检索结果-内蒙古大学图书馆

A Novel Scoring Algorithm Against HID Attacks Based on Static Text Feature Matching 1

6th International Conference on Science of cyber security, SciSec 2024

作者： Li, Haiyang Lv, Zhiqiang Zhang, Yixin Xue, Yanan Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China North Automatic Control Technology Institute Taiyuan China

ISBN: (数字)9789819624171

ISBN: (纸本)9789819624164

In recent years, the proliferation of HID attacks has raised significant security concerns. Previous research has primarily focused on detecting these attacks by analyzing behavior features extracted from keystroke timestamps. However, the sophisticated HID attack could highly imitate user behavior features with the rising trend of countermeasures to overcome the known flaws of existing studies. In this paper, we propose a novel scoring algorithm that relies exclusively on keystroke text analysis. It depends on a HID keystroke text feature space, within which each feature matching result of a text segment is scored and their sum is calculated. Once the total score surpasses a predefined threshold, the text segment will be flagged as indicative of an unsafe HID interaction. In confrontational testing, our algorithm demonstrates a precision rate exceeding 95% in detecting HID attacks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Attack detection HID attack Keystroke text feature

来源：评论

学校读者我要写书评

暂无评论

CACluster: A Clustering Approach for IoT Attack Activities Based on Contextual Analysis 29

CACluster: A Clustering Approach for IoT Attack Activities B...

引用

29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Yang, Huiran Zhang, Yan Dai, Yueyue Sun, Jiyan Cui, Huajun Ma, Can Wang, Weiping Chinese Academy of Sciences Institute of Information Engineering Beijing China University of Chinese Academy of Sciences School of Cyber Security Beijing China Huazhong University of Science and Technology School of Cyber Science and Engineering Wuhan China

ISBN: (纸本)9798350330717

Attacks against IoT have shown a rapid increase in both quantity and complexity. Analysts must handle massive alerts and determine the type of attack manually. In addition, the same attack activity may present polymorphism alert sequences due to overlapping attacks, adaptive attack strategy, error alerts, etc, which poses a severe challenge for human analysis. This manual-dependent and scenario-by-scenario security model is seriously overwhelming security analysts. This paper proposes a contextual-analysis-based clustering approach, CACluster, to aggregate similar attack activities end-to-end. It embeds alert context into vector space and uses an unsupervised clustering method to find similar attack activities based on domain matching and vector distance. Experimental results demonstrate that the CACluster could accurately aggregate similar attack activities, with 0.888 purity, reducing the number of attack activities by 84.8%. It will significantly cut down analysts' workload. © 2023 IEEE.

关键词： Attack activity Cluser Contextual Embedding

来源：评论

学校读者我要写书评

暂无评论

Query in Your Tongue: Reinforce Large Language Models with Retrievers for Cross-lingual Search Generative Experience 24

Query in Your Tongue: Reinforce Large Language Models with R...

引用

33rd ACM Web Conference, WWW 2024

作者： Guo, Ping Hu, Yue Cao, Yanan Ren, Yubing Li, Yunpeng Huang, Heyan Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences Haidian Beijing China Beijing Institute of Technology Haidian Beijing China

ISBN: (纸本)9798400701719

In the contemporary digital landscape, search engines play an invaluable role in information access, yet they often face challenges in Cross-Lingual Information Retrieval (CLIR). Though attempts are made to improve CLIR, current methods still leave users grappling with issues such as misplaced named entities and lost cultural context when querying in non-native languages. While some advances have been made using Neural Machine Translation models and cross-lingual representation, these are not without limitations. Enter the paradigm shift brought about by Large Language Models (LLMs), which have transformed search engines from simple retrievers to generators of contextually relevant information. This paper introduces the Multilingual Information Model for Intelligent Retrieval (MIMIR). Built on the power of LLMs, MIMIR directly responds in the language of the user's query, reducing the need for post-search translations. Our model's architecture encompasses a dual-module system: a retriever for searching multilingual documents and a responder for crafting answers in the user's desired language. Through a unique unified training framework, with the retriever serving as a reward model supervising the responder, and in turn, the responder producing synthetic data to refine the retriever's proficiency, MIMIR's retriever and responder iteratively enhance each other. Performance evaluations via CLEF and MKQA benchmarks reveal MIMIR's superiority over existing models, effectively addressing traditional CLIR challenges. © 2024 Owner/Author.

关键词： Search engines

来源：评论

学校读者我要写书评

暂无评论

Differential Fault Analysis on 3DES Middle Rounds Based on Error Propagation

引用

Chinese Journal of Electronics 2022年第1期31卷 68-78页

作者： MA Xiangliang ZHANG Lizhen WU Liji LI Xia ZHANG Xiangmin LI Bing LIU Yuling School of Integrated Circuits Tsinghua University Beijing National Research Center for Information Science and Technology National Research Center for Information Technology Security Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences

Since differential fault analysis(DFA)was first implemented on data encryption standard(DES), many scholars have improved this attack and extended the limit of the original last two rounds to the earlier rounds. However, the performance of the novel attacks which target middle rounds is not effective, i.e. the number of correct/incorrect ciphertexts required is very large and the recovered result maybe not correct. We address this problem by presenting new DFA methods that can break 3 DES when injecting faults at round 12 or *** simulating the process of single-bit error propagation,we have built two kinds of error propagation models as well as an intermediate error propagation state *** we simplify the intermediate states into state templates that will be further used to locate the injected fault position, which is the main difficulty of implementing fault injection in the middle rounds. Finally, in terms of the idea of error propagation and probability theory, we can recover the last round key only using 2 sets of correct/incorrect ciphertexts when inducting fault in the13 th round and 4 sets of correct/incorrect ciphertexts when inducting fault in the 12 th round.

关键词： intermediate error propagation state table probability theory data encryption standard single-bit error propagation fault injection 3DES middle rounds injected fault position cryptography error propagation models DFA methods differential fault analysis state templates inducting fault fault diagnosis error statistics

来源：评论

学校读者我要写书评

暂无评论

Unidirectional Encrypted Traffic Classification: A Survey 5

Unidirectional Encrypted Traffic Classification: A Survey

引用

5th Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2024

作者： Yang, Chen Gu, Zheyuan Wei, Yuhao Xiong, Gang Gou, Gaopeng Yao, Shan Yu, Yang Institute of Information Engineering University of Chinese Academy of Sciences Chinese Academy of Sciences School of Cyber Security Beijing China 360 Digital Security Technology Group Co. Ltd Beijing China

ISBN: (纸本)9798350374407

Techniques for classifying encrypted traffic typically rely on learning the interaction patterns between communicating parties to determine the traffic category. However, with the widespread application of asymmetric routing mechanisms and link load balancing, a large volume of network equipment cannot observe the complete bidirectional traffic, posing challenges to the deployment of existing methods. In order to solve this problem, research into unidirectional encrypted traffic classification methods has gradually emerged. In this paper, we provide a comprehensive survey of existing unidirectional encrypted traffic classification methods and showcase the latest research progress in this field. Based on how to resolve the contradiction between unidirectional traffic data and model reliance on bidirectional interaction features, we categorize existing methods into three main types: 1) unidirectional feature separation-based methods, 2) unidirectional feature mining-based methods, and 3) pairwise feature prediction-based methods. This paper details the characteristics of each method and discusses their advantages and disadvantages. We hope our work will draw researchers' attention to the real-world network environment, thereby better promoting the development of the encrypted traffic classification field. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Low Latency Implementations of CRYSTALS-Dilithium for Cloud Applications 25

Low Latency Implementations of CRYSTALS-Dilithium for Cloud ...

引用

25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Chen, Ya-Nan Gaol, Yiwen Liu, Yuejun Zhou, Yongbin School of Cyber Science and Engineering Nanjing University of Science and Technology Nanjing China Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350330014

This paper studies GPU-based implementations of CRYSTALS-Dilithium (Dilithium) algorithm, which is one of four post-quantum algorithms that NIST has standardized. We focus on the scenarios of batch processing and explore low latency implementations by parallelizing the critical components of Dilithium with the consideration of overhead due to inter-thread data sharing. We also investigate the techniques of using GPU memories and warp-level instructions for data sharing in GPU-based implementations of Dilithium. All of the efforts lead to effective low latency implementations that are suited to cloud applications. Finally, we conduct evaluations on two testbeds with NVIDIA GeForce RTX 3060 and RTX A4000, respectively. The experimental results show that our low latency implementations save up to 41 percent (resp. 33 percent) latency at low task loads on the former testbed (resp. the latter testbed) when compared with the baseline implementation. We also provide engineers with a practical strategy to achieve better overall performance for applications that the number of arrived tasks is not predictable. © 2023 IEEE.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

NFVDC: A flexible and efficient NFV platform for dynamic service chaining 22

NFVDC: A flexible and efficient NFV platform for dynamic ser...

引用

22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Lu, Qiuwen Liu, Qingyun Fang, Binxing Chinese Academy of Sciences Institute of Information Engineering Beijing China National Engineering Research Center of Information Security Beijing China University of Chinese Academy of Sciences School of Cyber Security Beijing China Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9798331509712

This paper presents the design and implementation of a novel Network Function Virtualization (NFV) platform, NFVDC, specifically for dynamic service chaining. Unlike traditional service chaining methods, NFVDC supports real-time, reconfigurable service chains that accommodate service functions dynamically joining or leaving the chain. By integrating an advanced traffic steering method, optimized CPU scheduling, and a causal message-passing mechanism, NFVDC addresses challenges in deploying dynamic service chaining, such as traffic steering, resource scheduling, and session state management. Our evaluation demonstrates that NFVDC's forwarding performance nearly doubles compared to existing solutions when extending service chain lengths to six. © 2024 IEEE.

关键词： Message passing

来源：评论

学校读者我要写书评

暂无评论

Multi-omics Sampling-based Graph Transformer for Synthetic Lethality Prediction

Multi-omics Sampling-based Graph Transformer for Synthetic L...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhao, Xusheng Liu, Hao Dai, Qiong Peng, Hao Bai, Xu Peng, Huailiang Chinese Academy of Sciences Institute of Information Engineering Beijing China University of Chinese Academy of Sciences School of Cyber Security Beijing China Beihang University School of Cyber Science and Technology Beijing China

ISBN: (纸本)9798350337488

Synthetic lethality (SL) prediction is used to identify if the co-mutation of two genes results in cell death. The prevalent strategy is to abstract SL prediction as an edge classification task on gene nodes within SL data and achieve it through graph neural networks (GNNs). However, GNNs suffer from limitations in their message passing mechanisms, including over-smoothing and over-squashing issues. Moreover, harnessing the information of non-SL gene relationships within large-scale multi-omics data to facilitate SL prediction poses a non-trivial challenge. To tackle these issues, we propose a new multi-omics sampling-based graph transformer for SL prediction (MSGT-SL). Concretely, we introduce a shallow multi-view GNN to acquire local structural patterns from both SL and multi-omics data. Further, we input gene features that encode multi-view information into the standard self-attention to capture long-range dependencies. Notably, starting with batch genes from SL data, we adopt parallel random walk sampling across multiple omics gene graphs encompassing them. Such sampling effectively and modestly incorporates genes from omics in a structure-aware manner before using self-attention. We showcase the effectiveness of MSGT-SL on real-world SL tasks, demonstrating the empirical benefits gained from the graph transformer and multi-omics data. © 2023 IEEE.

关键词： gene sampling graph neural network graph transformer multi-omics synthetic lethality

来源：评论

学校读者我要写书评

暂无评论

Multiclass Brain Tumor Detection using Convolutional Neural Network and Conventional Machine Learning 2

Multiclass Brain Tumor Detection using Convolutional Neural ...

引用

2nd IEEE International Conference on Emerging Research in Computational Science, ICERCS 2024

作者： Vidhya, K. Vamsi Krishna, B. Haritha, M. Rajasekaran, Arun Sekar Roopa Chandrika, R. Velusamy, Jayaraj Karunya Institute of Technology and Sciences Division of Data Science and Cyber Security School of Computer Science and Technology Coimbatore India QIS College of Engineering and Technology Department of AIMLDS Andhra Pradesh India QIS College of Engineering and Technology Department of Mechanical Engineering Andhra Pradesh India SR University Department of Electronics and Communication Engineering Telangana India Karpagam Academy of Higher Education Department of Cyber Security Coimbatore India Nehru Institute of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798331534950

Brain tumor (BT) affect the brain and reduce the lifespan of humans. Therefore, diagnosis and treatment of illnesses in its early stage is required. The objective of this paper is to evaluate the effectiveness of the Convolutional Neural Network (CNN) and Conventional Machine Learning (CML) strategies for identifying multiple classes of brain tumor. In the research, a comparison is made between these two systems for the picture classification of brain tumor. The first step is the collection and preprocessing of images of several classes of brain tumor. The CNN and CML models are trained using the preprocessed dataset. CML makes use of traditional machine learning (ML) algorithms for the purpose of feature extraction and classification, whereas CNN relies on convolutional layers to automatically extract significant features from the images it is fed as input. Precision, accuracy, F1 score, and recall are the criteria that are utilized to evaluate methods. In terms of accuracy and overall performance, CNN is superior to CML. CNN provides a more precise classification of a variety of tumor classifications. Based on these findings, convolutional neural networks (CNN) are likely superior than machine learning for the identification of multiclass brain tumor. CNNs are superior because of their ability to directly understand intricate patterns and characteristics from photographs. This work demonstrates the usefulness of CNNs for multiclass classification in brain tumor detection systems because of their high accuracy and efficiency. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Cloud Based AIVR Training System for Emergency Rescue 12

Cloud Based AIVR Training System for Emergency Rescue

引用

12th International Conference on Advanced Cloud and Big Data, CBD 2024

作者： Dong, Meiya Zhu, Biaokai Zhao, Jumin Song, Jie School of Computer Science Peking University Beijing China Suzhou Industrial Technology Institute Zhejiang University Suzhou China Cyber Security Shanxi Police College China College of Information and Optical Engineering Taiyuan University of Technology Taiyuan China Cyber security Intelligent Policing Key Laboratory of Sichuan Province Luzhou China

ISBN: (纸本)9798331511074

This paper mainly discusses the current situation and existing problems of training exercises in emergency medicial scenarios, as well as the importance and necessity of developing an AI training system for emergency medical scenarios. First, we introduce the current status of emergency medical training and emphasize the potential value of AI technology in this field. Then, the goal of developing an AI training system is defined as improving the efficiency and quality of medical education and training. We summarize the advantages of AI technology in emergency medical exercises and make a review and selection analysis of its related technologies. In the design and implementation stage, we describe in detail the requirement analysis, function design, system architecture, and core module development of the emergency medical AI training system. After system integration and testing, we verified the feasibility and effect of the system. In the process of evaluation and optimization, we evaluated the performance and user experience of the system and put forward optimization strategies and security considerations for the problems. In the application case analysis, we collect user feedback to verify its efficiency and carry out an in-depth analysis of the advantages and disadvantages of the system. Finally, in the conclusion and prospect part, we summarize the research results, point out the existing problems and improvement directions and look forward to the future development trends and challenges of AI training systems for emergency medical scenarios. © 2024 IEEE.

关键词： AI training AIVR system Emergency Rescue

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：