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检索条件"机构=State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou"

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An Improved key Mismatch Attack on Kyber 7

An Improved Key Mismatch Attack on Kyber

引用

7th International Conference on Cryptography, Security and Privacy, CSP 2023

作者： Wang, Yaru Jiang, Haodong Ma, Zhi State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9798350323368

Recently, American National Institute of Standards and Technology (NIST) announced Kyber as the first KEM candidate to be standardized. The security of Kyber is based on the modular learning with errors (MLWE) problem, which achieves excellent efficiency and size. This work proposes an improved key mismatch on Kyber, which can reduce the number of queries required to recover the secret key. We first transform the problem of finding a certain parameter of ciphertexts into a quantum ordered search problem. Then we give the procedure of finding the value of a parameter in the ciphertexts by the quantum method. Finally, we instantiate this attack method on Kyber512, Kyber768 and Kyber1024. Compared with the existing attack algorithm, our improved attack reduces the number of queries for Kyber512, Kyber768 and Kyber1024 by 63%, 59% and 45%, respectively. © 2023 IEEE.

关键词： Security of data

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

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

引用

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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Dynamic Array Double-Access Attack in Ethereum 6

Dynamic Array Double-Access Attack in Ethereum

引用

6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Chang, Xiangyang Zhu, Junhu Zhao, Shibin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781728186351

We propose a new type of variable coverage method called Dynamic Array Double-Access Attack (DADA Attack) in Ethereum Virtual Machine (EVM). Such attack can read and write operations anywhere in the storage area, resulting in abnormal execution of contract and out of control. Vulnerable contracts with such attacks will directly lead to the loss of a large amount of property. To evaluate the effectiveness of such Double-Access Attack, we conducted theoretical analysis and experimental verification, finding attack success rate is 100% under the condition that dynamic array length is controllable. © 2020 IEEE.

关键词： Blockchain

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SoK: A Survey on Redundant Execution Technology

SoK: A Survey on Redundant Execution Technology

引用

2021 International Conference on advanced computing and Endogenous Security, ICACES 2021

作者： Liu, Zijing Zhang, Zheng Xi, Ruicheng Zhu, Pengzhe Ma, Bolin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665424493

Redundant execution technology is one of the effective ways to improve the safety and reliability of computer systems. By rationally configuring redundant resources, adding components with the same function, using the determined redundant execution logic to coordinate and efficiently execute synchronously can effectively ensure high availability of the machine and system. Fault-tolerant is based on redundant execution, which is the primary method of dealing with system hardware failures. Recently, multi-threading redundancy has realized the continuous development of fault-tolerant technology, which makes the processing granularity of the system tolerate random failure factors gradually reduced. At the same time, intrusion tolerant technology has also been continuously developed with the emergence of multi-variant execution technology. It mainly uses the idea of dynamic heterogeneous redundancy to construct a set of variants with equivalent functions and different structures to complete the detection and processing of threats outside the system. We summarize the critical technologies of redundant execution to achieve fault tolerance and intrusion tolerance in recent years, sorts out the role of redundant execution in the development process from fault tolerance technology to intrusion tolerance technology, classify redundant execution technologies at different levels, finally point out the development prospects of redundant execution technology in multiple application fields and future technical research directions. © 2022 IEEE.

关键词： Redundancy

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Embedding Attribute and Relation Information for Person Entity Alignment 6

Embedding Attribute and Relation Information for Person Enti...

引用

6th International Conference on Big Data and Information Analytics, BigDIA 2020

作者： Wang, Can Liu, Xiaonan Yin, Meijuan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

Person entity alignment is to distinguish whether the person entity information extracted from different data sources refer to the same entity. Existing methods mainly use attribute and relation information of entity to solve entity alignment problem. Most of them are based on common information of entity, while ignore some non-common but semantically similar attribute information and they only consider the relation between first-order adjacent entity, which makes it difficult to accurately align entity in the case of scarcity of common information. so we propose a person entity alignment method based on joint embedding of attribute and relation information, which makes full use of non-common but related information of entity to align them and improves the Hit@k of alignment results when common information is sparse. In the method, the representation vector of attribute information and the representation vector of relation information are obtained by embedding. During embedding, we consider the identification of different attributes and the second-order relation between entities to improve the role of feature attributes and the second-order relation in entity alignment. When calculating the similarity of entities, binary linear regression model is used to fit the weight of attribute information and relation information similarity, so as to adapt to the different characteristics of the entity data under different circumstances. The experimental results show that, compared with the related methods, the Hit@1 value and Hit@10 value of the proposed method increased by more than 8.4% and more than 9.1% respectively. © 2020 IEEE.

关键词： Embeddings

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A short text spectrum clustering method based on frequent itemsets 4

A short text spectrum clustering method based on frequent it...

引用

4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Luo, Nan Zhang, Ping Li, Qingbao Chen, Zhifeng Feng, Peijun Xue, Tianxiao Engineering and Advanced Computing State Key Laboratory of Mathematical Zhengzhou China

ISBN: (纸本)9781538683392

Short text datum, which contains a lot of useful information, could be easily found on a wide variety of self-media platform and social communication tools. on It is significant to use datum mining technology to automatically acquire knowledge from these datum. However, in short text datum, the word count is small, the text length is short and the information contained is little. Due to all these disadvantages, there are problems of feature sparseness and high information dimensionality. The accuracy of general text mining algorithms is usually unacceptable. This paper proposes a spectral clustering short text analysis method based on frequent itemsets. Firstly, the method cuts the short text datum, and compresses the datum using frequent itemsets. Secondly, a spectral algorithm based on Nyström sampling method is applied to perform clustering and topic extraction on the frequent itemsets. The method effectively solves the problems of feature sparseness and wide dimensions of short text datum. Experiments show that the methodhas better accuracy and performance than the existing algorithms when clustering short texts, and has a good clustering effect. © 2018 IEEE.

关键词： Data mining

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Steganalysis of Adaptive Steganography Under the Known Cover Image 1st

Steganalysis of Adaptive Steganography Under the Known Cover...

引用

1st International Conference on Security and Privacy in Digital Economy, SPDE 2020

作者： Li, Jialin Luo, Xiangyang Zhang, Yi Zhang, Pei Yang, Chunfang Liu, Fenlin State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9789811591280

Digital image steganography is one of the important ways to achieve covert communication to protect users’ data privacy. Steganalysis technology is the key technology to check the security of steganography, and the extraction of embedded messages is an important challenge for image steganalysis technology. Existing methods are for plain text embedding or only for certain special scenarios, they are not applicable to the extraction under the known cover image. To this end, this paper proposes a method of extracting embedded messages under the condition of the known cover images. First, the STCs encoding process is analyzed using the syndrome trellis. Second, a path in the syndrome trellis can be obtained by using the stego sequence and a certain parity-check matrix. Meanwhile, the embedding process can also be partially simulated using the cover sequence and the parity-check matrix. By comparing whether the paths are consistent, the coding parameters can be quickly filtered to find the correct submatrices and extract the correct embedded messages. This algorithm avoids the second embedding of all possible secret messages, which significantly improves the efficiency of coding parameter recognition. The experimental results show that the proposed method can identify STCs parameters of stego images using HUGO steganography in a short time, so as to realize the extraction of embedded messages. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Steganography

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

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

引用

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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Zero WFuzzer: Target-Oriented Fuzzing for Web Interface of Embedded Devices 4

Zero WFuzzer: Target-Oriented Fuzzing for Web Interface of E...

引用

4th IEEE International Conference on Computer and Communication engineering Technology, CCET 2021

作者： Zheng, Yan Dong, Weiyu Cheng, Hui State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665438902

With the popularization of embedded devices, security issues continue to occur. The existing automated security testing methods for embedded devices are mainly carried out from two aspects: the Web interface of the device or the firmware binary file. This paper proposes a testing framework ZeroWFuzzer that combines the Web interface of embedded devices with firmware binary, which automatically generates test cases through the Web interface, and uses binary instrumentation to guide the fuzzing test. Experiments in embedded devices have found that ZeroWFuzzer has higher efficiency and quantity of triggering vulnerabilities than the protocol fuzzing tool Boofuzz and the Web security testing tool Xray. © 2021 IEEE.

关键词： Firmware

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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...

引用

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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