar multiplication and supports multi-authority and verifiable outsourced decryption. The proposed scheme satisfies indistinguishability against chosen-plaintext attacks (CPA) under the elliptic curve decisional Diffie-Hellman (ECDDH) problem. Performance analysis shows that our proposed scheme is more efficient and better suited to the IoT environment compared to existing schemes.
Keyword ：
ciphertext-policy attribute-based encryption ciphertext-policy attribute-based encryption pairing-free pairing-free access control access control Internet of Things Internet of Things
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| GB/T 7714 | Guo, Chong , Gong, Bei , Waqas, Muhammad et al. An Efficient Pairing-Free Ciphertext-Policy Attribute-Based Encryption Scheme for Internet of Things [J]. | SENSORS , 2024 , 24 (21) . |
| MLA | Guo, Chong et al. "An Efficient Pairing-Free Ciphertext-Policy Attribute-Based Encryption Scheme for Internet of Things" . | SENSORS 24 . 21 (2024) . |
| APA | Guo, Chong , Gong, Bei , Waqas, Muhammad , Alasmary, Hisham , Tu, Shanshan , Chen, Sheng . An Efficient Pairing-Free Ciphertext-Policy Attribute-Based Encryption Scheme for Internet of Things . | SENSORS , 2024 , 24 (21) . |
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Abstract ：
Internet of things (IoT) development tends to reduce the reliance on centralized servers. The zero-trust distributed system combined with blockchain technology has become a hot topic in IoT research. However, distribution data storage services and different blockchain protocols make network interoperability and cross-platform more complex. Relay chain is a promising cross-chain technology that solves the complexity and compatibility issues associated with blockchain cross-chain transactions by utilizing relay blockchains as cross-chain connectors. Yet relay chain cross-chain transactions need to collect asset information and implement asset transactions via two-way peg. Due to the release of user transaction information, there is the issue of privacy leakage. In this article, we propose a cross-chain privacy protection protocol based on the Groth16 zero-knowledge proof algorithm and coin-mixing technology, which changes the authentication mechanism and uses a combination of generating functions to map virtual external addresses in transactions. It allows fast cross-chain anonymous transactions while hiding the genuine user's address. The experiment shows that, in a zero-trust IoT context, our scheme can effectively protect user privacy information, accomplish controlled transaction traceability operations, and guarantee cross-chain transaction security.
Keyword ：
relay chain relay chain privacy protection privacy protection Zero trust Zero trust vritual address vritual address groth16 groth16
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| GB/T 7714 | Yang, Yinghong , Bai, Fenhua , Yu, Zhuo et al. An Anonymous and Super visory Cross-chain Privacy Protection Protocol for Zero-trust IoT Application [J]. | ACM TRANSACTIONS ON SENSOR NETWORKS , 2024 , 20 (2) . |
| MLA | Yang, Yinghong et al. "An Anonymous and Super visory Cross-chain Privacy Protection Protocol for Zero-trust IoT Application" . | ACM TRANSACTIONS ON SENSOR NETWORKS 20 . 2 (2024) . |
| APA | Yang, Yinghong , Bai, Fenhua , Yu, Zhuo , Shen, Tao , Liu, Yingli , Gong, Bei . An Anonymous and Super visory Cross-chain Privacy Protection Protocol for Zero-trust IoT Application . | ACM TRANSACTIONS ON SENSOR NETWORKS , 2024 , 20 (2) . |
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Abstract ：
To solve the problems of vote forgery and malicious election of candidate nodes in the Raft consensus algorithm, we combine zero trust with the Raft consensus algorithm and propose a secure and efficient consensus algorithm -Verifiable Secret Sharing Byzantine Fault Tolerance Raft Consensus Algorithm (VSSB-Raft). The VSSB-Raft consensus algorithm realizes zero trust through the supervisor node and secret sharing algorithm without the invisible trust between nodes required by the algorithm. Meanwhile, the VSSB-Raft consensus algorithm uses the SM2 signature algorithm to realize the characteristics of zero trust requiring authentication before data use. In addition, by introducing the NDN network, we redesign the communication between nodes and guarantee the communication quality among nodes. The VSSB-Raft consensus algorithm proposed in this paper can make the algorithm Byzantine fault tolerant by setting a threshold for secret sharing while maintaining the algorithm ' s complexity to be O(n). Experiments show that the VSSB-Raft consensus algorithm is secure and efficient with high throughput and low consensus latency.
Keyword ：
Blockchain Blockchain secret sharing secret sharing Byzantine fault tolerance Byzantine fault tolerance zero trust zero trust consensus algorithm consensus algorithm
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| GB/T 7714 | Tian, Siben , Bai, Fenhua , Shen, Tao et al. yVSSB-Raft: A Secure and Efficient Zero Trust Consensus Algorithm for Blockchain [J]. | ACM TRANSACTIONS ON SENSOR NETWORKS , 2024 , 20 (2) . |
| MLA | Tian, Siben et al. "yVSSB-Raft: A Secure and Efficient Zero Trust Consensus Algorithm for Blockchain" . | ACM TRANSACTIONS ON SENSOR NETWORKS 20 . 2 (2024) . |
| APA | Tian, Siben , Bai, Fenhua , Shen, Tao , Zhang, Chi , Gong, Bei . yVSSB-Raft: A Secure and Efficient Zero Trust Consensus Algorithm for Blockchain . | ACM TRANSACTIONS ON SENSOR NETWORKS , 2024 , 20 (2) . |
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Abstract ：
With the continuous development of mobile devices, mobile applications bring a lot of convenience to people's lives. The abuse of mobile device permissions is prone to the risk of privacy leakage. The existing detection technology can detect the inconsistency between the declared authority and the actual use authority. But using the third-party privacy policy as the analysis basis for SDK permissions will result in a large set of extracted declaration permissions, which will lead to identifying risky applications as normal applications during consistency comparison. The prevailing approach involves utilizing models based on TextCNN to extract information from privacy policies. However, the training of TextCNN relies on large-scale annotated datasets, leading to high costs. This paper uses BERT as the word vector extraction model to obtain private phrases from the privacy policy. And then we use cosine similarity to automatically filter permission phrase samples, reducing the workload of manual labeling. On the other hand, existing methods do not support the analysis of Chinese privacy policies. In order to solve the problem of consistency judgment between Chinese privacy policy and permission usage, we implement a BERT-based Android privacy policy and permission usage consistency analysis engine. The engine first uses static analysis to obtain the permission list of Android applications, and then combines the BERT model to achieve consistency analysis. After functional and speed testing, we found that the engine can successfully run the consistency analysis function of Chinese declaration permissions and usage permissions, and it is better than the existing detection methods.
Keyword ：
Privacy policy Privacy policy Mobile applications Mobile applications Policy conflicts Policy conflicts Text extraction Text extraction Android security Android security
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| GB/T 7714 | Tu, Tengfei , Zhang, Hua , Gong, Bei et al. Intelligent analysis of android application privacy policy and permission consistency [J]. | ARTIFICIAL INTELLIGENCE REVIEW , 2024 , 57 (7) . |
| MLA | Tu, Tengfei et al. "Intelligent analysis of android application privacy policy and permission consistency" . | ARTIFICIAL INTELLIGENCE REVIEW 57 . 7 (2024) . |
| APA | Tu, Tengfei , Zhang, Hua , Gong, Bei , Du, Daizhong , Wen, Qiaoyan . Intelligent analysis of android application privacy policy and permission consistency . | ARTIFICIAL INTELLIGENCE REVIEW , 2024 , 57 (7) . |
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Abstract ：
本发明提供一种基于预言机的边缘计算跨链算力交易方法。边缘计算将计算资源带到了网络边缘，满足了许多新兴应用对高效算力的需求。联盟链实现了不可信的交易者之间的可信算力交易。现有的大多数研究忽略了区块链之间的算力交易，这大大降低了算力的利用率。本发明设计了一种基于预言机的跨链算力交易框架。预言机作为连接区块链的中介，确保可信的跨链交易。本发明提出了一种基于预言机的算力交易机制，实现可信的链上和跨链算力交易。本发明通过效用函数综合地表示了交易者的利润、时延和能量消耗，并建立了双层Stackelberg博弈，以实现买卖双方的公平效用平衡。本发明证明了纳什均衡的存在性，并利用差分进化算法得到了最优解。
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| GB/T 7714 | 公备 , 朱光卓 , 王茜 . 一种基于预言机的边缘计算跨链算力交易方法 : CN202310635360.8[P]. | 2023-05-31 . |
| MLA | 公备 et al. "一种基于预言机的边缘计算跨链算力交易方法" : CN202310635360.8. | 2023-05-31 . |
| APA | 公备 , 朱光卓 , 王茜 . 一种基于预言机的边缘计算跨链算力交易方法 : CN202310635360.8. | 2023-05-31 . |
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Abstract ：
本发明公开了基于自编码器和双向长短时记忆网络的加密货币交易追踪方法，实现对交易网络中未来有可能出现的交易预测，达到交易追踪的目的；该预测模型可以自动学习高维非线性的网络结构，并且可以学习时间特征捕捉网络的时变特性，通过微调网络结构可以使模型适应不同尺度的网络；解决了现有方法存在的不足，提出了一种通用模型；实验结果表明该方法能够取得较好的结果。
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| GB/T 7714 | 黄静 , 丁金飞 , 韩红桂 et al. 基于自编码器和双向长短时记忆网络的加密货币交易追踪方法 : CN202310479078.5[P]. | 2023-04-28 . |
| MLA | 黄静 et al. "基于自编码器和双向长短时记忆网络的加密货币交易追踪方法" : CN202310479078.5. | 2023-04-28 . |
| APA | 黄静 , 丁金飞 , 韩红桂 , 公备 , 牛裕茸 . 基于自编码器和双向长短时记忆网络的加密货币交易追踪方法 : CN202310479078.5. | 2023-04-28 . |
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Abstract ：
本发明公开了一种适用于无线传感器网络的信任评估方法，从信任值准确性与反映攻击行为的角度出发，归纳总结了多维信任评估因子选取方案，较为全面地刻画可信关系，助力可信度量。采用基于客观信息熵理论的反馈信息融合算法实现对信任因子的主观加权计算，可以有效应对恶意反馈。使用可靠度对信任进行评估，降低不可靠数据对信任计算的影响。以及采用了风险控制，量化信任评估中网络的风险。本发明能够更加真实地反映节点的可信度，较为准确地过滤了恶意推荐或过时的推荐，能够及时感知恶意节点，降低网络中的安全隐患。
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| GB/T 7714 | 姚璐 , 公备 , 王茜 . 一种适用于无线传感器网络的信任评估方法 : CN202310022579.0[P]. | 2023-01-08 . |
| MLA | 姚璐 et al. "一种适用于无线传感器网络的信任评估方法" : CN202310022579.0. | 2023-01-08 . |
| APA | 姚璐 , 公备 , 王茜 . 一种适用于无线传感器网络的信任评估方法 : CN202310022579.0. | 2023-01-08 . |
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