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IEEE Information Technology, Networking, Electronic and Automation Control Conference

作者： Qiangqiang Niu Xiaoyong Li Ministry of Education Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Beijing China

ISBN: (数字)9781728143903

ISBN: (纸本)9781728143910

WEB attack detection is an important part of WEB security. This paper proposes a web attack detection method based on Convolutional Neural Network (CNN) combined with Gated Recurrent Unit (GRU). In order to improve the detection performance, we extract eight statistical features with good classification effect to augment the original data. In addition, we also pre-trained the word embedding matrix using the word2Vec model, then obtained the input of the CNN-GRU model and classified the final results. The experimental results show that the accuracy of the method in the HTTP CSIC 2010 dataset is 99.00%, the recall rate is 97.74%, the F1 value is 98.77% and the precision is 99.82%. Compared with traditional machine learning methods, this method proposed in this paper has better performance.

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Comprehensive Information Security Evaluation Model Based on Multi-Level Decomposition Feedback for IoT

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Computers, Materials & Continua 2020年第10期65卷 683-704页

作者： Jinxin Zuo Yueming Lu Hui Gao Ruohan Cao Ziyv Guo Jim Feng School of Cyberspace Security Beijing University of Posts and TelecommunicationsBeijing100876China School of Information and Communication Engineering Beijing University of Posts and Telecommunica-tionsBeijing100876China Key Laboratory of Trustworthy Distributed Computing and Service(BUPT) Ministry of EducationBeijing100876China Amphenol Global Interconnect Systems San JoseCA 95131USA

The development of the Internet of Things(IoT)calls for a comprehensive in-formation security evaluation framework to quantitatively measure the safety score and risk(S&R)value of the network *** this paper,we summarize the architecture and vulnerability in IoT and propose a comprehensive information security evaluation model based on multi-level decomposition *** evaluation model provides an idea for information security evaluation of IoT and guides the security decision maker for dynamic ***,we establish an overall evaluation indicator system that includes four primary indicators of threat information,asset,vulnerability,and management,*** also includes eleven secondary indicators of system protection rate,attack detection rate,confidentiality,availability,controllability,identifiability,number of vulnerabilities,vulnerability hazard level,staff organization,enterprise grading and service continuity,***,we build the core algorithm to enable the evaluation model,wherein a novel weighting technique is developed and a quantitative method is proposed to measure the S&R ***,in order to better supervise the performance of the proposed evaluation model,we present four novel indicators includes residual risk,continuous conformity of residual risk,head-to-tail consistency and decrease ratio,*** results show the advantages of the proposed model in the evaluation of information security for IoT.

关键词： IoT information security quantitative evaluation safety score residual risk

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MDPPC: Efficient Scalable Multiparty Delegated PSI and PSI Cardinality

MDPPC: Efficient Scalable Multiparty Delegated PSI and PSI C...

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Annual Conference on Privacy, Security and Trust, PST

作者： Yihao Yang Xiaolei Dong Jiachen Shen Zhenfu Cao Yunbo Yang Jun Zhou Liming Fang Zhe Liu Chunpeng Ge Chunhua Su Zongyang Hou Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Research Center for Basic Theories of Intelligent Computing Research Institute of Basic Theories Zhejiang Lab Hangzhou China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Science and Technology on Parallel and Distributed Processing Laboratory (PDL) Changsha China Shandong University Jinan China University of Aizu Fukushima Japan Print-Rite Technology Development Co. Ltd. Of Zhuhai China

Private Set Intersection (PSI) is one of the most important functions in secure multiparty computation (MPC). PSI protocols have been a practical cryptographic primitive and there are many privacy-preserving applications based on PSI protocols such as computing conversion of advertising and distributed computation. Private Set Intersection Cardinality (PSI-CA) is a useful variant of PSI protocol. PSI and PSI-CA allow several parties, each holding a private set, to jointly compute the intersection and cardinality, respectively without leaking any additional information. Nowadays, most PSI protocols mainly focus on two-party settings, while in multiparty settings, parties are able to share more valuable information and thus more desirable. On the other hand, with the advent of cloud computing, delegating computation to an untrusted server becomes an interesting problem. However, most existing delegated PSI protocols are unable to efficiently scale to multiple clients. In order to solve these problems, this paper proposes MDPPC, an efficient PSI protocol which supports scalable multiparty delegated PSI and PSI-CA operations. Security analysis shows that MDPPC is secure against semi-honest adversaries and it allows any number of colluding clients. For 15 parties with set size of 2 20 on server side and 2 16 on clients side, MDPPC costs only 81 seconds in PSI and 80 seconds in PSI-CA, respectively. The experimental results show that MDPPC has high scalability.

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An Improved Multi-objective Evolutionary Algorithm Based on Gaussian Distribution Estimation

An Improved Multi-objective Evolutionary Algorithm Based on ...

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作者： Li-yang HOU Xiao-yong LI Yan-rong LI Wen-ping KONG Hai-feng CHANG Key Laboratory of Trustworthy Distributed Computing and Service Ministry of EducationBeijing University of Posts and Telecommunications

When an emergency occurs, how to specify a reasonable resource scheduling scheme significantly affects disaster relief efficiency. However, most actual existing schemes lack considering satisfaction of potential disaster sites, and lack a scheduling model with 3 or more optimization goals, which makes it difficult to apply to complex scenarios. In this paper, we propose a four-objective resource scheduling optimization model that additionally considers potential disaster sites satisfaction. And we have designed an improved NSGA-Ⅲ-GD algorithm to optimize this model. First, we introduce NSGA-Ⅲ, an algorithm that has a great advantage in multi-objective optimization problems. And more importantly, we use Gaussian estimation distribution instead of traditional cross mutation operators to extract the overall characteristics of the population, which improves the search accuracy of the optimal solution and greatly improves the convergence speed. The experimental results clearly show that the algorithm proposed in this paper has achieved very good performance.

关键词： Potential disaster sites Resource scheduling Multi-objective optimization NSGA-Ⅲ-GD

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PDG2Vec: Identify the Binary Function Similarity with Program Dependence Graph

PDG2Vec: Identify the Binary Function Similarity with Progra...

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IEEE International Conference on Software Quality, Reliability and Security (QRS)

作者： Yuntao Zhang Yanhao Wang Yuwei Liu Zhengyuan Pang Binxing Fang Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China QI-ANXIN Technology Group Inc. Beijing China Chinese Academy of Sciences Institute of Software Beijing China Beijing DigApis Technology Co. Ltd Beijing China

Binary code similarity identification is an important technique applied to many security applications (e.g., plagiarism detection, bug search). The primary challenge of this research topic is how to extract sufficient information from the binary code for similarity comparison. Although numerous approaches have been proposed to address the challenge, most of them leverage features determined by human experience or extracted using machine learning methods and ignore some critical technique semantic information. Additionally, they assess their approach exclusively in laboratory environments and lack real-world datasets. Both problems lead to the limited effectiveness of these methods in real application scenarios (e.g., vulnerable function search).In this paper, we propose a novel approach PDG2Vec, which extracts the data dependence graph and control dependence graph (i.e., program dependence graph (PDG)) as the features of functions and uses them for identifying function similarity. Meanwhile, we design several strategies to optimize the PDG’s construction and use them in similarity comparison to balance time-consuming and accuracy. We implement the prototype of PDG2Vec, which can perform binary code similarity comparison across architectures of x86, x86_64, MIPS32, ARM32, and ARM64. We evaluate PDG2Vec with two datasets. The experimental results show that PDG2Vec is resilient to cross-architecture and extracts more precise semantics than other approaches. Moreover, PDG2Vec outperforms the state-of-the-art tools in the vulnerable function search scenario and has excellent performance.

关键词： Plagiarism Semantics Prototypes Binary codes Software quality Feature extraction Search problems

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QPSK pilot-aided carrier phase recovery algorithm for 800-Gb/s/? DP-256QAM transmission

QPSK pilot-aided carrier phase recovery algorithm for 800-Gb...

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2020 Asia Communications and Photonics Conference, ACPC 2020/International Conference on Information Photonics and Optical Communications, IPOC 2020

作者： Cui, Han Xu, Xuekai Liu, Shuangyue Lu, Yueming Qiao, Yaojun State Key Laboratory of Information Photonics and Optical Communications School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China

A QPSK pilot-aided carrier phase recovery algorithm is investigated for 800-Gb/s/? DP-256QAM transmission systems. Simulation results show that, compared with BPS, this proposed algorithm reduces by 99% computational ... 详细信息

ISBN: (纸本)9781557528209

关键词： Quadrature phase shift keying

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QPSK-assisted MIMO equalization for 800-Gb/s/? DP-256QAM systems

QPSK-assisted MIMO equalization for 800-Gb/s/? DP-256QAM sys...

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2020 Asia Communications and Photonics Conference, ACPC 2020/International Conference on Information Photonics and Optical Communications, IPOC 2020

作者： Liu, Siqi Liu, Shuangyue Tang, Xizi Guo, Mengqi Lu, Yueming Qiao, Yaojun State Key Laboratory of Information Photonics and Optical Communications School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing100876 China

A QPSK-assisted MIMO equalization is investigated to compensate bandwidth limitation for 800-Gb/s/? DP-256QAM systems with only 25G-class optics. Compared with conventional MIMO equalization, the proposed equalization... 详细信息

ISBN: (纸本)9781557528209

关键词： Quadrature phase shift keying

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Unsupervised Domain Adaptation for Human Activity Recognition in Radar

Unsupervised Domain Adaptation for Human Activity Recognitio...

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IEEE National Conference on Radar

作者： Xinyu Li Xiaojun Jing Yuan He Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9781728189420

ISBN: (纸本)9781728189437

The difficulty of obtaining large-scale labeled radar data hinders the generalization of supervised deep learning algorithms, which makes the performance of these approaches drop when applied to a new domain. In this paper, we propose an unsupervised adversarial domain adaptation method with radar micro- Doppler spectrograms for human activity recognition. An improved adversarial loss, which has the same mechanism as Generative Adversarial Network, is employed for optimization. Besides, a multi-layer domain discriminator is presented in this method. A simulated dataset (source domain) with labeled radar spectrograms and a measured dataset (target domain) with unlabeled spectrograms are utilized for experiment. Experimental results demonstrate that the proposed method has good performance (with an average accuracy of 81.6%) on recognizing human activities without labeled measured spectrograms in the target domain. And comparison experiments with several state-of-the-art domain adaptation methods also indicate the efficiency of the proposed model.

关键词： Radar Feature extraction Spectrogram Adaptation models Training Task analysis Radar measurements

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An Effective Encrypted Traffic Classification Method Based on Pruning Convolutional Neural Networks for Cloud Platform

An Effective Encrypted Traffic Classification Method Based o...

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International Conference on Electronics, Communications and Information Technology (CECIT)

作者： Zilong Han Erxia Li Shichao Li Xiaoyong Li Chaoqun Kang Ruiwen Deng Yali Gao State Grid Shanghai Energy Interconnection Research Institute Beijing China Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education Beijing China Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665437585

With the rapid development of cloud computing technology, the traffic of cloud platform also increases rapidly. Most of these traffic adopt encryption technology, the original traffic classification method is no longer effective. In this paper, we propose an efficient encrypted traffic classification method based on pruning convolution neural network: PCNN. This method does not need to extract features manually, but automatically extracts high-level features through CNN, which makes the model have generalization ability and reduces the cost. Then the pruning technology is adopted to prune the model and retain the parameters that are highly important to the model, which greatly reduces the size and computation of the model and will not affect the performance of the model. We used the public network dataset ISCXVPN2016 to verify our proposed method, the experiments show that the F1 score of our proposed approach is 93% which is improved by 3%, and the precision is 94%, which is improved by 5%.

关键词： Cloud computing Computational modeling Data preprocessing Neurons Telecommunication traffic Feature extraction Data models

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A Multi-Objective Emergency Resource Scheduling Method Based on MOEA/D

A Multi-Objective Emergency Resource Scheduling Method Based...

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2019第二届算法、计算和人工智能国际会议

作者： Yanrong Li Xiaoyong Li Liyang Hou Wenping Kong Wenxue Ma Key Laboratory of Trustworthy Distributed Computing and Servic Beijing University of Posts and Telecommunications

After unconventional events occur, rapid emergency response is often needed in order to reduce losses. When there are more than one disaster points and more than one supply points, how to coordinate the local dispatch of emergency resources among these points is a problem worth studying. In this paper, we design a multiobjective, multi-point to multi-point and multi-resource emergency scheduling model that consider resources arrive time and transportation cost. Then a new emergency resource scheduling algorithm based on multi objective evolutionary algorithm based on decomposition(MOEA/D) is proposed, a new mutation operator was also designed to solve this problem. The experimental results show that this method can get a feasible scheduling scheme, which is faster than NSGA-II and has better scheduling results.

关键词： emergency resource scheduling MOEA/D multi-objective optimization

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