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HDBFuzzer-Target-oriented Hybrid Directed Binary Fuzzer 21

HDBFuzzer-Target-oriented Hybrid Directed Binary Fuzzer

引用

5th International Conference on Computer Science and Application engineering, CSAE 2021

作者： Yu, Yingchao Qin, Xiaojun Gan, Shuitao State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China

ISBN: (纸本)9781450389853

In this paper, we propose a target-oriented hybrid directed binary fuzzer (HDBFuzzer) to solve the vulnerability confirmation problem based on binary code similarity comparison. HDBFuzzer combines macro function level direction fuzzing and micro path-constraint directed solving. For some branches with simple or loose constraints, it still uses directed mutation of the directed fuzzing to penetrate while for some really hard-to-penetrate constraints, it resorts to guided concolic execution. At the same time, in order to improve the efficiency of constraint solving, we propose a constraint solving method based on "path abstraction", which approximates the solution space by the linear expression and generates effective input utilizing the highly-effective sampling method towards the linear space. Then, under the guidance by the directed greybox fuzzing, HDBFuzzer can generate input that can quickly reach the vulnerable code region and finally crash the program under the test to confirm the vulnerability hidden in the binary program. We evaluate HDBFuzzer against AFLGo-B and QSYM on LAVA-M dataset and ten real-world programs, and the results show that HDBFuzzer is superior to AFLGo-B and QSYM on the bug discovery, bug reproduction and target reaching capabilities.. © 2021 Association for computing Machinery. All rights reserved.

关键词： Software testing

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Code Obfuscation Based on Inline Split of Control Flow Graph

Code Obfuscation Based on Inline Split of Control Flow Graph

引用

2021 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2021

作者： Li, Yang Sha, Zihan Xiong, Xiaobing Zhao, Yuntian State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665418676

Control flow graph is an important concept in the field of program analysis, which represents the source program in the form of graph. On the control flow graph, we can easily analyze the predecessor and successor relationship among basic blocks. This paper we inline the functions in the original program and outline the inlined program randomly to form outline functions. Therefore, we convert the intra-procedure basic block jump to an inter-procedure function call, which hides the basic block jump relationship in the process and obfuscates the function boundaries. In order to further increase the intensity of obfuscation, a bogus function similar to the outline function is added, and the bogus control flow is added in combination with opaque predicates simultaneously. Based on the above work, this paper proposes an obfuscation algorithm which converges and splits the program control flow graph. We utilize the commonly used cryptographic hash algorithm as the test set, and verify the feasibility and effectiveness of the obfuscation algorithm. © 2021 IEEE.

关键词： Graphic methods

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TCLD-Net: A Transfer Learning Internet Encrypted Traffic Classification Scheme Based on Convolution Neural Network and Long Short-Term Memory Network

TCLD-Net: A Transfer Learning Internet Encrypted Traffic Cla...

引用

2021 IEEE International Conference on Communications, computing, Cybersecurity and Informatics, CCCI 2021

作者： Hu, Xinyi Gu, Chunxiang Chen, Yihang Wei, Fushan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665432085

The Internet is about to enter the era of full encryption. Traditional traffic classification methods only work well in non-encrypted environments. How to identify the specific types of network encrypted traffic in an encrypted environment without decryption is one of the foundations for maintaining cyberspace security. Traffic classification based on machine learning relies heavily on the prior knowledge of experts to construct feature sets. Although traffic classification based on deep learning can reduce human intervention, it requires a large amount of labeled data for parameter determination. This paper proposes a tCLD-Net model that combines transfer learning and deep learning. It can be trained on a small amount of labeled data to distinguish network encrypted traffic with a high accuracy. It pre-trains a CLD-Net model in the source domain data set, and fixes the parameters of the convolutional neural network module in it, and trains and tests it in the target domain data set. In order to verify the effectiveness of the tCLD-Net model, we use the ISCX public data set to conduct experiments. The results show that our proposed model can complete 100 epoches training in 208 seconds when the training set only occupies 20% of the target domain. And achieve a classification accuracy rate about 86%. This is 4% higher than the model without pre-training, and the training time is only one third of the model without pre-training. © 2021 IEEE.

关键词： Cryptography

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Inter-domain Link Inference with Confidence Using Naïve Bayes Classifier 2021

Inter-domain Link Inference with Confidence Using Naïve Bay...

引用

2021 13th International Conference on Machine Learning and computing, ICMLC 2021

作者： Zhao, Yi Liu, Yan Guo, XiaoYu Sui, ZhongHang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781450389310

Inter-domain link inference is not only important for network security and fault diagnosis, but also helps to conduct research on inter-domain congestion detection and network resilience assessment. Current researches on this issue lack confidence analysis of the inferred results. In this paper, the IP link types (i.e., intra-domain link and inter-domain link) are considered as the latent variable in probability model, while the parameters are probabilities of different link types with particular features. The expectation maximization algorithm is applied to estimate parameters of the model. In each iteration of EM algorithm, Naïve Bayes is used for classification. The final result is determined according to the probability, and the probability is the confidence of the result. The experimental results show that our method can achieve better precision and recall on the validation set than two existing general methods. © 2021 ACM.

关键词： Network security

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Semantic Understanding of Source and Binary Code based on Natural Language Processing 4

Semantic Understanding of Source and Binary Code based on Na...

引用

4th IEEE advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021

作者： Zhang, Zhongtang Liu, Shengli Yang, Qichao Guo, Shichen State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781728185347

With the development of open source projects, a large number of open source codes will be reused in binary software, and bugs in source codes will also be introduced into binary codes. In order to detect the reused open source codes in binary codes, it is sometimes necessary to compare and analyze the similarity between source codes and binary codes. One of the main challenge is that the compilation process can generate different binary code representations for the same source code, such as different compiler versions, compilation optimization options and target architectures, which greatly increases the difficulty of semantic similarity detection between source code and binary code. In order to solve the influence of the compilation process on the comparison of semantic similarity of codes, this paper transforms the source code and binary code into LLVM intermediate representation (LLVM IR), which is a universal intermediate representation independent of source code and binary code. We carry out semantic feature extraction and embedding training on LLVM IR based on natural language processing model. Experimental results show that LLVM IR eliminates the influence of compilation on the syntax differences between source code and binary code, and the semantic features of code are well represented and preserved. © 2021 IEEE.

关键词： Open source software

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Improving CoatNet for Spatial and JPEG Domain Steganalysis

Improving CoatNet for Spatial and JPEG Domain Steganalysis

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Hao Li Xiangyang Luo Yi Zhang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Advanced Computing and Key Laboratory of Cyberspace Situation Awareness of Henan Provinc Zhengzhou China

The covert communication technology represented by image steganography can realize the safe and reliable information transmission over an open network. Steganalysis is an important way to measure the security of steganography. The application of deep learning in the field of steganalysis has begun to emerge and achieved certain results. However, the existing steganalysis methods based on deep learning extract limited global features and the detection accuracy still needs to be improved. Therefore, this manuscript proposes an improving CoatNet for spatial and JPEG domain steganalysis (IMCoatNet). Firstly, the SKAttention structure is used to extract fine-grained features. Then, the convolution layer, Transformer layer and the pyramid squeezed attention is used to capture multi-scale spatial features. Finally, a weighted loss is designed to enhance the expression ability of the model. The results show that compared with the traditional Spatial Rich Model (SRM) method, the classical deep residual network for steganalysis (SRNet), and the latest siamese CNN for steganalysis (SiaStegNet), the detection accuracy of the proposed CoatNet method for WOW steganography is improved by 19.61%, 4.33% and 5.04%, respectively; The proposed IMCoatNet is also superior on JPEG domain detection.

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Research and Practice of Blending Teaching of Database System Integrating Ideological and Political Theories 3

Research and Practice of Blending Teaching of Database Syste...

引用

3rd IEEE International Conference on Computer Science and Educational Informatization, CSEI 2021

作者： Yao, Jinyang Liu, Fudong Wang, Junchao Zhao, Bo Shan, Zheng Xu, Peng Engineering and Advanced Computing State Key Laboratory of Mathematical Zhengzhou China

ISBN: (纸本)9781728184739

For the problem of the monotonous teaching form of the database system course, we integrate ideology and politics theories into the teaching design of the database system, combined with the 'Ideological and Political Theories teaching in All Course' concepts. And we have absorbed the advantages of online teaching into the offline teaching, forming an efficient teaching program. The program enable teachers to impart knowledge of professional courses to students while also deepening students' understanding of the connotation of ideology and politics theories. © 2021 IEEE.

关键词： Blending

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Dynamic Instrumentation Framework Based on Entity Equipment 6

Dynamic Instrumentation Framework Based on Entity Equipment

引用

6th IEEE International Conference on Computer and Communication Systems, ICCCS 2021

作者： Jiangtao, Zhao Dong, Weiyu Zhang, Haotian Lin, Jian State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9780738126043

Dynamic binary analysis is an important way of program analysis. Most of the existing dynamic analysis tools are based on dynamic binary instrumentation platforms. The existing gdb tool, which is often used for debugging of embedded devices, has low performance on dynamic instrumentation. This paper implements basic block-level instrumentation based on dynamic binary rewriting technology and provides a simple and flexible application programming interface. Through the evaluation, the local instrumentation efficiency of this system is mostly better than the Pin platform, and the remote instrumentation efficiency is about 28.7 times that of the gdb+gdbserver platform. The instrumentation performance has been greatly improved. © 2021 IEEE.

关键词： Efficiency

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Parent-based Powershell Script Fusion Technology

Parent-based Powershell Script Fusion Technology

引用

2021 International Symposium on Computer Technology and Information Science, ISCTIS 2021

作者： Cheng, Sipeng Sha, Zihan Yu, Pu Bu, Wenjuan Huo, Guovu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665414418

To address the characteristics of traditional obfuscation methods such as single approach and obvious features, a Parent-based Powershell Script Fusion Technology is proposed based on code fusion. This technology uses the target script to undergo slice encryption processing, and in-depth fusion with the parent script in the execution logic and execution flow, and uses the parent script to conceal the behavior characteristics of the target script. A number of Powershell scripts commonly used for infiltration are selected as the test set to test the proposed technique. The test results show that the proposed technique can reduce the detection rate of the antivirus engine for the target script and has a greater advantage in anti-static analysis. © 2021 IEEE.

关键词： Cryptography

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Research on security assessment based on big data and multi-entity profile 5

Research on security assessment based on big data and multi-...

引用

5th IEEE advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2021

作者： Liu, Wenfu Pang, Jianmin Yang, Shudan Li, Nan Du, Qiming Sun, Daozhu Liu, Fudong State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

Security assessment is one of the important problems, especially in the fields of military training, transportation and network management. The security "related parties"(entities in this paper) have internal relations in the three fields. It is of great significance of constructing the attributes of these entities or even designing a unified security assessment method. Security assessment in these areas has been studied and explored for a long time. However, the research is relatively scattered and unilateral. It is no unified and reusable method from data collection to security assessment. Based on the advantages of big data technology in the storage and analysis of massive data, the paper proposed a security risk element acquisition method from data collection and preprocessing, storage and mining to attribute extraction and aggregation. In addition, drawing on the idea of user portraits in other fields, constructed personnel entities, equipment entities and "other"entity labels related to security risks. Finally, a security risk assessment process based on these entities is designed. © 2021 IEEE.

关键词： Big data

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