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International Conference on P2P, Parallel, Grid, Cloud and Internet computing (3PGCIC)

作者： Xiaolong Liu Qiang Wei Ziwei Ye State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781479978724

CCFIR (Compact Control Flow Integrity and Randomization) has low performance overhead as an exploit mitigation, but it is hard to mitigate exploits by hijacking virtual function pointer, which are emerging in recent years. Because of the polymorphism of virtual functions, CCFIR can't determine a unique spring board stub. We propose a new practical protection method named SDCFI (Static-Dynamic Control Flow Integrity), whose goal is to protect virtual function pointers from hijacking. Taking advantage of static analysis result of IDA and PIN dynamic instrumentation, SDCFI improves the accuracy of the disassembly and identifies indirect call target addresses at runtime. We observe that there are always double 0x90 bytes for alignment in the gap between two functions, which can be substituted by a two-byte checkmark. Using the checkmark, SDCFI can validate a target more simply and faster than traditional CFI. Based on these approaches, SDCFI can prevent control-flow hijacking attacks including ROP, because the gadgets of stack pivot can't pass the validation. We evaluate our prototype implementation for Internet Explorer8 browser on Windows XP, which faces serious security threats since April 8, 2014. SDCFI protects most indirect call instructions in ***, and has low runtime overhead of 1.48% on average. Experiments on real-world exploits for IE8 browser also show that SDCFI can effectively mitigate exploits by hijacking virtual function pointer.

关键词： Runtime Browsers Registers Instruments Security Internet Accuracy

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Convergence and Scalarization in Whole Function Vectorization

Convergence and Scalarization in Whole Function Vectorizatio...

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IEEE International Symposium on Dependable, Autonomic and Secure computing (DASC)

作者： Feng Yue Jianmin Pang Jiuzhen Jin Dai Chao State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

When implementing SPMD programs on multi core platforms, whole function vectorization is an important optimization method. SPMD program has drawback that lots of instructions across multi threads are redundant which is sustained in vectorization. This paper proposes to alleviate this overhead by detecting scalar operations and extract them out in vectorization instructions. An algorithm is designed to deal with control flow and data flow synchronously in which convergent and invariance analysis is employed to statically identify convergent execution and invariant values or instructions. Our algorithm is effectively on implementing SPMD programs on multi core platforms. The experiments show our method could improve the execution efficiency by 13.3%.

关键词： Convergence Optimization Algorithm design and analysis Vectors Instruction sets Graphics processing units Multicore processing

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An Automatic Parallel-Stage Decoupled Software Pipelining Parallelization Algorithm Based on OpenMP

An Automatic Parallel-Stage Decoupled Software Pipelining Pa...

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Xiaoxian Liu Rongcai Zhao Lin Han Peng Liu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781479914449

While multicore processors increase throughput for multi-programmed and multithreaded codes, many important applications are single threaded and thus do not benefit. Automatic parallelization techniques play an important role in migrating singe threaded applications to multicore platforms. Unfortunately, the prevalence of control flow, recursive data structures, and general pointer accesses in ordinary programs renders the traditional automatic parallelization techniques unsuitable. Parallel-Stage Decoupled Software Pipelining (PS-DSWP) is proposed to exploit fine-grained pipeline parallelism lurking in ordinary programs with the existence of all kinds of dependences, including arbitrary control dependences, at the instruction level. But it requires knowledge of architectural properties and hardware support of a communication channel and two special instructions. We propose an improved PS-DSWP algorithm based on OpenMP in this paper. It is implemented without relying on CPU architectures by using a high level intermediate representation. Moreover, the Program Dependence Graph (PDG) used in the algorithm is built based on the basic blocks, which exploits coarser-grained parallelism than the original PS-DSWP transformation with PDG based on instructions. OpenMP is employed in our algorithm to assign task and implement synchronization among threads while avoiding dependence on hardware support. We evaluate the loops with complex memory patterns and control flow, which cannot be dealt with by traditional techniques, on multicore platform. As a result, they can be parallelized and gain significant performance improvement with our algorithm. We obtain a maximum speedup as high as 2.07x and on average 1.39x with 5 threads.

关键词： Instruction sets Synchronization Pipeline processing Multicore processing Merging

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An Efficient Sieve Algorithm with Evolutionary Technique

An Efficient Sieve Algorithm with Evolutionary Technique

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International Conference on Communication Technology (ICCT)

作者： Zedong Sun Chunxiang Gu Yonghui Zheng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (数字)9781728181417

ISBN: (纸本)9781728181424

Sieve algorithm plays an important role in solving the shortest vector problem, which is one of the most representative hard lattice problems. In this paper, we propose an efficient sieve algorithm with evolutionary techniques. By combining Gauss Sieve algorithm with global selection, we propose an efficient sieve algorithm. Experimental results show that our algorithm performs better than FPLLL's Gauss Sieve algorithm in solving the shortest vector problem. Furthermore, we explore how mutation behaves in accelerating sieve algorithm.

关键词： Conferences Diversity reception Lattices Communications technology Cryptography Acceleration

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Detecting Information Leakage Based on Subtracting Matrix

Detecting Information Leakage Based on Subtracting Matrix

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International Symposium on Computational Intelligence and Design, ISCID

作者： Zongda Han Binglong Li State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781479970063

This paper proposes an approach of detecting information leakage based on subtracting matrix to determine files when and where were leaked from file system. Due to the low efficiency of detecting leak operation and the rapid growth of the size of storage device make it difficult to locate the place where the leakage occurred. We build a time matrix model by file system access timestamps in a suspicious information system. Then three kinds of two-value (0-1) matrices are generated based on the similarity of access timestamps in the time matrix. The behavior of information leakage can be finally determined by comparing the degree of the similarity in these matrices. The experimental results show the method can detect information leakage more quickly and accurately.

关键词： File systems Measurement Probability distribution Forensics Time complexity Drives Real-time systems

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ZeroDVS: Trace-Ability and Security Detection of Container Image Based on Inheritance Graph

ZeroDVS: Trace-Ability and Security Detection of Container I...

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Cryptography, Security and Privacy (CSP), IEEE International Conference on

作者： Yan Zheng Weiyu Dong Jiangtao Zhao State Key Laboratory of Mathematical Engineering and Advanced Computing ZhengZhou China

ISBN: (数字)9781728186214

ISBN: (纸本)9781728186221

Docker image is the foundation for container operation. Docker Hub is the largest online repository of public container images. Users can upload and download any random image file to the hub due to the absence of adequate security scanning and detection, potentially causing substantial security risks. This paper introduces ZeroDVS, a container image traceability and security detection system based on inheritance graphs. In ZeroDVS, a basic image inheritance graph is built with 160 official images published by Docker Hub. Then, the basic image source of the downloaded image can be identified, and the public vulnerability database is used to scan for public vulnerabilities in image files. ZeroDVS scans the public container images of Docker Hub and identifies the inheritance relationship of public container images to detect public vulnerabilities in the image layer above the parent image simultaneously. Docker image is the foundation for container operation. Docker Hub is the largest online repository of public container images. Users can upload and download any random image file to the hub due to the absence of adequate security scanning and detection, potentially causing substantial security risks. This paper introduces ZeroDVS, a container image traceability and security detection system based on inheritance graphs. In ZeroDVS, a basic image inheritance graph is built with 160 official images published by Docker Hub. Then, the basic image source of the downloaded image can be identified, and the public vulnerability database is used to scan for public vulnerabilities in image files. ZeroDVS scans the public container images of Docker Hub and identifies the inheritance relationship of public container images to detect public vulnerabilities in the image layer above the parent image simultaneously.

关键词： Privacy Databases Operating systems Containers Security Reliability Cryptography

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An Intrusion Detection Feature Selection Method Based on Improved Mutual Information

An Intrusion Detection Feature Selection Method Based on Imp...

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IEEE Information Technology, Networking, Electronic and Automation Control Conference

作者： Zan Qi Jinlong Fei Jue Wang Xue Li State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

Feature selection methods for classification are crucial for intrusion detection techniques using machine learning. High-dimensional features in intrusion detection data affect computational complexity, consume more used resources and more time for data analysis, and the irrelevant and redundant features among them often hinder the performance of classifiers and mislead the classification task. Therefore, it is challenging to select more relevant features from intrusion detection data containing many such features. In this paper, we propose an efficient feature selection algorithm that first considers the correlation between features and the redundancy of pairs of features with respect to class labels based on an improved Pearson correlation coefficient, and later improves the evaluation function based on conditional mutual information to obtain a final subset of features with the goal of improving the classification rate and accuracy. The proposed feature selection method based on improved conditional mutual information is compared with three existing feature selection methods on the frequently studied public benchmark intrusion detection dataset NSL-KDD. The experimental results show that the features selected by the proposed method in this paper lead to a significant reduction in execution time while resulting in higher classification accuracy.

关键词： Correlation coefficient Correlation Redundancy Intrusion detection Machine learning Telecommunication traffic Feature extraction

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Method of multi-feature fusion based on SVM and D-S evidence theory in Trojan detection

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Computer Modelling and New Technologies 2014年第6期18卷 304-310页

作者： Liu, Shengli Gao, Xiang Xu, Pan Liu, Long State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

According to the low accuracy and low stability of the single feature-based method for Trojan detection, a multi-feature fusion method based on SVM and DS evidence theory is proposed. First, three types of flow features such as session, upload data of session/download data of session, distribution of data packet size are extracted from the data stream. Then the SVM classification results of each single feature are used as evidences to construct the basic probability assigned (BPA). Finally, we use DS combination rule of evidence to achieve the decision fusion and give the final detection results by fusion results. The experimental results showed that the accuracy of multi-feature fusion method was 97.48% which has good performance on accuracy and stability compared with the single feature method in Trojan detection.

关键词： Support vector machines

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Distributed key revocation scheme based on shared binary tree

Distributed key revocation scheme based on shared binary tre...

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IEEE International Conference on Progress in Informatics and computing (PIC)

作者： Shaoren Wang Xuehui Du Zhi Yang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

Concerning the identity-based binary tree key revocation scheme, the storage and use of binary tree can not be guaranteed in open cloud environment. This paper proposes a distributed key revocation scheme based on shared binary tree. The scheme splits the binary key tree into branches and distributes them to multiple nodes to save. Then multiple nodes work together to rebuild the key. At the same time, this paper optimizes the lookup algorithm during rebuilding. It solves the issues on distributed storage, safe use and fast reconstruction of the binary tree in the open environment. Experiments and analysis show that the scheme has higher efficiency and makes identity-based key revocation scheme run safely in the open environment.

关键词： Peer-to-peer computing Cryptography

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Bintaint: A Static Taint Analysis Method for Binary Vulnerability Mining

Bintaint: A Static Taint Analysis Method for Binary Vulnerab...

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International Conference on Cloud computing, Big Data and Blockchain (ICCBB)

作者： Zenan Feng Zhenyu Wang Weiyu Dong Rui Chang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781728112787

Vulnerabilities in the current network space has been increasingly concerned by all parties. More and more software is currently in the form of binary code in practical applications. Therefore, the research on vulnerability mining technology for binary code attracts more attention from the researchers. In order to address the problem of binary vulnerability mining, this paper focuses on the taint analysis, and proposes a method called Bintaint, which can perform static taint analysis and generate the taint control flow graph (TCFG). In addition, we implement a system based on Bintaint to reduce the path explosion in the traditional vulnerability analysis process. Combined with our bidirectional search technology and path guidance algorithm to assist the symbol execution technology to generate test cases, the high computational overhead caused by complex constraints can be reduced. Finally, we evaluate our method on X86 programs and six core programs in different architecture embedded devices, and the result shows that our method detect all known vulnerability without false negative and mitigates the problem of path explosion and computational overhead effectively.

关键词： Decoding Data mining Explosions Tools Pollution Software Flow graphs

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