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Towards Efficient and Privacy-Preserving Anomaly Detection of Blockchain-Based Cryptocurrency Transactions 25th

Towards Efficient and Privacy-Preserving Anomaly Detection ...

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25th International Conference on Information and Communications Security, ICICS 2023

作者： Song, Yuhan Zhu, Yuefei Wei, Fushan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Henan Key Laboratory of Network Cryptography Technology Zhengzhou China

ISBN: (纸本)9789819973552

In recent years, a growing number of breaches targeting cryptocurrency exchanges have damaged the credibility of the entire cryptocurrency ecosystem. To prevent further harm, it’s crucial to detect the anomalous behaviors hidden within cryptocurrency transactions and offer predictive suggestions. However, details of transaction records must be carefully analyzed for effective detection, and this information could be exploited by adversaries to launch attacks such as de-anonymization and model interference. As a result, it is essential to prioritize privacy preservation when designing an anomaly detection system for cryptocurrency transactions. In this paper, we propose a privacy-preserving anomaly detection (PPad) scheme for cryptocurrency transactions based on a decision tree model, which achieves privacy preservation by using additively homomorphic encryption and matrix perturbation techniques. We also design and implement PPad’s underlying protocol in a cloud outsourcing environment. The correctness and privacy properties of PPad have been proven through detailed analysis. Experimental results show that our scheme can offer privacy assurance with desirable detection effectiveness and efficiency, making it suitable for real-world applications. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Decision trees

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Resolving Anonymous Nodes Based on "Watermelon Patterns" Towards Constructing Router-Level Topology in Mesh Network 29th

Resolving Anonymous Nodes Based on "Watermelon Patterns" Tow...

引用

29th International Conference on Computational and Experimental engineering and Sciences, ICCES 2023

作者： Li, Ruixiang Feng, Xinzhu Liu, Chong Yuan, Fuxiang Ding, Shichang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Key Laboratory of Cyberspace Situation Awareness of Henan Province Zhengzhou China Sichuan University Chengdu China

ISBN: (纸本)9783031425141

Router-level topology, portraying the connection relationship between network devices, is important for discovering key devices in network. In actual networks, there are some anonymous routers, which do not respond traceroute due to network congestion, firewall security settings, router response rate limitations, and other factors. As these anonymous routers are difficult to eliminate, it makes the constructed router-level topology huge in size. Currently, the time cost of finding key nodes is high. Resolving anonymous nodes for reducing the topology size is necessary to improve the efficiency in finding key node. Although anonymous route resolving methods have been available, they are difficult to handle two-hop anonymous route structures in mesh topologies. To this end, based on the four structures summarized in Graph Based Induction (GBI) method, we propose a method to resolve anonymous nodes based on "watermelon patterns". Combining with Kapar, an alias IP merging method, to build router-level topologies in mesh networks. We have conducted experiments in 8 cities, such as New York, Tokyo, Seoul and so on. The experimental results show that, our method can handle the local topology containing two-hop anonymous nodes. And using our method to further reduce the size of the router-level topology built using GBI and Kapar, which is conducive to improving the efficiency of discovering key nodes in the topology. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Topology

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Packet Modification and Utilization Technology of SOHO Router 2

Packet Modification and Utilization Technology of SOHO Route...

引用

2nd International Conference on advanced Manufacturing Technology and Manufacturing Systems, ICAMTMS 2023

作者： Gai, Xianzhe Cai, Ruijie Jia, Fan Chen, Hongwei Yang, Pengfei Liu, Shengli State Key Laboratory of Mathematical Engineering and Advanced Computing 62 Science Ave. Zhengzhou450001 China

ISBN: (纸本)9781510667327

As a gateway to handle all intranet terminal traffic, SOHO router plays an important role in the network. In this paper, we introduced the security threats faced by SOHO routers, and on this basis, we propose a packet modification method of " Discard-Resend". The method does not affect the normal operation of the router, nor does it affect the normal communication between the two sides. We have done experiments on this packet modification method in several scenarios from the view of network security personnel and network attackers, and achieved the desired results. The packet modification method of " Discard-Resend" is a basic work in the security research of SOHO router, and it is of great significance. © 2023 SPIE.

关键词： Network security

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A review of auxiliary hardware architectures supporting dynamic taint analysis

A review of auxiliary hardware architectures supporting dyna...

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2022 International Conference on Cloud computing, Internet of Things, and Computer Applications, CICA 2022

作者： Yang, Anfeng Guang, Yan Zhao, Yuntian State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781510656673

Dynamic taint analysis is a widely used information flow analysis method. The software structure supporting dynamic taint analysis needs running program to monitor the spread of taint, which will bring a large running time overhead. The architecture based on hardware implementation can shorten the running time overhead of taint analysis through hardware modification, which has great research significance. Firstly, we introduced the research background and significance of hardware. Then, we describe the problems of providing support structure for dynamic taint analysis based on software and how to solve or alleviate these problems in hardware architecture on the basis of the introduction of the specific classification and structure of hardware architecture. Finally, on the basis of comparing the characteristics of hardware structure from different dimensions, the future research direction of hardware structure is prospected. © 2022 SPIE.

关键词： Memory architecture

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PFCA: An Intelligent Method of Multidimensional User Profile Construction and Application 7

PFCA: An Intelligent Method of Multidimensional User Profile...

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7th International Conference on Big Data Analytics, ICBDA 2022

作者： Xia, Yi Zhou, Gang Luo, Junyong Lan, Mingjing Chen, Xiaohui Wang, Shiyu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665479387

User profile plays an important role in analyzing high influencers in the era of big data. For example, the profile can help the political strategists to scrutinize the performance of a candidate or party and overcome their weakness long before election day. In this work, we propose a novel profile construction and application model (PFCA) that aims to discover the overall character of high influencers, and apply PFCA to Donald Trump, one of the most influential people recently, to identify Trump's comprehensive personalities. We first collect and preprocess profile data from static and dynamic aspects of multi-source data, and then categorize multi-source data topics and emotions. Next, we attempt to construct the profile from four aspects: fundamental characteristic, behavior characteristic, value characteristic and situation characteristic, to explore the correlation among these characteristics. Finally, PFCA is verified by the outcomes of the 2016 and 2020 U.S. presidential elections, and is evaluated by relevant experts, which proves that PFCA is relatively effective and efficient to profile high influencers. Moreover, PFCA can be further applied to related analysis and prediction in the 2024 U.S. presidential election. © 2022 IEEE.

关键词： Sentiment analysis

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A PV-DM-based feature fusion method for binary malware clustering 4

A PV-DM-based feature fusion method for binary malware clust...

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4th International Conference on Communications, Information System and Computer engineering, CISCE 2022

作者： Gui, Hairen Zhang, Chunyan Huang, Yizhao Liu, Fudong State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9781665498487

ISBN: (纸本)9781665498487

Utilizing NLP methods in malware classification or clustering applications is a hotspot in malware analysis. Binary malware embedding has become an important direction and basis for malware analysis. Existing binary malware vectorizing methods cannot extract semantic and functional information simultaneously, which may affect the performance of family clustering. In this paper, a novel feature fusion representation method is proposed based on PV-DM (Paragraph Vector-Distributed Memory) model, and the K-Means algorithm is adopted for family clustering. The method combines the features of program-level API call sequence and function-level instruction sequences by means of PV-DM. The functional and semantic representation capabilities of binary malwares can be improved. Malware public dataset VXHeavon is taken as the dataset. A series of experiments are conducted, using the existing family labels as the clustering accuracy evaluation standard. The results demonstrate that our feature fusion representation method outperforms the baseline method by 4.96% in terms of accuracy. © 2022 IEEE.

关键词： Malware

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A Malware Classification Method based on Attentive Bidirectional Model 7

A Malware Classification Method based on Attentive Bidirecti...

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7th International Conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Gui, Hairen Liu, Fudong Zhang, Chunyan Tang, Ke State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665478571

Deep learning techniques have achieved significant improvements in malware analysis application, such as malware detection, malware classification and vulnerability mining. Convolutional neural network (CNN) is applied to extract local features of samples, while recurrent neural network (RNN) mainly extracts global features from sequence context. However, the pooling layer in CNN is a nonlinear dimensionality reduction operation, which can cause a loss of correlation feature. The raw RNN or LSTM model cannot perform parallel computing when calculating the feature vectors, limiting the effect of model application. Hence, we propose a novel malware classification model named BGSA (Bidirectional GRU with Self- Attention), which applies bi-direction gated recurrent unit (BiGRU) and self-attention mechanism. To demonstrate that the model can improve the feature extraction capability, a series of comparison experiments have been conducted on the VxHeavon dataset. The results show that the classification of BGSA reaches 92.54% in term of precision, which surpass the performance of method based on LSTM+CNN and BiGRU. © 2022 IEEE.

关键词： Long short-term memory

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A Review of Few-Shot Network Traffic Classification Based on Deep Learning

A Review of Few-Shot Network Traffic Classification Based on...

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2023 International Conference on Mechatronics and Intelligent Control, ICMIC 2023

作者： Yang, Kai Wang, Ruo Nan Meng, Qi Meng, Long Qi, Zan Li, Xue Fei, Jin Long State Key Laboratory of Mathematical Engineering And Advanced Computing PLA Strategic Support Force Information Engineering University Zhengzhou China

ISBN: (纸本)9781510668393

At present, deep learning has achieved excellent performance in the field of network traffic classification. However, deep learning relies on massive data-driven classification models. When the data set is small, it is usually hindered. In order to solve this problem, few-shot network traffic classification technology based on deep learning has been gradually studied. In this paper, we conducted a comprehensive survey to fully understand the few-shot traffic classification techniques. We first define the few-shot traffic classification problem. Based on how to solve the contradiction between the few-shot data set and the large number of parameters to be trained in the model, we classify the current few-shot traffic classification method based on deep learning from two perspectives: (1) Data augmentation method, which uses the method of expanding the data set to enhance the supervision experience. In this paper, the methods based on data enhancement are divided into two categories based on GAN and feature transformation.(2) Model-based methods. Model-based methods are divided into three categories: transfer learning, metric learning and meta-learning. And discuss the advantages and disadvantages of each classification method. Finally, the results are summarized and the future development direction of few-shot network traffic classification technology based on deep learning is prospected. © 2023 SPIE.

关键词： Deep learning

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A Tree-based Structure Mutation Method for Network Protocol Fuzzing 6

A Tree-based Structure Mutation Method for Network Protocol ...

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2021 6th International Conference on Information Science, Computer Technology and Transportation, ISCTT 2021

作者： Yang, Rui Jing, Jing Qi, Xuyan Zheng, Hongbing State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9783800757282

It is difficult to fuzz the protocol because the format of network protocol is complex and often involves syntax and semantic constraints. Traditional fuzzing often makes a trade-off between the validity of protocol message and mutation space when applied to network protocol. In this paper, we present a tree-based structure mutation method for network protocols. Firstly, the test template is parsed into a tree structure, then the tree nodes are mutated specifically, and finally the test message is reassembled for fuzzing. To demonstrate the effectiveness of our method, we evaluated it on three protocol programs, and the results show compared with the traditional mutation-based and grammar-based method, the tree-based structure mutation method can further expand the mutation space while ensuring the efficiency of the message, and has a higher probability of discovering program paths and triggering vulnerabilities. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Semantics

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Multi-protocol comprehensive topology probe technology under non-cooperative conditions

Multi-protocol comprehensive topology probe technology under...

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2022 International Symposium on Computer Applications and Information Systems, ISCAIS 2022

作者： Lu, Xuanting Yang, Qichao Liu, Shengli Yang, Pengfei State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781510655010

With the rapid development of the Internet and the increasingly complex and diverse network environment, it is of great significance to quickly and accurately obtain the topology environment of the target network for optimizing network management, locating network resources and ensuring network security. Most of the existing network topology detection methods are implemented based on the SNMP protocol, or use the Traceroute-like method for active detection. However, in a non-cooperative environment, that is, the router disables SNMP permissions or prohibits responding to probe packets to shield Traceroute probes, network probes will face problems such as missing information and blocked probes. Based on the original SNMP protocol detection, this paper adopts RIP, OSPF and other routing protocols to supplement the detection method, which greatly reduces the number of undetectable nodes. In addition, for a small number of router devices that are still undetectable, the Traceroute directional breakthrough method using the routing table as a clue is used to bypass these undetectable nodes, complete the missing information in the network topology, and further optimize and improve the detection results. © 2022 SPIE

关键词： Network topology

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