Inf. Sci.最新文献_第8页

Adversarial Camouflage for Node Injection Attack on Graphs 图上节点注入攻击的对抗伪装

Inf. Sci. Pub Date : 2022-08-03 DOI: 10.48550/arXiv.2208.01819

Shuchang Tao, Qi Cao, Huawei Shen, Yunfan Wu, Liang Hou, Xueqi Cheng

{"title":"Adversarial Camouflage for Node Injection Attack on Graphs","authors":"Shuchang Tao, Qi Cao, Huawei Shen, Yunfan Wu, Liang Hou, Xueqi Cheng","doi":"10.48550/arXiv.2208.01819","DOIUrl":"https://doi.org/10.48550/arXiv.2208.01819","url":null,"abstract":"Node injection attacks on Graph Neural Networks (GNNs) have received increasing attention recently, due to their ability to degrade GNN performance with high attack success rates. However, our study indicates that these attacks often fail in practical scenarios, since defense/detection methods can easily identify and remove the injected nodes. To address this, we devote to camouflage node injection attack, making injected nodes appear normal and imperceptible to defense/detection methods. Unfortunately, the non-Euclidean structure of graph data and the lack of intuitive prior present great challenges to the formalization, implementation, and evaluation of camouflage. In this paper, we first propose and define camouflage as distribution similarity between ego networks of injected nodes and normal nodes. Then for implementation, we propose an adversarial CAmouflage framework for Node injection Attack, namely CANA, to improve attack performance under defense/detection methods in practical scenarios. A novel camouflage metric is further designed under the guide of distribution similarity. Extensive experiments demonstrate that CANA can significantly improve the attack performance under defense/detection methods with higher camouflage or imperceptibility. This work urges us to raise awareness of the security vulnerabilities of GNNs in practical applications.","PeriodicalId":13641,"journal":{"name":"Inf. Sci.","volume":"182 1","pages":"119611"},"PeriodicalIF":0.0,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77462788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

A new approach to generalized neighborhood system-based rough sets via convex structures and convex matroids 基于凸结构和凸拟阵的广义邻域系统粗糙集的新方法

Inf. Sci. Pub Date : 2022-08-01 DOI: 10.1016/j.ins.2022.08.084

Fangfang Zhao, B. Pang, Jusheng Mi

引用次数: 2

Primitively visually meaningful image encryption: A new paradigm 原始视觉上有意义的图像加密:一种新范式

Inf. Sci. Pub Date : 2022-08-01 DOI: 10.1016/j.ins.2022.08.027

Ruoyu Zhao, Yushu Zhang, Y. Nan, Wenying Wen, Xiu-li Chai, Rushi Lan

引用次数: 13

Optimized adaptive consensus control for multi-agent systems with prescribed performance 具有预定性能的多智能体系统的优化自适应共识控制

Inf. Sci. Pub Date : 2022-08-01 DOI: 10.1016/j.ins.2022.08.012

Lei Yan, Zhi Liu, C. L. Chen, Yun Zhang, Zongze Wu

引用次数: 7

Rethinking Attention Mechanism in Time Series Classification 重新思考时间序列分类中的注意机制

Inf. Sci. Pub Date : 2022-07-14 DOI: 10.48550/arXiv.2207.07564

Bowen Zhao, Huanlai Xing, Xinhan Wang, Fuhong Song, Zhiwen Xiao

{"title":"Rethinking Attention Mechanism in Time Series Classification","authors":"Bowen Zhao, Huanlai Xing, Xinhan Wang, Fuhong Song, Zhiwen Xiao","doi":"10.48550/arXiv.2207.07564","DOIUrl":"https://doi.org/10.48550/arXiv.2207.07564","url":null,"abstract":"Attention-based models have been widely used in many areas, such as computer vision and natural language processing. However, relevant applications in time series classification (TSC) have not been explored deeply yet, causing a significant number of TSC algorithms still suffer from general problems of attention mechanism, like quadratic complexity. In this paper, we promote the efficiency and performance of the attention mechanism by proposing our flexible multi-head linear attention (FMLA), which enhances locality awareness by layer-wise interactions with deformable convolutional blocks and online knowledge distillation. What's more, we propose a simple but effective mask mechanism that helps reduce the noise influence in time series and decrease the redundancy of the proposed FMLA by masking some positions of each given series proportionally. To stabilize this mechanism, samples are forwarded through the model with random mask layers several times and their outputs are aggregated to teach the same model with regular mask layers. We conduct extensive experiments on 85 UCR2018 datasets to compare our algorithm with 11 well-known ones and the results show that our algorithm has comparable performance in terms of top-1 accuracy. We also compare our model with three Transformer-based models with respect to the floating-point operations per second and number of parameters and find that our algorithm achieves significantly better efficiency with lower complexity.","PeriodicalId":13641,"journal":{"name":"Inf. Sci.","volume":"107 1","pages":"97-114"},"PeriodicalIF":0.0,"publicationDate":"2022-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76741435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Approximate synchronization of coupled multi-valued logical networks 耦合多值逻辑网络的近似同步

Inf. Sci. Pub Date : 2022-07-14 DOI: 10.48550/arXiv.2207.06615

Rong Zhao, Jun‐e Feng, Biao Wang

{"title":"Approximate synchronization of coupled multi-valued logical networks","authors":"Rong Zhao, Jun‐e Feng, Biao Wang","doi":"10.48550/arXiv.2207.06615","DOIUrl":"https://doi.org/10.48550/arXiv.2207.06615","url":null,"abstract":"This article deals with the approximate synchronization of two coupled multi-valued logical networks. According to the initial state set from which both systems start, two kinds of approximate synchronization problem, local approximate synchronization and global approximate synchronization, are proposed for the first time. Three new notions: approximate synchronization state set (ASSS), the maximum approximate synchronization basin (MASB) and the shortest approximate synchronization time (SAST) are introduced and analyzed. Based on ASSS, several necessary and sufficient conditions are obtained for approximate synchronization. MASB, the set of all possible initial states, from which the systems are approximately synchronous, is investigated combining with the maximum invariant subset. And the calculation method of the SAST, associated with transient period, is presented. By virtue of MASB, pinning control scheme is investigated to make two coupled systems achieve global approximate synchronization. Furthermore, the related theories are also applied to the complete synchronization problem of $k$-valued ($kgeq2$) logical networks. Finally, four examples are given to illustrate the obtained results.","PeriodicalId":13641,"journal":{"name":"Inf. Sci.","volume":"55 1","pages":"19-41"},"PeriodicalIF":0.0,"publicationDate":"2022-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83517569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An adaptive differential evolution framework based on population feature information 基于种群特征信息的自适应差分进化框架

Inf. Sci. Pub Date : 2022-07-01 DOI: 10.1016/j.ins.2022.07.043

Zijian Cao, Zhenyu Wang, Yanfang Fu, Haowen Jia, Feng Tian

引用次数: 6

UHD Low-light image enhancement via interpretable bilateral learning 通过可解释的双边学习来增强UHD低光图像

Inf. Sci. Pub Date : 2022-07-01 DOI: 10.1016/j.ins.2022.07.051

Qiaowanni Lin, Zhuoran Zheng, Xiuyi Jia

引用次数: 5

A content-oriented no-reference perceptual video quality assessment method for computer graphics animation videos 面向内容的计算机图形动画视频无参考感知视频质量评价方法

Inf. Sci. Pub Date : 2022-07-01 DOI: 10.1016/j.ins.2022.07.053

Weizhi Xian, Mingliang Zhou, Bin Fang, S. Kwong