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47th International Conference on Very Large data Bases, VLDB 2021

作者： Li, Dongjie Lv, Siyi Huang, Yanyu Liu, Yijing Li, Tong Liu, Zheli Guo, Liang College of Cyber Science Nankai University China Tianjin Key Laboratory of Network and Data Security Technology Nankai University China Huawei Technology Co. Ltd Shenzhen China

The range query on encrypted databases is usually implemented using the order-preserving encryption (OPE) technique which preserves the order of plaintexts. Since the frequency leakage of plaintexts makes OPE vulnerable to frequency-analyzing attacks, some frequency-hiding order-preserving encryption (FH-OPE) schemes are proposed. However, existing FH-OPE schemes require either the large client storage of size O(n) or O(log n) rounds of interactions for each query, where n is the total number of plaintexts. To this end, we propose a FH-OPE scheme that achieves the small client storage without additional client-server interactions. In detail, our scheme achieves O(N) client storage and 1 interaction per query, where N is the number of distinct plaintexts and N ≤ n. Especially, our scheme has a remarkable performance when N © 2021, VLDB Endowment. All rights reserved.

关键词： Cryptography

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Privacy-preserving Trajectory data Release Hierarchical Model 13

Privacy-preserving Trajectory Data Release Hierarchical Mode...

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13th International Conference on Communication and network security, ICCNS 2023

作者： Zhang, Qian Zhang, Xing Shi, Wei Key Laboratory of Security for Network and Data in Industrial Internet of Liaoning Province Liaoning University of Technology Jinzhou121000 China

ISBN: (纸本)9798400707964

The development of positioning technology and mobile intelligent devices has given rise to plentiful location-based services and generated much trajectory data. The publication and analysis of trajectory data bring convenience to users, but also carry the risk of sensitive information being exposed. Existing trajectory data publication models mostly only consider the processing of static trajectory data and do not effectively combine spatiotemporal properties, and the problem of dishonest third parties unconsciously collecting data from other parties also occurs from time to time. This paper proposes a new privacy-preserving trajectory data publication hierarchical model based on secure two-party computation. The user layer, the cloud layer, and the local server layer collaborate to complete the trajectory publishing process. Experimental statistics have proved that the proposed method has better privacy and data availability. © 2023 ACM.

关键词： Trajectories

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PathAFL: Path-Coverage Assisted Fuzzing 20

PathAFL: Path-Coverage Assisted Fuzzing

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15th ACM Asia Conference on Computer and Communications security, ASIA CCS 2020

作者： Yan, Shengbo Wu, Chenlu Li, Hang Shao, Wei Jia, Chunfu Nankai University College of Cyber Science TianJin China Nankai University College of Artificial Intelligence TianJin China Nankai University College of Cyber Science TianJin Key Laboratory of Network and Data Security Technology TianJin300350 China

ISBN: (纸本)9781450367509

Fuzzing is an effective method to find software bugs and vulnerabilities. One of the most useful techniques is the coverage-guided fuzzing, whose key element is the tracing code coverage information. Existing coverage-guided fuzzers generally use the the number of basic blocks or edges explored to measure code coverage. Path-coverage can provide more accurate coverage information than basic block and edge coverage. However, the number of paths grows exponentially as the size of a program increases. It is almost impossible to trace all the paths of a real-world application. In this paper, we propose a fuzzing solution named PathAFL, which assists a fuzzer by path identification. It can effectively identify and utilize the important h-path, which is a new path but whose edges have all been touched previously. First, PathAFL only inserts one assembly instruction to AFL's original code to calculate the path hash, and uses a selective instrumentation strategy to reduce the tracing granularity of an execution path. Second, we design a fast filtering algorithm to choose higher weight paths from a large number of h-paths and add them to the seed queue. Third, both the seed selection algorithm and the power schedule are implemented based on the path weight. Finally we implemented PathAFL based on the popular fuzzer AFL and evaluated it on 10 well-fuzzed benchmark programs. In 24 hours, PathAFL explored 38% more paths and 9.3% more edges than AFL. Compared with CollAFL-x, the number is 25% and 5.9% correspondingly. Moreover, PathAFL found the more bugs on the LAVA-M dataset, even four unlisted bugs. The results show that PathAFL outperforms the previous fuzzers in terms of both code coverage and bug discovery. In well-tested programs, PathAFL found 8 new security bugs with 6 CVEs assigned. © 2020 ACM.

关键词： Program debugging

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A Performance Comparison Study of Parallel Clustering Algorithms in Cluster Environments 2

A Performance Comparison Study of Parallel Clustering Algori...

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2017 IEEE 2nd International Conference on Big data Analysis（ICBDA 2017）

作者： Mo Hai School of Information Central University of Finance and Economics Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China

ISBN: (纸本)9781509036202

We compare the performance of three parallel clustering algorithms:Canopy,K-means and fuzzy K-means in real cluster *** constructing cluster platform of different scale,we compare these algorithms from three metrics:run time,speedup and *** results show that:(1) if both the data set and the number of nodes in the cluster are the same,both the runtime and the sizeup of Canopy is the smallest,and the speedup of Canopy is the largest among these three algorithms;(2) when the number of nodes is larger than 2,for each algorithm,the difference between the sizeup on different data set becomes more and more smaller as the number of nodes increases;at the same time,when the number of nodes is larger than 2 and the data set is the same,the sizeup of Canopy has the maximum decrease with the increase of the number of nodes;(3) when the number of nodes keeps the same,the difference between the sizeup of these three algorithms becomes more and more apparent as the size of the data set increases.

关键词： Canopy K-means Fuzzy K-means Cluster platform Run time Speedup Sizeup

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Improved Global and Local Graph Neural network for Session-based Recommendation 25

Improved Global and Local Graph Neural Network for Session-b...

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25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022

作者： Wang, Yifan Yu, Qing Wang, Zuohua Tianjin University of Technology Tianjin Key Laboratory of Intelligence Computing and Network Security Tianjin China China Everbright Bank Co. Ltd Beijing China

ISBN: (纸本)9781665405270

The session-based recommendation(SBR) aims to predict user actions based on anonymous sessions. SBR focuses on recent sessions to make more real-time and reliable recommendations and does not need to extract user IDs, thereby alleviating privacy issues. Recent research mainly models user preferences based on the target session while ignoring other sessions, which may contain items transitions related to and unrelated to the target session. This paper proposes a novel method, namely Improved Global and Local Graph Neural network (IGL-GNN), to models item transitions within not only the target session but also the other sessions. Specifically, we learn the session-level item representation from the local graph, learns the global-level item representation from the global graph. We propose a new method to effectively aggregate global and local representations, which not only retains more useful information but also removes useless information. In addition, we innovatively introduced Transformer, incorporated it into the model as a general deformation function, enhanced the ability to obtain complex transformations, and solved the limitations of the model in learning complex representations. We have done a lot of experiments on three benchmark datasets, and the results show that the performance of IGL-GNN is better than the most advanced methods. © 2022 IEEE.

关键词： Graph neural networks

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Chosen-Instruction Attack Against Commercial Code Virtualization Obfuscators 29

Chosen-Instruction Attack Against Commercial Code Virtualiza...

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29th Annual network and Distributed System security Symposium, NDSS 2022

作者： Li, Shijia Jia, Chunfu Qiu, Pengda Chen, Qiyuan Ming, Jiang Gao, Debin Tianjin Key Laboratory of Network and Data Security Technology College of Computer Science Nankai University China The University of Texas Arlington United States Singapore Management University Singapore

ISBN: (纸本)1891562746

Code virtualization is a well-known sophisticated obfuscation technique that uses custom virtual machines (VM) to emulate the semantics of original native instructions. Commercial VM-based obfuscators (e.g., Themida and VMProtect) are often abused by malware developers to conceal malicious behaviors. Since the internal mechanism of commercial obfuscators is a black box, it is a daunting challenge for the analyst to understand the behavior of virtualized programs. To figure out the code virtualization mechanism and design deobfuscation techniques, the analyst has to perform reverse-engineering on large-scale highly obfuscated programs. This knowledge learning process suffers from painful cost and imprecision. In this project, we study how to automatically extract knowledge from the commercial VM-based obfuscator via a novel chosen-instruction attack (CIA) technique. Our idea is inspired by chosen-plaintext attack, which is a cryptanalysis attack model to gain information that reduces the security of the encryption scheme. Given a commercial VM-based obfuscator, we carefully construct input programs, proactively interact with the obfuscator, and extract knowledge from virtualized output programs. We propose using the anchor instruction and the guided simplification technique to efficiently locate and extract knowledge-related instructions from output programs, respectively. Our experimental results demonstrate that the modern commercial VM-based obfuscators are under the threat of CIA. We have discovered 760 anchor instructions and extracted 1,915 verified instruction mapping rules from the four most widely used commercial obfuscators. The extracted knowledge enables security analysts to understand virtualized malware and improve deobfuscation techniques. Besides, we also contributed the first fine-grained benchmark suite for systematically evaluating the deobfuscation techniques. The evaluation result shows that three state-of-the-art deobfuscation techniques are ins

关键词： Virtual machine

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Novel way to research nonlinear feedback shift register

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Science China(Information Sciences) 2014年第9期57卷 161-174页

作者： ZHAO DaWei PENG HaiPeng LI LiXiang HUI SiLi YANG YiXian Information Security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and Telecommunications Zhejiang Provincial Key Lab of Data Storage and Transmission Technology Hangzhou Dianzi University National Engineering Laboratory for Disaster Backup and Recovery Beijing University of Posts and Telecommunications Shandong Provincial Key Laboratory of Computer Network Shandong Computer Science Center

In this paper,we regard the nonlinear feedback shift register(NLFSR)as a special Boolean network,and use semi-tensor product of matrices and matrix expression of logic to convert the dynamic equations of NLFSR into an equivalent algebraic *** on them,we propose some novel and generalized techniques to study ***,a general method is presented to solve an open problem of how to obtain the properties(the number of fixed points and the cycles with different lengths)of the state sequences produced by a given NLFSR,i.e.,the analysis of a given *** then show how to construct all 22n-(l-n)/22n-lshortest n-stage feedback shift registers(nFSR)and at least 22n-(l-n)-1/22n-l-1shortest n-stage nonlinear feedback shift registers(nNLFSR)which can output a given nonperiodic/periodic sequence with length ***,we propose two novel cycles joining algorithms for the construction of full-length ***,two algorithms are presented to construct 22n-2-1different full-length nNLFSRs,respectively.

关键词： nonlinear feedback shift register semi-tensor product Boolean network full-length nNLFSR binary sequence

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SSpose: Self-Supervised Spatial-Aware Model for Human Pose Estimation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5403-5417页

作者： Yu, Linfang Qin, Zhen Xu, Liqun Qin, Zhiguang Choo, Kim-Kwang Raymond University of Electronic Science and Technology of China Network and Data Security Key Laboratory of Sichuan Province Chengdu610054 China Industrial Research Institute Chengdu610213 China University of Electronic Science and Technology of China Network and Data Security Key Laboratory of Sichuan Province School of Information and Software Engineering Chengdu610054 China Industrial Research Institute Chengdu610213 China University of Texas at San Antonio Department of Information Systems and Cyber Security San AntonioTX78249 United States

Human pose estimation (HPE) relies on the anatomical relationships among different body parts to locate keypoints. Despite the significant progress achieved by convolutional neural networks (CNN)-based models in HPE, they typically fail to explicitly learn the global dependencies among various body parts. To overcome this limitation, we propose a spatial-aware HPE model called SSpose that explicitly captures the spatial dependencies between specific key points and different locations in an image. The proposed SSpose model adopts a hybrid CNN-Transformer encoder to simultaneously capture local features and global dependencies. To better preserve image details, a multiscale fusion module is introduced to integrate coarse- and fine-grained image information. By establishing a connection with the activation maximization (AM) principle, the final attention layer of the Transformer aggregates contributions (i.e., attention scores) from all image positions and forms the maximum position in the heatmap, thereby achieving keypoint localization in the head structure. Additionally, to address the issue of visible information leakage in convolutional reconstruction, we have devised a self-supervised training framework for the SSpose model. This framework incorporates mask autoencoder (MAE) technology into SSpose models by utilizing masked convolution and hierarchical masking strategy, thereby facilitating efficient self-supervised learning. Extensive experiments demonstrate that SSpose performs exceptionally well in the pose estimation task. On the COCO val set, it achieves an AP and AR of 77.3% and 82.1%, respectively, while on the COCO test-dev set, the AP and AR are 76.4% and 81.5%. Moreover, the model exhibits strong generalization capabilities on MPII. © 2024 IEEE.

关键词： Supervised learning

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FortisAVQA and MAVEN: a Benchmark dataset and Debiasing Framework for Robust Multimodal Reasoning

arXiv

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arXiv 2025年

作者： Ma, Jie Gao, Zhitao Chai, Qi Liu, Jun Wang, Pinghui Tao, Jing Su, Zhou Ministry of Education of Key Laboratory for Intelligent Networks and Network Security School of Cyber Science and Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China Shannxi Provincial Key Laboratory of Big Data Knowledge Engineering School of Computer Science and Technology Xi’an Jiaotong University Shaanxi Xi’an710049 China Guangdong Guangzhou510000 China

Audio-Visual Question Answering (AVQA) is a challenging multimodal reasoning task requiring intelligent systems to answer natural language queries based on paired audio-video inputs accurately. However, existing AVQA approaches often suffer from overfitting to dataset biases, leading to poor robustness. Moreover, current datasets may not effectively diagnose these methods. To address these challenges, we first introduce a novel dataset, FortisAVQA, constructed in two stages: (1) rephrasing questions in the test split of the public MUSIC-AVQA dataset and (2) introducing distribution shifts across questions. The first stage expands the test space with greater diversity, while the second enables a refined robustness evaluation across rare, frequent, and overall question distributions. Second, we introduce a robust Multimodal Audio-Visual Epistemic network (MAVEN) that leverages a multifaceted cycle collaborative debiasing strategy to mitigate bias learning. Experimental results demonstrate that our architecture achieves state-of-the-art performance on FortisAVQA, with a notable improvement of 7.81%. Extensive ablation studies on both datasets validate the effectiveness of our debiasing components. Additionally, our evaluation reveals the limited robustness of existing multimodal QA methods. We also verify the plug-and-play capability of our strategy by integrating it with various baseline models across both datasets. Our dataset and code are available at https://***/reml-group/fortisavqa. Copyright © 2025, The Authors. All rights reserved.

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Design and implementation of content confidentiality check system 3

Design and implementation of content confidentiality check s...

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3rd International Conference on Electronic Information Engineering, Big data, and Computer technology, EIBDCT 2024

作者： Song, Yanyan Chen, Menghong Pi, Chunying Nie, Peng College of Computer Science Nankai University Tianjin300350 China College of Cyber Science Nankai University Tianjin300350 China College of Cyber Science Tianjin Key Laboratory of Network and Data Security Technology Nankai University Tianjin300350 China

ISBN: (纸本)9781510680449

Nowadays, companies use databases for information storage and it is inevitable that there will be confidential information which can cause severe crises and public relations problems if leaked. In order to solve this problem, we designed and implemented a content confidentiality check system for database. In this paper, the first section introduces the module design of the system. The second section introduces the key technology implementation of the system, which includes how to detect sensitive words and user password strength. The third section shows the running interface and detection results of the system. In short, this system helps users to realize a more convenient self inspection of the confidential content stored in their database, aiming to provide a strong guarantee for data storage security. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： database systems

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