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学者姓名：刘西蒙
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Federated learning (FL) has become a popular mode of learning, allowing model training without the need to share data. Unfortunately, it remains vulnerable to privacy leakage and poisoning attacks, which compromise user data security and degrade model quality. Therefore, numerous privacy-preserving frameworks have been proposed, among which mask-based framework has certain advantages in terms of efficiency and functionality. However, it is more susceptible to poisoning attacks from malicious users, and current works lack practical means to detect such attacks within this framework. To overcome this challenge, we present DefendFL, an efficient, privacy-preserving, and poisoning-detectable mask-based FL scheme. We first leverage collinearity mask to protect users' gradient privacy. Then, cosine similarity is utilized to detect masked gradients to identify poisonous gradients. Meanwhile, a verification mechanism is designed to detect the mask, ensuring the mask's validity in aggregation and preventing poisoning attacks by intentionally changing the mask. Finally, we resist poisoning attacks by removing malicious gradients or lowering their weights in aggregation. Through security analysis and experimental evaluation, DefendFL can effectively detect and mitigate poisoning attacks while outperforming existing privacy-preserving detection works in efficiency.
Keyword ：
Federated learning (FL) Federated learning (FL) poisoning attacks poisoning attacks poisoning detection poisoning detection privacy protection privacy protection secure aggregation secure aggregation
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| GB/T 7714 | Liu, Jiao , Li, Xinghua , Liu, Ximeng et al. DefendFL: A Privacy-Preserving Federated Learning Scheme Against Poisoning Attacks [J]. | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS , 2024 . |
| MLA | Liu, Jiao et al. "DefendFL: A Privacy-Preserving Federated Learning Scheme Against Poisoning Attacks" . | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2024) . |
| APA | Liu, Jiao , Li, Xinghua , Liu, Ximeng , Zhang, Haiyan , Miao, Yinbin , Deng, Robert H. . DefendFL: A Privacy-Preserving Federated Learning Scheme Against Poisoning Attacks . | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS , 2024 . |
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加密DNS协议最初被设计用于保护用户和递归解析器之间(用户-递归侧)的DNS通信隐私.目前,加密DNS协议获得了广泛应用.然而,递归解析器和权威服务器之间(递归-权威侧)的DNS通信仍遭受着大量隐私威胁.历经4年的标准化进程,互联网工程任务组在2024年2月正式发布RFC 9539,提出可利用加密DNS协议来保障递归-权威侧的DNS通信隐私.聚焦于在递归-权威侧部署加密DNS协议所带来的隐私收益,提出评估互联网域名隐私收益的方法.针对243万个流行域名和4万个敏感域名,结合1 058个顶级域名的区域文件,分析权威服务器所托管的域名数量,从而判定目标域名的隐私收益等级.测量结果表明,超过90%的域名可获得递归-权威侧部署加密DNS协议的隐私保护,但是6.28%的敏感域名无法从递归-权威侧部署加密DNS协议中获得隐私收益.此外,一些高流行度的域名也没有获得足够的隐私收益.相较于大型域名托管商,小型域名托管商可为域名提供更高的隐私收益.将域名部署于仅托管单个域名的权威服务器上会极大地损害递归-权威侧加密DNS协议的隐私保护效果,管理人员应重新审视域名托管服务.
Keyword ：
互联网测量 互联网测量 加密DNS 加密DNS 域名系统 域名系统 隐私保护 隐私保护
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| GB/T 7714 | 段丽莹 , 李瑞烜 , 刘西蒙 et al. 递归-权威侧部署加密DNS协议的隐私收益评估方法及测量分析 [J]. | 网络与信息安全学报 , 2024 , 10 (5) : 71-80 . |
| MLA | 段丽莹 et al. "递归-权威侧部署加密DNS协议的隐私收益评估方法及测量分析" . | 网络与信息安全学报 10 . 5 (2024) : 71-80 . |
| APA | 段丽莹 , 李瑞烜 , 刘西蒙 , 邵俊 , 刘保君 . 递归-权威侧部署加密DNS协议的隐私收益评估方法及测量分析 . | 网络与信息安全学报 , 2024 , 10 (5) , 71-80 . |
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Abnormal email bounces seriously disrupt user lives and company transactions. Proliferating security protocols and protection strategies have made email delivery increasingly complex. A natural question is how and why email delivery fails in the wild. Filling this knowledge gap requires a representative global email delivery dataset, which is rarely disclosed by email service providers (ESPs). In this paper, we first systematically reveal the scale and root causes of email bounces, and evaluate the email squatting risk in the real world. Through a 15-month passive dataset from a large ESP, we present a unique global view of 298M emails delivered to 3M receiver mail servers in 169 countries. We find that 38M (12.93%) emails fail to be delivered in the first attempt, about one-third of which could be successfully delivered after retrying, while the rest are permanently undeliverable. Delving deeper into bounce reasons, we observe that poor server reputation and network communication quality are significant factors leading to temporary email bounces. In particular, spam blocklists affect many normal email deliveries. The misconfiguration of authentication mechanisms and email address typos result in many permanently undeliverable emails. More seriously, many email addresses with significant residual value can be exploited by squatting attackers. Overall, we call for the community to revisit email delivery failures, especially to improve standards for email bounce reporting and resolution.
Keyword ：
Email security Email security Email squatting Email squatting Internet measurement Internet measurement
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| GB/T 7714 | Li, Ruixuan , Xiao, Shaodong , Liu, Baojun et al. Bounce in the Wild: A Deep Dive into Email Delivery Failures from a Large Email Service Provider [J]. | PROCEEDINGS OF THE 2024 ACM INTERNET MEASUREMENT CONFERENCE, IMC 2024 , 2024 : 659-673 . |
| MLA | Li, Ruixuan et al. "Bounce in the Wild: A Deep Dive into Email Delivery Failures from a Large Email Service Provider" . | PROCEEDINGS OF THE 2024 ACM INTERNET MEASUREMENT CONFERENCE, IMC 2024 (2024) : 659-673 . |
| APA | Li, Ruixuan , Xiao, Shaodong , Liu, Baojun , Lin, Yanzhong , Duan, Haixin , Pan, Qingfeng et al. Bounce in the Wild: A Deep Dive into Email Delivery Failures from a Large Email Service Provider . | PROCEEDINGS OF THE 2024 ACM INTERNET MEASUREMENT CONFERENCE, IMC 2024 , 2024 , 659-673 . |
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With the popularity of blockchains, low transaction throughput has become a significant bottleneck in applications such as cryptocurrencies. Payment channel networks (PCNs) have received attention as a way to improve throughput. However, due to the difficulty of predicting future transactions for nodes, the transactions are prone to failure when the channel balances do not meet required conditions. It has been shown that increasing buffers (queues) in PCNs can increase the success rate of transactions and throughput. Nevertheless, there is no effective transaction scheduling strategy in buffers when transaction values are flexible and variable. To solve this problem, we first formulate the Scheduling Problem in PCNs (named PSP), and then prove it is NP-hard. We design a neural network solver based on the Sequence to Sequence (Seq2Seq) architecture and train the solver using the reinforcement learning method. With the solver, we first give two scheduling strategies to maximize transaction throughput, and then design a PCN simulator for performance evaluation. Extensive experiments are conducted to show the superiority and various performances of our proposal and illustrate that our proposal can get a significant advantage in terms of the transaction throughput compared to the existing works.
Keyword ：
Blockchain Blockchain deep reinforcement learning deep reinforcement learning off-chain payments off-chain payments payment channel networks payment channel networks transaction scheduling transaction scheduling
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| GB/T 7714 | Ren, Zhe , Wang, Zihao , Li, Xinghua et al. Deep Reinforcement Learning Based Scheduling Strategy in Blockchain Payment Channel Networks [J]. | IEEE-ACM TRANSACTIONS ON NETWORKING , 2024 . |
| MLA | Ren, Zhe et al. "Deep Reinforcement Learning Based Scheduling Strategy in Blockchain Payment Channel Networks" . | IEEE-ACM TRANSACTIONS ON NETWORKING (2024) . |
| APA | Ren, Zhe , Wang, Zihao , Li, Xinghua , Miao, Yinbin , Li, Zhuowen , Liu, Ximeng et al. Deep Reinforcement Learning Based Scheduling Strategy in Blockchain Payment Channel Networks . | IEEE-ACM TRANSACTIONS ON NETWORKING , 2024 . |
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国家自然科学基金委员会作为国家科研资助体系的重要组成部分，着力促进信息化与科研活动、科研管理体系的融合。科学基金数据作为新型生产要素，是数字化、网络化、智能化的基础，已快速融入科学基金服务管理等各个环节，用于持续提升科学基金资助效能，为推动基础研究高质量发展。本文介绍现有自然科学基金数据现状，分析目前数据管理中面临的挑战，设计了适用于现状的通用数据中台架构(以下简称“数据中台”),构造了面向数据中台的安全系统结构，并给出基于数据中台的数据安全管理实践，该工作可以实现自然科学基金委数据中台中存储的数据在创建、存储、发布、访问、处理、重用过程中保证数据全生命周期安全性，有效促进自然科学基金委数据业务化数据长效优质管理的建设发展。
Keyword ：
国家自然科学基金 国家自然科学基金 数据中台 数据中台 数据安全 数据安全 数据管理 数据管理 服务架构 服务架构 系统性改革 系统性改革
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| GB/T 7714 | 郝艳妮 , 李东 , 韩陆超 et al. 面向数据中台的全周期数据安全管理研究与初步实践——以国家自然科学基金数据管理为例 [J]. | 中国科学基金 , 2024 , 38 (04) : 696-702 . |
| MLA | 郝艳妮 et al. "面向数据中台的全周期数据安全管理研究与初步实践——以国家自然科学基金数据管理为例" . | 中国科学基金 38 . 04 (2024) : 696-702 . |
| APA | 郝艳妮 , 李东 , 韩陆超 , 彭升辉 , 刘西蒙 . 面向数据中台的全周期数据安全管理研究与初步实践——以国家自然科学基金数据管理为例 . | 中国科学基金 , 2024 , 38 (04) , 696-702 . |
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As an emerging distributed ledger technology, blockchain provides multi-party trust between unreliable devices to share data and resources cooperatively, which facilitates the Internet of Vehicles (IoV) applications. In the typical blockchain enabled IoV (BIoV) scenarios, based on the data of common interest collected by various sensors, the IoV devices jointly maintain the world state in the form of address-balance pairs as the proof for transaction issuing and validation, where Ethereum like blockchain is used as the finite-state machine driven by the transactions. However, with the extension of the IoV network, an enormous number of accounts leads to the explosive growth of the state data, which has been the main challenge for BIoV with resource-limited devices. This paper proposes a modular-based adaptive bit-width compression (ABC) scheme to reduce the state data storage on each device by representing the address as a remainder with a shorter bit-width. Besides, a new transaction validation method is designed with the support of the XOR filter, which guarantees that the core functions of the blockchain can still be performed normally with the proposed scheme applied. Theoretical analysis and simulation results show that the compression ratio for the address data could be more than 80%, which dramatically improves the scalability of BIoV system. In addition, the extra privacy-preserving property is introduced with the compression scheme because the account information is unrecoverable from the remainders. IEEE
Keyword ：
Address compression Address compression blockchain-enabled Internet of Vehicles (BIoV) blockchain-enabled Internet of Vehicles (BIoV) Blockchains Blockchains Data structures Data structures Distributed ledger Distributed ledger modular arithmetic modular arithmetic privacy-preserving privacy-preserving Proposals Proposals Real-time systems Real-time systems Scalability Scalability Smart contracts Smart contracts
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| GB/T 7714 | Guo, Z. , Liu, Q. , Gao, Z. et al. Modular-based Compression Scheme for Address Data in the Blockchain System for IoV Applications [J]. | IEEE Transactions on Vehicular Technology , 2024 , 73 (10) : 1-16 . |
| MLA | Guo, Z. et al. "Modular-based Compression Scheme for Address Data in the Blockchain System for IoV Applications" . | IEEE Transactions on Vehicular Technology 73 . 10 (2024) : 1-16 . |
| APA | Guo, Z. , Liu, Q. , Gao, Z. , Liu, L. , Gong, Y. , Liu, X. et al. Modular-based Compression Scheme for Address Data in the Blockchain System for IoV Applications . | IEEE Transactions on Vehicular Technology , 2024 , 73 (10) , 1-16 . |
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Advanced Persistent Threats (APTs) employ sophisticated and covert tactics to infiltrate target systems, leading to increased vulnerability and an elevated risk of exposure. Consequently, it is essential for us to proactively create an extensive and clearly outlined attack chain for APTs in order to effectively combat these threats. Unlike traditional malware or application threats, APTs can sidestep cyber security efforts and cause severe damage to organizations or even state security. Nonetheless, earlier methods struggle to accurately track APTs and may face a dependency explosion issue, as identifying the intricate and complex unknown malicious activities within APTs proves to be challenging. In this paper, we propose and build an approach, T-trace, which constructs the events provenance graphs by analyzing the correlations among logs. The approach precisely finds the log communities with tensor decomposition and calculates significance scores to extract the events. The APTs can be inferred by discovering the event communities and constructing the provenance graph with log correlation. In the experiment, we used DARPA data sets and launched four current practical APTs. Compared with current approaches, the results show that T-trace can efficiently reduce time cost by 90% and achieve a 92% accuracy rate in constructing the provenance graph, which can be practically applied in APTs provenance.
Keyword ：
APTs APTs Behavioral sciences Behavioral sciences Correlation Correlation Explosions Explosions Feature extraction Feature extraction forensic system forensic system log analysis log analysis provenance provenance Remote control Remote control tensor decomposition tensor decomposition Tensors Tensors Training data Training data
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| GB/T 7714 | Li, Teng , Liu, Ximeng , Qiao, Wei et al. T-Trace: Constructing the APTs Provenance Graphs Through Multiple Syslogs Correlation [J]. | IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING , 2024 , 21 (3) : 1179-1195 . |
| MLA | Li, Teng et al. "T-Trace: Constructing the APTs Provenance Graphs Through Multiple Syslogs Correlation" . | IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 21 . 3 (2024) : 1179-1195 . |
| APA | Li, Teng , Liu, Ximeng , Qiao, Wei , Zhu, Xiongjie , Shen, Yulong , Ma, Jianfeng . T-Trace: Constructing the APTs Provenance Graphs Through Multiple Syslogs Correlation . | IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING , 2024 , 21 (3) , 1179-1195 . |
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Adversarial examples (AEs), which are maliciously hand-crafted by adding perturbations to benign images, reveal the vulnerability of deep neural networks (DNNs) and have been used as a benchmark for evaluating model robustness. With great efforts have been devoted to generating AEs with stronger attack ability, the visual quality of AEs is generally neglected in previous studies. The lack of a good quality measure of AEs makes it very hard to compare the relative merits of attack techniques and is hindering technological advancement. How to evaluate the visual quality of AEs remains an understudied and unsolved problem. In this work, we make the first attempt to fill the gap by presenting an image quality assessment method specifically designed for AEs. Towards this goal, we first construct a new database, called AdvDB, developed on diverse adversarial examples with elaborated annotations. We also propose a detection-based structural similarity index (AdvDSS) for adversarial example perceptual quality assessment. Specifically, the visual saliency for capturing the near-threshold adversarial distortions is first detected via human visual system (HVS) techniques and then the structural similarity is extracted to predict the quality score. Moreover, we further propose AEQA for overall adversarial example quality assessment by integrating the perceptual quality and attack intensity of AEs. Extensive experiments validate that the proposed AdvDSS achieves state-of-the-art performance which is more consistent with human opinions. © 2024 ACM.
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| GB/T 7714 | Yin, Jia-Li , Chen, Menghao , Han, Jin et al. Adversarial Example Quality Assessment: A Large-scale Dataset and Strong Baseline [C] . 2024 : 4786-4794 . |
| MLA | Yin, Jia-Li et al. "Adversarial Example Quality Assessment: A Large-scale Dataset and Strong Baseline" . (2024) : 4786-4794 . |
| APA | Yin, Jia-Li , Chen, Menghao , Han, Jin , Chen, Bo-Hao , Liu, Ximeng . Adversarial Example Quality Assessment: A Large-scale Dataset and Strong Baseline . (2024) : 4786-4794 . |
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Edge storage is becoming an increasingly appealing alternative for data owners (DOs), offering benefits like decreased latency and minimized bandwidth usage compared to traditional cloud storage solutions. Nonetheless, stored data within edge servers (ESs) remains vulnerable to disruptions. Existing data integrity auditing schemes face challenges such as the costs of third-party auditors (TPA), unreliable and delayed audit results, and effective management of data inspection concerning time and energy consumption. To tackle these challenges, we introduce DIVO, a decentralized data inspection approach. DIVO leverages ESs as each others’ auditors, removing the necessity for a centralized party, thereby mitigating collision risks and potential biases in audit results. We propose a game-theoretic technique to efficiently manage data inspection and verification offloading to ESs. By formulating the decision-making issue as a strategic game for optimally allocating verification tasks among multiple ESs, we establish the presence of Nash equilibrium and design a strategy to attain it. Through comprehensive security and performance evaluations, DIVO has been shown to operate securely within the random oracle model while delivering notable efficiency improvements over recent methods. Our analysis highlights that DIVO surpasses a wide range of recent approaches in both communication and computation efficiency. © 2002-2012 IEEE.
Keyword ：
Data integrity auditing Data integrity auditing edge storage edge storage game theory game theory provable security provable security
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| GB/T 7714 | Seyedi, Z. , Rahmati, F. , Ali, M. et al. Decentralized data integrity inspection offloading in edge computing systems using potential games [J]. | IEEE Transactions on Mobile Computing , 2024 . |
| MLA | Seyedi, Z. et al. "Decentralized data integrity inspection offloading in edge computing systems using potential games" . | IEEE Transactions on Mobile Computing (2024) . |
| APA | Seyedi, Z. , Rahmati, F. , Ali, M. , Liu, X. . Decentralized data integrity inspection offloading in edge computing systems using potential games . | IEEE Transactions on Mobile Computing , 2024 . |
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Ensuring the security of data outsourced to cloud is a prerequisite for the application of Internet of Things (IoT) in actual production. Secure search based on homomorphic encryption can provide high security and require no expensive setup procedure, which can be applied to resource-limited devices in IoT. However, the existing schemes usually have poor search performance and do not consider multi-owner setting. To solve these issues, we propose an efficient homomorphic encryption-based secure search scheme in multi-owner setting. Specifically, we construct a secure search protocol based on multi-key homomorphic encryption, which can be deployed in multi-owner setting. Meanwhile, we improve the efficiency of our scheme by optimizing the search algorithm. Formal security analysis proves that our scheme is secure against chosen plaintext attack, and extensive experiments demonstrate that our scheme improves the search efficiency by 1000x when compared with state-of-the-art solutions. © 2014 IEEE.
Keyword ：
fully homomorphic encryption fully homomorphic encryption internet of things internet of things multi-owner setting multi-owner setting Secure search Secure search
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| GB/T 7714 | Wang, Y. , Miao, Y. , Li, X. et al. Efficient Homomorphic Encryption-Based Secure Search in Multi-owner Setting for Internet of Things (IoT) [J]. | IEEE Internet of Things Journal , 2024 . |
| MLA | Wang, Y. et al. "Efficient Homomorphic Encryption-Based Secure Search in Multi-owner Setting for Internet of Things (IoT)" . | IEEE Internet of Things Journal (2024) . |
| APA | Wang, Y. , Miao, Y. , Li, X. , Leng, T. , Liu, Z. , Liu, X. et al. Efficient Homomorphic Encryption-Based Secure Search in Multi-owner Setting for Internet of Things (IoT) . | IEEE Internet of Things Journal , 2024 . |
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