Yao Yu

Northeastern University

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i-10 index

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Yonghui Li

University of Sydney

Shumei Liu

Chang'an University

Branka Vucetic

University of Sydney

Phee Lep Yeoh

University of the Sunshine Coast

Lei Guo

Chongqing University of Posts and Telecommunications

Qingyang Song

Chongqing University of Posts and Telecommunications

Lei Guo

Chongqing University of Posts and Telecommunications

Wanyi Gu

Guangzhou University

Yue Zong

Powerchina Huadong Engineering Corporation (China)

Yuhuai Peng

Northeastern University

Cooperative Institutions

Northeastern University

Beijing University of Posts and Telecommunications

Chinese Academy of Sciences

Universidad del Noreste

Shanghai Jiao Tong University

Chongqing University of Posts and Telecommunications

University of Chinese Academy of Sciences

Peking University

Beijing Jiaotong University

State Key Laboratory of Information Photonics and Optical Communications

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Analysis and Countermeasure for Wormhole Attacks in Wireless Mesh Networks on a Real Testbed

Jie Zhou Jiannong Cao Jun Zhang Chisheng Zhang Yao Yu

The wormhole attack is a severe attack in Wireless Mesh Networks (WMNs). It involves two or more wormhole endpoints colluding to capture traffic from one place in the network and replay it to another faraway place through a secret tunnel, so as to distort network routing. It may lead to even more serious threats such as packet dropping and denial of service (DoS). Although a lot of works have been done on detecting wormhole attacks, few of them actually evaluated their solutions on a testbed to consider the real network conditions. In this paper, we set up a WMN testbed for studying wormhole attacks to fill this gap. Some existing approaches used RTT to detect wormhole attacks. However, from both theoretical analysis and experimental results, we observed that the standard deviation of round trip time (stdev(RTT)) is a more efficient metric than RTT to identify wormhole attacks. Accordingly, we propose a new algorithm called Neighbor-Probe-Acknowledge (NPA) to detect wormhole attacks. Compared with existing works, NPA does not need time synchronization or extra hardware support. Moreover, it achieves higher detection rate and lower false alarm rate than the methods using RTT under different background traffic load conditions.

Testbed

Wormhole

Countermeasure

10.1109/aina.2012.81

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Citations (13)

Reliable Fog-Based Crowdsourcing: A Temporal–Spatial Task Allocation Approach

IEEE Internet of Things Journal (2019)

Yao Yu Fuliang Li Shumei Liu Jinli Huang Lei Guo

With the rapid increase in service requirements driven by Internet of Things (IoT) networks, mobile crowdsourcing has become a compelling paradigm that can efficiently solve complex tasks in the physical world. Nevertheless, we found that most IoT tasks have constraints on deadline, location, and resource consumption, which limit the application of crowdsourcing platforms in the IoT networks. In this article, we innovatively propose a reliable fog-based temporal-spatial crowdsourcing for serving the above tasks. In this scenario, the key point is to achieve the best match of the attributes among tasks, fog nodes, and workers. As the bridge of the other two parts, fog nodes determine the orientation of tasks. Therefore, we present a temporal-spatial task allocation (TS-TA) scheme in the fog layer, aiming to make task results more reliable. In this scheme, we build a temporal-spatial attribute learning model based on the user behaviors. Then, we use the users' interest attribute matching model to identify the candidate fog nodes that satisfy the requirements of temporal-spatial tasks. We choose the fog nodes with low spatial correlation that is benefit to defense the attack on the nodes in the intensive area. Meanwhile, we assign the redundancy nodes for intrusion response through replacing the attacked/negative node. Both theoretical and real-topology simulation results validate that the proposed scheme can get better performance in system resource consumption and system robustness compared with other benchmark schemes.

Crowdsourcing

Robustness

10.1109/jiot.2019.2957035

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Citations (13)

Anomaly Intrusion Detection Approach Using Hybrid MLP/CNN Neural Network

Yao Yu Yang Wei Fuxiang Gao Ge Yu

An anomaly intrusion detection approach based on hybrid MLP/CNN (multi-layer perceptron/chaotic neural network) neural network is proposed in this paper. Most anomaly detection approaches using MLP can detect novel real-time attacks, but still has high false alarm rates. Most attacks are composed of a series of anomaly events. These attacks are called time-delayed attacks, which current neural network IDSs (intrusion detection system) cannot identify efficiently. A hybrid MLP/CNN neural network is constructed in order to improve the detection rate of time-delayed attacks. While obtaining a similarly detection rate of real-time attacks as the MLP does, the proposed approach can detect time-delayed attacks efficiently with chaotic neuron. This approach also exhibits a lower false alarm rate when detects novel attacks. The simulation tests are conducted using DARPA 1998 dataset. The experimental results are presented and compared in ROC curves, which can demonstrate that the proposed approach performs exceptionally in terms of both detection rate and false alarm rate

Perceptron

False alarm

False positive rate

Multilayer perceptron

Anomaly (physics)

10.1109/isda.2006.253765

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Citations (43)

A Signature-Behavior-Based P2P Worm Detection Approach

Yao Yu Yong Li Fuxiang Gao Ge Yu

P2P worm based on loopholes spreading in peer-to-peer network is a serious security threat. According to the characteristics of P2P worms, a signature-behavior-based P2P worm detection approach detecting the known P2P worm based on characteristic string matching is proposed. In addition, this method can also detect unknown P2P worms based on behavior. This method is mainly composed of the technology of application identification, the technology of worm characteristic string matching and unknown worm detection technology. A simple and efficient, with lower time complexity of alternative suffix tree algorithm - suffix array algorithm implements matching the characteristic string of worms. Because P2P data have fragment transfer mechanism, the worm characteristic string has the chance to be assigned to different data blocks. Besides, reorganization of characteristic string can detect the worm. Experimental results show that the P2P worm detection method is an effective way to detect P2P worms and restrain its spread.

Signature (topology)

Identification

10.1109/his.2009.192

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Citations (0)

Online intrusion detection mechanism based on model migration in intelligent pumped storage power stations

China Communications (2023)

Yue Zong Yuanlin Luo Yuechao Wu Huang Jiande Bowen Yang

With the continuous integration of new energy into the power grid, various new attacks continue to emerge and the feature distributions are constantly changing during the deployment of intelligent pumped storage power stations. The intrusion detection model trained on the old data is hard to effectively identify new attacks, and it is difficult to update the intrusion detection model in time when lacking data. To solve this issue, by using model-based transfer learning methods, in this paper we propose a convolutional neural network (CNN) based transfer online sequential extreme learning machine (TOS-ELM) scheme to enable the online intrusion detection, which is called CNN-TOSELM in this paper. In our proposed scheme, we use pre-trained CNN to extract the characteristics of the target domain data as input, and then build online learning classifier TOS-ELM to transfer the parameter of the ELM classifier of the source domain. Experimental results show the proposed CNNTOSELM scheme can achieve better detection performance and extremely short model update time for intelligent pumped storage power stations.

Transfer of learning

Extreme Learning Machine

10.23919/jcc.fa.2022-0690.202304

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Citations (1)

The Intelligent Offense and Defense Mechanism of Internet of Vehicles Based on the Differential Game-IP Hopping

IEEE Access (2020)

Yun He Min Zhang Xiaolong Yang Qifu Tyler Sun Jingtang Luo

The Road Side Unit (RSU) is an important part of the Internet of Vehicles (IoV), which collects a large number of user's privacy information and connects vehicles to the Internet. The current RSU is running with static configurations, and the adversary can get enough time to analyze the vulnerability of the RSU and launch attacks, which poses a huge threat to the privacy security of the IoV. Under this asymmetrical condition, the attackers occupy a predominant position, and it is difficult to fully defend. To solve the above asymmetry offense-defense problem, we adopt the moving target defense (MTD) to dynamically change the IP address of the RSU, which increases the difficulty of the attacker's attack. However, due to the unreasonable selection of the RSU's IP hopping frequency, it is difficult for the RSU's IP hopping to exert its defense effect or it may introduce excessive defense overheads. Given the above issue, we propose an intelligent offense and defense mechanism based on a differential game approach, which can adaptively adjust the RSU's IP hopping frequency and maximize its defense benefits. First, based on the offense and defense relationship, we model the RSU's IP hopping frequency intelligent arrangement as a differential game (i.e., IP hopping game) in which the attacker attempts to maximize his potential benefits, and the RSU manages to maximize its defense benefits. On this basis, we calculate a potential Nash equilibrium of the IP hopping game. Finally, simulation results show our proposed mechanism can adaptively adjust the RSU's IP hopping frequency according to the attack frequency and effectively defend attacks. Compared with the mechanisms with a fixed IP hopping frequency, our proposed mechanism can make up for the ineffectiveness of the fixed low-frequency IP hopping defense and avoid the excessive defense overheads of the fixed high-frequency IP hopping defense.

Frequency-hopping spread spectrum

Vulnerability

Differential game

Bayesian game

10.1109/access.2020.3004255

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Citations (10)

Distributed packet-aware routing scheme based on dynamic network coding

China Communications (2016)

Yao Yu Yuhuai Peng Xiaoling Li Jinfeng Gao Xiaozhu Cong

In this paper, we study transmission of packets with time constraints in cooperative 5G wireless networks. As we know, the packets which are transmitted with large delay become useless and have to be dropped. In order to minimize packet dropping probability, we consider multiple transmission methods and integrate packet scheduling with adaptive network coding method selection. Firstly we introduce queue length to obtain the gain of network. Based on this, we present the dynamic coding-aware routing metric, which can increase potential coding opportunities. Moreover, we propose a distributed packet-aware transmission routing scheme based on the above routing metric, which can discover the available paths timely and efficiently. Simulation results show that the proposed method can reduce average packet dropping probability with lower computational complexity.

Linear network coding

Source routing

Equal-cost multi-path routing

Packet forwarding

Performance metric

10.1109/cc.2016.7732009

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Citations (4)

A secure routing scheme based on social network analysis in wireless mesh networks

Science China Information Sciences (2016)

Yao Yu Zhaolong Ning Lei Guo

10.1007/s11432-015-5467-7

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Citations (12)

A P2P-Based Worm in Next Gernation Network

Wei Yang Xiaomeng Shen Guiran Chang Yao Yu

In recent years, many IPv6 networks have been deployed, and the security issues of which arouse more and more public concern. It is commonly believed that IPv6 provides greater security against random-scanning worms by virtue of a very large address space. However, a clever worm can develop a more intelligent scanning strategy to find target hosts. This paper presents a worm which uses the p2p-based hit-list scan strategy to propagate. This worm applied a two-level scanning mechanism to find its targets in IPv6 internet. Based on this idea, we model the behavior of such a worm, and simulation is performed to validate the worm propagation model. Research results demonstrate that this worm can significantly promotes worm propagation in IPv6 internet. We hope that our work can assist in detecting and limiting future worm propagation.

Address space

Limiting

10.1109/icgec.2010.110

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Citations (2)

Research on the Teaching Method for Computer Network Course

International Forum on Computer Science-Technology and Applications (2009)

Fuxiang Gao Lan Yao Yao Yu Xiuli Cui Zhang Dong-mei

Combined with the characteristics of this course and the authors' teaching experience, a teaching method that seeks to innovate in teaching objective, teaching concept, teaching content, and teaching resources is proposed in this paper after deep consideration into the necessity to conduct teaching reform in the era in which computer networks is highly developed.

Course (navigation)

10.1109/ifcsta.2009.223

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Citations (5)