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作者： Jin, Hui Li, Zhaoyang Hu, Ruiqin Tan, Jinglei Zhang, Hongqi State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan450001 China School of Cyberspace Security Zhengzhou University Zhengzhou Henan450001 China

Eavesdropping attacks have seriously threatened network security. Attackers could eavesdrop on target nodes and link to steal confidential data. In the traditional network architecture, the static routing path and the important nodes determined by the nature of network topology provide a great convenience for eavesdropping attacks. To resist monitoring attacks, this paper proposes a random routing mutation defense method based on dynamic path weight (DPW-RRM). It utilizes network centrality indicators to determine important nodes in the network topology and reduces the probability of important nodes in path selection, thereby distributing traffic to multiple communication paths, achieving the purpose of increasing the difficulty and cost of eavesdropping attacks. In addition, it dynamically adjusts the weight of the routing path through network state constraints to avoid link congestion and improve the availability of routing mutation. Experimental data shows that DPW-RRM could not only guarantee the normal algorithmic overhead, communication delay, and CPU load of the network, but also effectively resist eavesdropping attacks. Copyright © 2023 KSII.

关键词： Network topology

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FirmVulSeeker—BERT and Siamese Network-Based Vulnerability Search for Embedded Device Firmware Images

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Journal on Internet of Things 2022年第1期4卷 1-20页

作者： Yingchao Yu Shuitao Gan Xiaojun Qin State Key Laboratory of Mathematical Engineering and Advanced Computing WuxiJiangsu214083China

In recent years,with the development of the natural language processing(NLP)technologies,security analyst began to use NLP directly on assembly codes which were disassembled from binary executables in order to examine binary similarity,achieved great ***,we found that the existing frameworks often ignored the complex internal structure of instructions and didn’t fully consider the long-term dependencies of *** this paper,we propose firmVulSeeker—a vulnerability search tool for embedded firmware images,based on BERT and Siamese *** first builds a BERT MLM task to observe and learn the semantics of different instructions in their context in a very large unlabeled binary ***,a finetune mode based on Siamese network is constructed to guide training and matching semantically similar functions using the knowledge learned from the first ***,it will use a function embedding generated from the fine-tuned model to search in the targeted corpus and find the most similar function which will be confirmed whether it’s a real vulnerability *** evaluate the accuracy,robustness,scalability and vulnerability search capability of *** show that it can greatly improve the accuracy of matching semantically similar functions,and can successfully find more real vulnerabilities in real-world firmware than other tools.

关键词： Embedded device firmware vulnerability search BERT siamese network

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Ultra-Fast Mini License Plate Recognition System Based-on Vision Processing Unit 2

Ultra-Fast Mini License Plate Recognition System Based-on Vi...

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2nd International Conference on Big-Data Service and Intelligent Computation, BDSIC 2020

作者： Wang, Junhui Ren, Shuangyin He, Jiezhong Ji, Xiaolan Huang, Diqing College of Computer National University of Defense Technology State Key Laboratory of Mathematical Engineering and Advanced Computing China College of Computer National University of Defense Technology

ISBN: (纸本)9781450388399

As more embedded environments need license plate recognition systems, how to recognize car plates with high speed/accuracy and low energy has become an important and challenging problem. In this paper, we propose a ultra-Fast miNi (FaNi) license plate recognition (LPR) system. The FaNi system are divided into one training sub-system and one inference sub-system. The former are used to get some offline features;then, the latter is deployed online to recognize license numbers with nearly real-time speed. The inference system is comprised of the vision processing unit (VPU) and the display unit. These two parts are both implemented with hardware logic. Experiments show that the FaNi system can obtain high accuracy and high speed with low resource cost. © 2020 ACM.

关键词： Field programmable gate arrays (FPGA)

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Research on the Protection Mechanism of Cisco IOS Exploit

Research on the Protection Mechanism of Cisco IOS Exploit

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作者： Jinzhu Wang Ruijie Cai Shengli Liu State Key Laboratory of Mathematical Engineering and Advanced Computing

Cisco IOS is an operating system that runs on Cisco routing and switching *** security is important to the entire *** vulnerability attacks have become one of the main sources of threat to Cisco IOS security,it is necessary to analyze the defense mechanism of IOS against vulnerability *** purpose of this paper is to find out the deficiencies of IOS vulnerability defense mechanism in time and put forward improvement methods and preventive ***,this paper introduces the protection mechanism of Cisco IOS vulnerability,including CheckHeaps,DEP,*** principle of these mechanisms and the idea of vulnerability protection are *** then,after analyzing the shortcomings of these protection mechanisms,the basic idea of bypassing these protection mechanisms is ***,in view of the shortcomings of Cisco IOS vulnerability defense mechanism and the proposed bypass methods,some advices about how to better protect Cisco IOS from vulnerability exploitation are given.

关键词： Research on the Protection Mechanism of Cisco IOS Exploit Cisco IOS

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Summary of Large Scale Graph computing Models

Summary of Large Scale Graph Computing Models

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2019 2nd International Conference on Mechanical,Electronic and engineering Technology(MEET 2019)

作者： Sheng Yang State Key Laboratory of Mathematical Engineering and Advanced Computing

Large-scale graph data is a research hotspot in the processing of big data and is generally used in traffic management, analysis of social network and semantic web, etc., resulting in the emergence of a variety of large-scale graph computing platforms. How to select a more suitable graph computing platform for different tasks has become one of the hot topics in the field of graph computing. The related knowledge of graph computing models is systematically reviewed in this paper. First of all, the concept of graph computing model is outlined, including the definition and characteristics of graph computing and the development of graph computing models. Then, three kinds of graph computing models are introduced. Finally, the development process of the graph computing models is summarized, and the future research direction is prospected.

关键词： Large-scale graph computing graph processing distributed computing

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Fw-fuzz: A code coverage-guided fuzzing framework for network protocols on firmware

Fw-fuzz: A code coverage-guided fuzzing framework for networ...

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作者： Gao, Zicong Dong, Weiyu Chang, Rui Wang, Yisen Cyberspace Security Department State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China College of Computer Science and Technology Zhejiang University Hangzhou China

Fuzzing is an effective approach to detect software vulnerabilities utilizing changeable generated inputs. However, fuzzing the network protocol on the firmware of IoT devices is limited by inefficiency of test case generation, cross-architecture instrumentation, and fault detection. In this article, we propose the Fw-fuzz, a coverage-guided and crossplatform framework for fuzzing network services running in the context of firmware on embedded architectures, which can generate more valuable test cases by introspecting program runtime information and using a genetic algorithm model. Specifically, we propose novel dynamic instrumentation in Fw-fuzz to collect the running state of the firmware program. Then Fw-fuzz adopts a genetic algorithm model to guide the generation of inputs with high code coverage. We fully implement the prototype system of Fw-fuzz and conduct evaluations on network service programs of various architectures in MIPS, ARM, and PPC. By comparing with the protocol fuzzers Boofuzz and Peach in metrics of edge coverage, our prototype system achieves an average growth of 33.7% and 38.4%, respectively. We further verify six known vulnerabilities and discover 5 0-day vulnerabilities with the Fw-fuzz, which prove the validity and utility of our framework. The overhead of our system expressed as an additional 5% of memory growth. © 2020 John Wiley & Sons, Ltd.

关键词： Firmware

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LID-senone extraction via deep neural networks for end-to-end language identification

LID-senone extraction via deep neural networks for end-to-en...

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Speaker and Language Recognition Workshop, Odyssey 2016

作者： Jin, Ma Song, Yan McLoughlin, Ian Dai, Li-Rong Ye, Zhong-Fu National Engineering Laboratory of Speech and Language Information Processing University of Science and Technology of China China School of Computing University of Kent Medway United Kingdom State Key Laboratory of Mathematical Engineering and Advanced Computing China

A key problem in spoken language identification (LID) is how to effectively model features from a given speech utterance. Recent techniques such as end-to-end schemes and deep neural networks (DNNs) utilising transfer learning such as bottleneck (BN) features, have demonstrated good overall performance, but have not addressed the extraction of LID-specific features. We thus propose a novel end-to-end neural network which aims to obtain effective LID-senone representations, which we define as being analogous to senones in speech recognition. We show that LID-senones combine a compact representation of the original acoustic feature space with a powerful descriptive and discriminative capability. Furthermore, a novel incremental training method is proposed to extract the weak language information buried in the acoustic features of insufficient language resources. Results on the six most confused languages in NIST LRE 2009 show good performance compared to state-of-the-art BN-GMM/i-vector and BN-DNN/i-vector systems. The proposed end-to-end network, coupled with an incremental training method which mitigates against over-fitting, has potential not just for LID, but also for other resource constrained tasks. © Odyssey 2016: Speaker and Language Recognition Workshop. All rights reserved.

关键词： Deep neural networks

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Simulation detection based on single photon quantum key distribution protocol

Simulation detection based on single photon quantum key dist...

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2020 International Conference on Electronics, Communications and Information Technology, CECIT 2020

作者： Liu, X.N. Hu, C.C. Yin, M.J. Jin, L. School of Information Engineering Zhengzhou University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China School of Cyberspace and Security Information Engineering University Zhengzhou China

With the continuous development of quantum communication in recent years, quantum key distribution (QKD) has also become a key technology in the field of quantum communication. Due to the limitation of physical resources and experimental conditions, the effectiveness of different communication protocols cannot be accurately analyzed. To solve this problem, a protocol simulation method is proposed, BB84 and B92 protocols are simulated and analyzed on a classic computer by this method. On the Eclipse IDE Developers platform, the simulation program of the quantum communication protocol was written using Java language, the simulation process under the ideal environment and the eavesdropping environment was analyzed with emphasis. The simulation results show that the key distribution efficiency of BB84 is about 50% without eavesdroppers, which is much higher than 25% of B92, and the key distribution efficiency under eavesdropping conditions is about 25% and 18%. The experimental results are consistent with theoretical expectations, verifying the correctness of the protocol simulation, and also proving the feasibility of using computers for quantum communication protocol simulation. © Published under licence by IOP Publishing Ltd.

关键词： Computer software

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A survey on federated learning:a perspective from multi-party computation

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Frontiers of Computer Science 2024年第1期18卷 93-103页

作者： Fengxia LIU Zhiming ZHENG Yexuan SHI Yongxin TONG Yi ZHANG Institute of Artificial Intelligence and Key Laboratory of Mathematics Informatics Behavioral Semantics Beihang UniversityBeijing 100191China State Key Laboratory of Software Development Environment and Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang UniversityBeijing 100191China Pengcheng Laboratory Shenzhen 518055China Zhongguancun Laboratory Beijing 100190China Institute for Mathematical Sciences and Engineering Research Center of Financial Computing and Digital Engineering Renmin University of ChinaBeijing 100872China

Federated learning is a promising learning paradigm that allows collaborative training of models across multiple data owners without sharing their raw *** enhance privacy in federated learning,multi-party computation can be leveraged for secure communication and computation during model *** survey provides a comprehensive review on how to integrate mainstream multi-party computation techniques into diverse federated learning setups for guaranteed privacy,as well as the corresponding optimization techniques to improve model accuracy and training *** also pinpoint future directions to deploy federated learning to a wider range of applications.

关键词： sfederated learning multi-party ycomputation privacy-preserving data mining distributed learning

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Method based on GSCPN for network vulnerability analysis

Journal of Software

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Journal of Software 2013年第8期8卷 2032-2038页

作者： Gao, Xiang Zhu, Yue-Fei Fei, Jin-Long Han, Tao State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450002 China

With the development of network security research, network attack modeling and analysis techniques have been paid more and more attention. A generalized stochastic colored Petri Net (GSCPN) Model is proposed. To each attack, a GSCPN model is constructed to describe the relation of components graphically. Algorithm to construct a composite attack and method for network vulnerability analysis are delivered also. The exploitation cost of vulnerabilities is estimated. The method is relatively simple, which is different from traditional method. The network example further validates the proposed method for network vulnerability analysis. © 2013 ACADEMY PUBLISHER.

关键词： Network security

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