检索结果-内蒙古大学图书馆

IEEE International Conference on Industrial Technology (ICIT)

作者： Fei Yu Cheng Xu Yue Shen Ji-yao An Lin-feng Zhang State Key Laboratory of Information Security Graduate School of Chinese Academy of Sciences Beijing China School of Computer &Information Engineering Hunan Agricultural University Changsha China College of Computer & Communication Hunan University Changsha China

With our human beings entering the information age, information security has already become the new problem as the development of human society. This paper first review the application of system call for intrusion detection, and highlight the problems in few commonly cited papers such as Forrest et al and Sekar et al. Then, propose some improvements for finite-state automation machine algorithm, which are technical sound and original. It uses system calls regarded as input, and creates a finite-state automation machine for the functions in the program. Last, the finite-state automation machine is used to detect the attack. Moreover, It can find the place of the vulnerability which exists in the program. This can help to alter the source program

关键词： Intrusion detection Automation information security Humans Safety National security Protection Agricultural engineering Laboratories Application software

来源：评论

学校读者我要写书评

暂无评论

Type-aware Enhanced Cylinder Embedding for Multi-hop Reasoning over Knowledge Graphs

Type-aware Enhanced Cylinder Embedding for Multi-hop Reasoni...

引用

International Joint Conference on Neural networks (IJCNN)

作者： Yong Shang Xiaoding Zhou Yan Ming Yuyan Zheng Huiting Li Weiyu Zhang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Shcool of Business Shandong Normal University Jinan China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Query embedding (QE) is designed to embed entities and first-order logic (FOL) queries in low-dimensional spaces, it has demonstrated considerable effectiveness in multi-hop reasoning over knowledge graphs. Recently, the practice of embedding entities and queries using geometric shapes has emerged as a promising approach, given the natural ability of these shapes to represent query answer sets and the logical relationships between them. However, existing geometry-based models, such as those employing point and box embeddings, cannot handle logical negation operations. Additionally, these models typically focus only on entities and relations, overlooking the rich semantic information available in knowledge graphs. To address these limitations, we propose the Type-aware Enhanced Cylinder Embedding (TECE) model. This model leverages three-dimensional geometric representations, integrating entity relationship type information. TECE covers a spectrum of essential First-Order Logic (FOL) operations, such as conjunctive, disjunctive, and negative. TECE improves the representation of entities and relationships in queries by incorporating semantic information. Moreover, it strengthens the model’s ability in generalization, along with deductive and inductive reasoning. Our experiment results demonstrate that TECE achieves significantly superior performance compared with existing SOTA methods on standard datasets.

关键词： Solid modeling Shape Semantics Neural networks Knowledge graphs Spread spectrum communication Cognition

来源：评论

学校读者我要写书评

暂无评论

Algebraic geometry codes with complementary duals exceed the asymptotic Gilbert-Varshamov bound

arXiv

引用

arXiv 2017年

作者： Jin, Lingfei Xing, Chaoping School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai200433 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China School of Physical and Mathematical Sciences Nanyang Technological University

It was shown by Massey that linear complementary dual (LCD for short) codes are asymptotically good. In 2004, Sendrier proved that LCD codes meet the asymptotic Gilbert-Varshamov (GV for short) bound. Until now, the GV bound still remains to be the best asymptotical lower bound for LCD codes. In this paper, we show that an algebraic geometry code over a finite field of even characteristic is equivalent to an LCD code and consequently there exists a family of LCD codes that are equivalent to algebraic geometry codes and exceed the asymptotical GV bound. Copyright © 2017, The Authors. All rights reserved.

关键词： Geometry

来源：评论

学校读者我要写书评

暂无评论

Self-Evaluation of Large Language Model based on Glass-box Features

arXiv

引用

arXiv 2024年

作者： Huang, Hui Qu, Yingqi Liu, Jing Yang, Muyun Xu, Bing Zhao, Tiejun Lu, Wenpeng Faculty of Computing Harbin Institute of Technology Harbin China Baidu Inc. Beijing China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology Jinan China

The proliferation of open-source Large Language Models (LLMs) underscores the pressing need for evaluation methods. Existing works primarily rely on external evaluators, focusing on training and prompting strategies. However, a crucial aspect – model-aware glass-box features – is overlooked. In this study, we explore the utility of glass-box features under the scenario of self-evaluation, namely applying an LLM to evaluate its own output. We investigate various glass-box feature groups and discovered that the softmax distribution serves as a reliable quality indicator for self-evaluation. Experimental results on public benchmarks validate the feasibility of self-evaluation of LLMs using glass-box features1 Copyright © 2024, The Authors. All rights reserved.

关键词： Open systems

来源：评论

学校读者我要写书评

暂无评论

Scalable and Extensible Static Memory Safety Analysis with Summary over Access Path

Scalable and Extensible Static Memory Safety Analysis with S...

引用

Asia-Pacific Conference on Software Engineering

作者： Guang Chen Min Zhou Jiaguang Sun Xiaoyu Song Key Laboratory for Information System Security Beijing National Research Center for Information Science and Technology Beijing China Electrical and Computer Engineering Portland State University Portland U.S.

ISBN: (纸本)9781728119717;9781728119700

Static analysis is an effective way of checking memory safety issues in program. Usually, multiple analysis algorithms usually run together to achieve a precise analysis result. In this paper, a novel analysis frame work over access path is presented for incorporating analysis algorithms. A pointer analysis based on access path works as a base layer, alias and pointer information are automatically handled. An summary based checking algorithm is designed for checking real world project. Moreover, the framework is fully extensible and various analysis can be added as plugins. Experimental results show that our method has good precision on Juliet Test Suite and scales to large software.

关键词： Safety Static analysis Indexes Arrays security Kernel

来源：评论

学校读者我要写书评

暂无评论

A Median Filtering Forensics CNN Approach Based on Local Binary Pattern

A Median Filtering Forensics CNN Approach Based on Local Bin...

引用

作者： Tao Zhu Haiyan Gu Zenan Chen Department of Computer Information and Cyber Security Jiangsu Police Institute Jiangsu Province Electronic Data Forensics and Analysis Engineering Research Center Key Laboratory of Digital Forensics of Jiangsu Provincial Public Security Department

Median filtering forensics has gradually become a research hotspot because of the wide application of the traditional median filtering(MF) in image tampering and anti-forensics. The difficulty of traditional median filtering based on machine learning forensics is feature extraction which is a manual selection process, and the Convolutional Neural network(CNN) cannot also well perceive the traces left by median filtering straightly. By taking the Local Binary Pattern(LBP) data of an image as a presentation of the streaking artifact that is a very strong indication for median filtering, a median filtering forensics CNN approach with LBP is proposed, which can automatically learn and get median filtering features from image. Different from traditional CNN, an LBP perception layer is added before the following deep learning layers. Then, five convolution layers constitute the feature extraction group. Finally, the classifier group is composed of three full connected layers to decide whether the image is median filtered or not. The proposed approach is tested on several experiments and the experimental results demonstrate its effectiveness.

关键词： Median filtering Image forensics Convolutional Neural network Local Binary Pattern

来源：评论

学校读者我要写书评

暂无评论

Multi-scale Motion Feature Integration for Action Recognition

Multi-scale Motion Feature Integration for Action Recognitio...

引用

International Conference on computer and Communications (ICCC)

作者： Jinming Lai Huicheng Zheng Jisheng Dang School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China Guangdong Province Key Laboratory of Information Security Technology China

Analyzing video data with intricate temporal structures and extracting comprehensive motion information remains a significant challenge. In this work, we introduce the multi-scale motion feature integration (MMFI) network, which leverages two key modules for motion analysis: the progressive local context aggregation (PLCA) module and the multi-scale motion excitation (MSME) module. The PLCA module captures frame-level motion details by incrementally processing frame-wise differences near the input frame in the early stages of the network. The MSME module provides motion-attentive channel weights in deeper layers with higher dimensions, incorporating short- and long-range segment-level motion information. These modules synergistically capture motion details across various scales. Our approach is evaluated on the large-scale video dataset Something-Something V1, yielding state-of-the-art performance with minimal computational overhead.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Face hallucination by deep traversal network

Face hallucination by deep traversal network

引用

International Conference on Pattern Recognition

作者： Zhanxiang Feng Jianhuang Lai Xiaohua Xie Dakun Yang Ling Mei School of Electronics and Information Technology Sun Yat-sen University China Guandong Key Laboratory of Information Security Technology School of Data and Computer Science Sun Yat-Sen University China

ISBN: (纸本)9781509048489

In this paper, we propose a novel patch-based face hallucination method that consists of two patch-based sparse autoencoder (SAE) networks and a deep fully connected network (namely traversal network). The SAE networks are used to capture the intrinsic features of low-resolution (LR) images and high-resolution (HR) images in the hidden layers, while the traversal network is used to map features from the LR hidden layer to the HR hidden layer. In the training stage, these three networks are jointly optimized. Compared with previous network-based methods that learn an end-to-end mapping from LR images to HR images, our method learns the mapping between hidden layers, which can better alleviate the over-fitting problem. Experimental results demonstrate that our method is efficient and robust for hallucinating face images from both lab environment and the wild. The proposal achieves state-of-the-art performance when conducting face hallucination in CAS-PEAL-R1 database, CMU-PIE database and Casia database.

关键词： Face Image reconstruction Training Databases Feature extraction Image coding Decoding

来源：评论

学校读者我要写书评

暂无评论

Anomaly-Free Prior Guided Knowledge Distillation for Industrial Anomaly Detection

Anomaly-Free Prior Guided Knowledge Distillation for Industr...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Gang Li Tianjiao Chen Min Li Delong Han MingLe Zhou Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Faculty of Data Science City University of Macau Macau China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In industrial manufacturing, visual anomaly detection is critical for maintaining product quality by detecting and preventing production anomalies. Anomaly detection methods based on knowledge distillation demonstrate promising performance in addressing the unpredictability and diversity of anomalies. However, they suffer from a lack of effective guidance from anomaly-free priors when handling anomalous features and underutilize multi-scale features during the segmentation scoring stage, yielding suboptimal detection results. To alleviate these issues, we propose an Anomaly-free Prior Guided knowledge distillation (APG) for industrial anomaly detection. Firstly, it filters the abnormal features by training the de-noising target network with knowledge distillation structure. Concurrently, we propose the Prior Perception Propagation Module (P 3 M), which extracts more efficient anomaly-free features by imposing constraints on anomalous features. Secondly, we propose the Multi-scale Prior Guided Fusion Module (MPGFM) to improve anomaly detection accuracy by utilizing anomaly-free features from the target network as priors to guide the generation and fusion of cross-scale differential features. Finally, the Global Perception Enhancement Module (GPEM) is proposed to construct an anomaly scoring network, leveraging comprehensive scene features to enhance the detection and localization performance of numerous small-target anomalies in industrial manufacturing. Extensive experiments on the MVTecAD and BTAD datasets show that the proposed method demonstrates a consistent and significant outperformance against competing methods.

关键词： Training Location awareness Visualization Noise reduction Production Feature extraction Product design Manufacturing Quality assessment Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

DeepkeyGen: A deep learning-based stream cipher generator for medical image encryption and decryption

arXiv

引用

arXiv 2020年

作者： Ding, Yi Tan, Fuyuan Qin, Zhen Cao, Mingsheng Choo, Kim-Kwang Raymond Qin, Zhiguang Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China ChengduSichuan610054 China Institute of Electronic and Information Engineering of UESTC in Guangdong Guangdong523808 China Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China ChengduSichuan610054 China Department of Information Systems and Cyber Security University of Texas at San Antonio San AntonioTX78249-0631 United States

The need for medical image encryption is increasingly pronounced, for example to safeguard the privacy of the patients’ medical imaging data. In this paper, a novel deep learning-based key generation network (DeepkeyGen) is proposed as a stream cipher generator to generate the private key, which can then be used for encrypting and decrypting of medical images. In DeepkeyGen, the generative adversarial network (GAN) is adopted as the learning network to generate the private key. Furthermore, the transformation domain (that represents the "style" of the private key to be generated) is designed to guide the learning network to realize the private key generation process. The goal of DeepkeyGen is to learn the mapping relationship of how to transfer the initial image to the private key. We evaluate DeepkeyGen using three datasets, namely: the Montgomery County chest X-ray dataset, the Ultrasonic Brachial Plexus dataset, and the BraTS18 dataset. The evaluation findings and security analysis show that the proposed key generation network can achieve a high-level security in generating the private key. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：