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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Zhou, Ziqi Song, Yufei Li, Minghui Hu, Shengshan Wang, Xianlong Zhang, Leo Yu Yao, Dezhong Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Computer Science and Technology Huazhong University of Science and Technology China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia

Segment Anything Model (SAM) has recently gained much attention for its outstanding generalization to unseen data and tasks. Despite its promising prospect, the vulnerabilities of SAM, especially to universal adversarial perturbation (UAP) have not been thoroughly investigated yet. In this paper, we propose DarkSAM, the first prompt-free universal attack framework against SAM, including a semantic decoupling-based spatial attack and a texture distortion-based frequency attack. We first divide the output of SAM into foreground and background. Then, we design a shadow target strategy to obtain the semantic blueprint of the image as the attack target. DarkSAM is dedicated to fooling SAM by extracting and destroying crucial object features from images in both spatial and frequency domains. In the spatial domain, we disrupt the semantics of both the foreground and background in the image to confuse SAM. In the frequency domain, we further enhance the attack effectiveness by distorting the high-frequency components (i.e., texture information) of the image. Consequently, with a single UAP, DarkSAM renders SAM incapable of segmenting objects across diverse images with varying prompts. Experimental results on four datasets for SAM and its two variant models demonstrate the powerful attack capability and transferability of DarkSAM. Our codes are available at: https://***/CGCL-codes/DarkSAM. © 2024 Neural information processing systems foundation. All rights reserved.

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Automatic data distribution in large-scale OLTP applications

International Journal of Database Theory and Application

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International Journal of database Theory and Application 2014年第4期7卷 37-46页

作者： Wang, Xiaoyan Fan, Xu Chen, Jinchuan Du, Xiaoyong Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Information and Electrical Engineering Ludong University Yantai 264025 China School of Information Renmin University of China Beijing 100872 China

With the dramatic increase of data volume, automatic data distribution has been one of the key techniques and intractable problem for distributed systems. This work summarizes the problem of data distribution and abstracts it as a general triangle model called DaWN. Based on data and workload analysis, it presents a novel strategy called ADDS for automatic data distribution in OLTP applications. According to the results of a series of experiments over TPC-C datasets and transactions, the proposed approach shows effective improvements.© 2014 SERSC.

关键词： data handling

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A property of reductions in Fuzzy Variable Precision Rough Set model

A property of reductions in Fuzzy Variable Precision Rough S...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Eric C. C. Tsang Su-Yun Zhao Cai-Li Zhou Faculty of Information Technology Macau University of Science and Technology Taipa Macao China Key Laboratory of Data Engineering and Knowledge Engineering MOE Renmin University of China China School of Mathematics and Computer Sciences Hebei University China

In this paper, we use strict mathematics reasoning to discover the relation between the threshold and reduction in Fuzzy Variable Precision Rough Sets (FVPRS), i.e., the reductions act as a nested structure with the monotonously increasing threshold. By using the nested structure of reductions, we could design algorithms to quickly find different reductions when a reduction is required. Here `different' means the reductions obtained using different thresholds.

关键词： Rough sets Approximation methods Fuzzy sets Educational institutions Computational modeling Machine learning Cybernetics

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An Efficient Customized Blockchain System for Inter-Organizational Processes

An Efficient Customized Blockchain System for Inter-Organiza...

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IEEE International Conference on Web services (ICWS)

作者： Puwei Wang Zhouxing Sun Rui Li Jinchuan Chen Ping Gong Xiaoyong Du School of Information Renmin University of China Key Laboratory of Data Engineering and Knowledge Engineering (Ministry of Education) Renmin University of China School of Mathematics Renmin University of China College of Computer and Cyber Security Fujian Normal University

Blockchain technologies pave a promising way for implementing the inter-organizational processes. Most of the current research works translate the execution logic in the process models into the smart contracts, which can run independently on the blockchain without the outside process engine. However, the works usually suffer from the execution and storage costs, since the translation needs to be done when the processes are deployed. In this paper, we customize a process engine for executing the inter-organizational business processes via a blockchain-style procedure, i.e., checking the validity of transactions, adding the valid transactions into the blockchain through the consensus mechanism, and then updating the process states according to the committed transactions. And then, we build a blockchain system by embedding the customized process engine into the blockchain nodes. Moreover, in order to realize the interactions between the inter-organizational processes running on blockchain and the services outside blockchain, we propose a blockchain-based approach for service registration, binding and invocation, and design a lease-based concurrency control protocol to logically isolate transactions from each other when invoking the services simultaneously. Finally, we implement a prototype system based on a permissioned blockchain platform Hyperledger Fabric and a process engine Activiti. The experimental results show the proposed blockchain system can execute the inter-organizational processes correctly and efficiently.

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DGA-Net: Dynamic gaussian attention network for sentence semantic matching

arXiv

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arXiv 2021年

作者： Zhang, Kun Lv, Guangyi Wang, Meng Chen, Enhong Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology China School of Computer Science and Information Engineering Hefei University of Technology China School of Computer Science and Technology University of Science and Technology of China China

Sentence semantic matching requires an agent to determine the semantic relation between two sentences, where much recent progress has been made by advancement of representation learning techniques and inspiration of human behaviors. Among all these methods, attention mechanism plays an essential role by selecting important parts effectively. However, current attention methods either focus on all the important parts in a static way or only select one important part at one attention step dynamically, which leaves a large space for further improvement. To this end, in this paper, we design a novel Dynamic Gaussian Attention Network (DGA-Net) to combine the advantages of current static and dynamic attention methods. More specifically, we first leverage pre-trained language model to encode the input sentences and construct semantic representations from a global perspective. Then, we develop a Dynamic Gaussian Attention (DGA) to dynamically capture the important parts and corresponding local contexts from a detailed perspective. Finally, we combine the global information and detailed local information together to decide the semantic relation of sentences comprehensively and precisely. Extensive experiments on two popular sentence semantic matching tasks demonstrate that our proposed DGA-Net is effective in improving the ability of attention mechanism. © 2021, CC BY.

关键词： Gaussian distribution

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Automatic detection of integer sign vulnerabilities

Automatic detection of integer sign vulnerabilities

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International Conference on Information and Automation (ICIA)

作者： Bin Liang Hui Liu Wenchang Shi Zhiyong Shan Renmin University of China Beijing CN College of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China) MOE Beijing 100872 China

The integer sign vulnerability is a comparatively new and subtle type of vulnerabilities, they can compromise system security. Especially, if a sign vulnerability occurs in operating system kernel, it may result in very serious invalid read/write operations to kernel memory area. Unfortunately, little attention has been paid to static detecting them automatically. This paper presents a novel approach to detecting sign vulnerabilities in Linux kernel using type qualifier technique. We introduce three pairs of type qualifier and corresponding lattices to identify some key kernel data and relationships between them. Based on an extended type inference tool, we are able to effectively detect known and unknown sign vulnerabilities from elaborately preprocessed Linux kernel files. Our experiences demonstrate that type qualifier technique can be applied to detect sign vulnerabilities effectively.

关键词： Kernel Linux Lattices Indexes Arrays Security Buffer overflow

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Vulnerabilities Static Detection for Web Applications with False Positive Suppression

Vulnerabilities Static Detection for Web Applications with F...

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2010 IEEE International Conference on Information Theory and Information Security(2010 IEEE 国际信息论与信息安全会议)

作者： Bin Liang Qianqian Wang Jianjun Huang Jiagui Zhong Jingjing Cai Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China) MOE Schoo School of Information Renmin University of China Beijing 100872 China Beijing Venustech Cybervision Co. Ltd Beijing 100094 China

Web applications become more and more important, and the corresponding security problems have been concerned about. This paper presents TASA, an ASP static analyzer, which employs a path-sensitive, inter-procedural and contextsensitive data flow analysis, mainly concerning the taint propagation and sanitization. This paper also discusses some techniques used in TASA, such as sanitization routines modeling, ASP specific features, alias analysis and path-related routines modeling, to prune false positives. Experiments on four open source applications show that TASA has a rate of false positive of 4.98% and it can avoid certain false warnings owing to the proposed approaches.

关键词： Security Detectors Computer bugs Portals Analytical models Browsers Merging

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Hypernode: Entity Fusion for data Traceability and Link Prediction

Hypernode: Entity Fusion for Data Traceability and Link Pred...

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IEEE International Conference on data Mining (ICDM)

作者： Bingbing Dong Zan Zhang Jiao Li Yi Zhu Chenyang Bu Xindong Wu Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China) Hefei University of Technology China School of Computer Science and Information Engineering Hefei University of Technology Hefei China Institute of Big Knowledge Science Hefei University of Technology Hefei China School of Information Engineering Yangzhou University Yangzhou China

In the era of big data, fragmented knowledge, multisource heterogeneity, and different representation forms of the same entities in various data sources have posed considerable challenges to entity fusion. How to effectively integrate multisource knowledge for the same entities has provoked vast amounts of attention and research from multiple disciplines. Most existing methods for entity fusion can be categorized into two classes: one is to establish an association between the same entities, and the other is to delete duplicate entities after knowledge fusion and create a new fusion entity. However, in these two classes of methods, the former does not achieve true knowledge fusion and semantic interoperability, while the latter may cause irreversible loss of original information. In this paper, we propose a novel entity fusion scheme: Hypernode. Hypernode fuses the same entity in different data sources into a new entity while retaining the original data. We verify the effectiveness of Hypernode on multiple models of link prediction experiments. Several practical application cases illustrate the applicability of Hypernode in data traceability, open domain knowledge fusion, and multi-modal knowledge graph fusion.

关键词： Fuses Soft sensors Semantics Predictive models Big data Cognition data mining

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Multi-Agent Genetic Algorithm for Sparse Optical Phased Array Optimization

Multi-Agent Genetic Algorithm for Sparse Optical Phased Arra...

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Asia Communications and Photonics Conference

作者： Chuxin Liu Weihan Xu Linjie Zhou Liangjun Lu Jianping Chen Shanghai Institute for Advanced Communication and Data Science Shanghai Key Lab of Navigation and Location Services State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering SJTU Shanghai China

We propose a multi-agent Genetic algorithm to suppress the peak sidelobe ratio (PSLR) in the OPA far-field diffraction pattern. The optimized 128-channel sparse array achieves beam-steering range of ±60° wit... 详细信息

ISBN: (纸本)9781943580705

关键词： Far field diffraction Free space optics Genetic algorithms Optical coherence tomography Phased arrays Ptychography

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SAMPLING LOVÁSZ LOCAL LEMMA FOR GENERAL CONSTRAINT SATISFACTION SOLUTIONS IN NEAR-LINEAR TIME

arXiv

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arXiv 2022年

作者： He, Kun Wang, Chunyang Yin, Yitong The Key Lab of Data Engineering and Knowledge Engineering MOE Renmin University of China No. 59 Zhongguancun Street Haidian District Beijing China State Key Laboratory for Novel Software Technology Nanjing University 163 Xianlin Avenue Jiangsu Province Nanjing China

We give a fast algorithm for sampling uniform solutions of general constraint satisfaction problems (CSPs) in a local lemma regime. Suppose that the CSP has n variables with domain size at most q, each constraint contains at most k variables, shares variables with at most Δ constraints, and is violated with probability at most p by a uniform random assignment. The algorithm returns an almost uniform satisfying assignment in expected poly(q,k, Δ) ·(n) time, as long as a local lemma condition is satisfied: k · p · q2 · Δ5 ≤ C0 for a suitably small absolute constant C0. Previously, under similar local lemma conditions, sampling algorithms with running time polynomial in both nand Δ were only known for the almost atomic case, where each constraint is violated by a small number of forbidden local configurations. The key term Δ5 in our local lemma condition also improves the previously best known Δ7 for general CSPs [JPV21b] and Δ5.714 for atomic CSPs, including the special case of k-CNF [JPV21a, HSW21]. Our sampling approach departs from previous fast algorithms for sampling LLL, which were based on Markov chains. A crucial step of our algorithm is a recursive marginal sampler that is of independent interests. Within a local lemma regime, this marginal sampler can draw a random value for a variable according to its marginal distribution, at a cost independent of the size of the CSP. Copyright © 2022, The Authors. All rights reserved.

关键词： Constraint satisfaction problems

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