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With a large of time series dataset from the Internet of Things in Ambient Intelligence-enabled smart environments, many supervised learning-based anomaly detection methods have been investigated but ignored the correlation among the time series. To address this issue, we present a new idea for anomaly detection based on dynamic graph embedding, in which the dynamic graph comprises the multiple time series and their correlation in each time interval. We propose an entropy for measuring a graph’s information injunction with a correlation matrix to define similarity between graphs. A dynamic graph embedding model based on the graph similarity is proposed to cluster the graphs for anomaly detection. We implement the proposed model in vehicular edge computing for traffic incident detection. The experiments are carried out using traffic data produced by the Simulation of Urban Mobility framework. The experimental findings reveal that the proposed method achieves better results than the baselines by 14.5% and 18.1% on average with respect to F1-score and accuracy, respectively.
Gen Li; Tri-Hai Nguyen; Jason Jung. Traffic Incident Detection Based on Dynamic Graph Embedding in Vehicular Edge Computing. Applied Sciences 2021, 11, 5861 .
AMA StyleGen Li, Tri-Hai Nguyen, Jason Jung. Traffic Incident Detection Based on Dynamic Graph Embedding in Vehicular Edge Computing. Applied Sciences. 2021; 11 (13):5861.
Chicago/Turabian StyleGen Li; Tri-Hai Nguyen; Jason Jung. 2021. "Traffic Incident Detection Based on Dynamic Graph Embedding in Vehicular Edge Computing." Applied Sciences 11, no. 13: 5861.
Traffic congestion is one of the most critical issues in developing sustainable transportation in smart cities. As the Internet of Things evolves, connected vehicle technology has arisen as an essential research topic in smart, sustainable transportation. This study investigates a decentralized green traffic optimization framework by pushing swarm intelligence into connected vehicles to mitigate traffic congestion. We present a dynamic traffic routing method based on ant species’ swarm intelligence for connected vehicles so that they can communicate with each other and their surrounding environment via digital pheromones to perform routing decision-making in a decentralized manner. Traditional pheromones attract other vehicles to move to the optimal path, which will soon be congested if many vehicles travel on that path concurrently. To overcome this limitation, we propose the concept of repelling pheromone, which generates a repulsive force among vehicles so that their travel paths are distributed throughout a road network, resulting in a congestion-free road network. The proposed method is validated in the Simulation of Urban Mobility platform. Simulation findings reveal that the proposed method outperforms baseline methods in mitigating traffic congestion, reducing average fuel consumption and emissions by 13–19% and the average trip duration by 19–28%.
Tri-Hai Nguyen; Jason J. Jung. Swarm intelligence-based green optimization framework for sustainable transportation. Sustainable Cities and Society 2021, 71, 102947 .
AMA StyleTri-Hai Nguyen, Jason J. Jung. Swarm intelligence-based green optimization framework for sustainable transportation. Sustainable Cities and Society. 2021; 71 ():102947.
Chicago/Turabian StyleTri-Hai Nguyen; Jason J. Jung. 2021. "Swarm intelligence-based green optimization framework for sustainable transportation." Sustainable Cities and Society 71, no. : 102947.
The increasing number of vehicles needs effective routing schemes to be introduced, which is a challenge due to the uncertainty of the traffic network. This paper, inspired by the ant colony optimization algorithm, proposes an inverse pheromone-based routing method to solve the dynamic traffic routing problem in the connected vehicle environment. Traditionally, the pheromone is used to attract other ants; however, the inverse pheromone represents the negative effect. Each connected vehicle is modeled as an ant that deposits its pheromones on the road segments. The more pheromone deposited on a road segment, the more congestion is in that road segment. The connected vehicles should then avoid the high congestion path and select a less congested road segment for travel. The proposed method is implemented in a decentralized traffic management system in which the connected vehicles share information to support route choice decision-making process. Results from simulations performed with a realistic map in the Simulation of Urban Mobility demonstrate that the proposed method outperforms the conventional pheromone-based routing method by reducing the average trip duration by 13% on average.
Tri-Hai Nguyen; Jason J. Jung. Inverse pheromone-based decentralized route guidance for connected vehicles. Proceedings of the 36th Annual ACM Symposium on Applied Computing 2021, 1 .
AMA StyleTri-Hai Nguyen, Jason J. Jung. Inverse pheromone-based decentralized route guidance for connected vehicles. Proceedings of the 36th Annual ACM Symposium on Applied Computing. 2021; ():1.
Chicago/Turabian StyleTri-Hai Nguyen; Jason J. Jung. 2021. "Inverse pheromone-based decentralized route guidance for connected vehicles." Proceedings of the 36th Annual ACM Symposium on Applied Computing , no. : 1.
Collaborative filtering recommendation systems, which analyze sets of user ratings, have been applied to various domains and have resulted in considerable improvements in the traditional recommendation system. However, they still have problems with data sparsity and cold‐start of the user ratings. To solve these problems, we present a hybrid recommendation approach by combining collaborative filtering methods and word embedding‐based content analysis. This study focuses on the movie domain, and therefore, the contents of the items are represented as a set of features such as titles, genres, directors, actors, and plots. The main aim of this paper is to understand the content of the movie plot using a word embedding to improve the measurement of similarity of each plot content to other plot content (called plot embedding). To enhance the accuracy in measuring the similarity between movies, we also consider other features such as titles, genres, directors, and actors extracted from movies. In the experiments, the movie dataset was collected by our crowdsourcing platform, which is the OMS platform. The experimental findings indicate that the proposed approach can enhance the efficiency of applied collaborative filtering recommendation systems.
Luong Vuong Nguyen; Tri‐Hai Nguyen; Jason J. Jung; David Camacho. Extending collaborative filtering recommendation using word embedding: A hybrid approach. Concurrency and Computation: Practice and Experience 2021, e6232 .
AMA StyleLuong Vuong Nguyen, Tri‐Hai Nguyen, Jason J. Jung, David Camacho. Extending collaborative filtering recommendation using word embedding: A hybrid approach. Concurrency and Computation: Practice and Experience. 2021; ():e6232.
Chicago/Turabian StyleLuong Vuong Nguyen; Tri‐Hai Nguyen; Jason J. Jung; David Camacho. 2021. "Extending collaborative filtering recommendation using word embedding: A hybrid approach." Concurrency and Computation: Practice and Experience , no. : e6232.
Sustainable energy development consists of design, planning, and control optimization problems that are typically complex and computationally challenging for traditional optimization approaches. However, with developments in artificial intelligence, bio-inspired algorithms mimicking the concepts of biological evolution in nature and collective behaviors in societies of agents have recently become popular and shown potential success for these issues. Therefore, we investigate the latest research on bio-inspired approaches for smart energy management systems in smart homes, smart buildings, and smart grids in this paper. In particular, we give an overview of the well-known and emerging bio-inspired algorithms, including evolutionary-based and swarm-based optimization methods. Then, state-of-the-art studies using bio-inspired techniques for smart energy management systems are presented. Lastly, open challenges and future directions are also addressed to improve research in this field.
Tri-Hai Nguyen; Luong Nguyen; Jason Jung; Israel Agbehadji; Samuel Frimpong; Richard Millham. Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges. Sustainability 2020, 12, 8495 .
AMA StyleTri-Hai Nguyen, Luong Nguyen, Jason Jung, Israel Agbehadji, Samuel Frimpong, Richard Millham. Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges. Sustainability. 2020; 12 (20):8495.
Chicago/Turabian StyleTri-Hai Nguyen; Luong Nguyen; Jason Jung; Israel Agbehadji; Samuel Frimpong; Richard Millham. 2020. "Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges." Sustainability 12, no. 20: 8495.
The lack of sufficient ratings will reduce effectively modeling user reference and finding trustworthy similar users in collaborative filtering (CF)-based recommendation systems, also known as a cold-start problem. To solve this problem and improve the efficiency of recommendation systems, we propose a new content-based CF approach based on item similarity. We apply the model in the movie domain and extract features such as genres, directors, actors, and plots of the movies. We use the Jaccard coefficient index to covert the extracted features such as genres, directors, actors to the vectors while the plot feature is converted to the semantic vectors. Then, the similarity of the movies is calculated by soft cosine measure based on vectorized features. We apply the word embedding model (i.e., Word2Vec) for representing the plots feature as semantic vectors instead of using traditional models such as a binary bag of words and a TF-IDF vector space. Experiment results show the superiority of the proposed system in terms of accuracy, precision, recall, and F1 scores in cold-start conditions compared to the baseline systems.
Luong Vuong Nguyen; Tri-Hai Nguyen; Jason J. Jung. Content-Based Collaborative Filtering using Word Embedding. Proceedings of the International Conference on Research in Adaptive and Convergent Systems 2020, 1 .
AMA StyleLuong Vuong Nguyen, Tri-Hai Nguyen, Jason J. Jung. Content-Based Collaborative Filtering using Word Embedding. Proceedings of the International Conference on Research in Adaptive and Convergent Systems. 2020; ():1.
Chicago/Turabian StyleLuong Vuong Nguyen; Tri-Hai Nguyen; Jason J. Jung. 2020. "Content-Based Collaborative Filtering using Word Embedding." Proceedings of the International Conference on Research in Adaptive and Convergent Systems , no. : 1.
In this study, we focus on dynamic traffic routing of connected vehicles with various origins and destinations; this is referred to as a multi-source multi-destination traffic routing problem. Ant colony optimization (ACO)-based routing method, together with the idea of coloring ants, is proposed to solve the defined problem in a distributed manner. Using the concept of coloring ants, traffic flows of connected vehicles to different destinations can be distinguished. To evaluate the performance of the proposed method, we perform simulations on the multi-agent NetLogo platform. The simulation results indicate that the ACO-based routing method outperforms the shortest path-based routing method (i.e., given the same simulation period, the average travel time decreases by 8% on average and by 11% in the best case, whereas the total number of arrived vehicles increases by 13% on average and by 23% in the best case).
Tri-Hai Nguyen; Jason J. Jung. Multiple ACO-based method for solving dynamic MSMD traffic routing problem in connected vehicles. Neural Computing and Applications 2020, 33, 6405 -6414.
AMA StyleTri-Hai Nguyen, Jason J. Jung. Multiple ACO-based method for solving dynamic MSMD traffic routing problem in connected vehicles. Neural Computing and Applications. 2020; 33 (12):6405-6414.
Chicago/Turabian StyleTri-Hai Nguyen; Jason J. Jung. 2020. "Multiple ACO-based method for solving dynamic MSMD traffic routing problem in connected vehicles." Neural Computing and Applications 33, no. 12: 6405-6414.
Recently, the advance of the Internet of Things (IoT) and wireless communication technology, specifically Vehicles-to-Everything (V2X), makes a huge contribution to road transportation. The fully connected and autonomous system of road transportation can be basically made in practice by integrating V2X with a current autonomous vehicle. In this paper, we focus on dynamic traffic routing for IoT-based connected vehicles. First, we define the problem of identifying the best paths for all vehicles with different sources and different destinations, or multi-source multi-destination (MSMD) traffic flows. Then, Ant Colony Optimization (ACO)-based approach with coloring ants concept is proposed to solve the problem in a decentralized and self decision-making manner. The simulation is carried out on the NetLogo platform with a multi-intersection scenario. The simulation results show that the ACO-based routing approach outperforms the non-ACO-based approach in terms of average traveling time and the number of vehicles passing metrics.
Tri-Hai Nguyen; Jason J. Jung. ACO-based Approach on Dynamic MSMD Routing in IoV Environment. 2020 16th International Conference on Intelligent Environments (IE) 2020, 68 -73.
AMA StyleTri-Hai Nguyen, Jason J. Jung. ACO-based Approach on Dynamic MSMD Routing in IoV Environment. 2020 16th International Conference on Intelligent Environments (IE). 2020; ():68-73.
Chicago/Turabian StyleTri-Hai Nguyen; Jason J. Jung. 2020. "ACO-based Approach on Dynamic MSMD Routing in IoV Environment." 2020 16th International Conference on Intelligent Environments (IE) , no. : 68-73.
네트워크 기능 가상화 (NFV)는 가상화 기술을 통해 네트워크 서비스의 동적 프로비저닝을 용이하게하는 패러다임이다. 네트워크 서비스는 가상화 된 범용 하드웨어, 즉 가상 네트워크 기능 (VNF) 위에 소프트웨어 구성 요소로 구현되는 일련의 기능을 연결함으로써 구현할 수 있다. VNF 배치는 사용 가능한 컴퓨팅 자원 및 네트워크 링크의 현재 특성에서 서비스 요청에 따라 VNF 체인에 대한 최적 위치 집합을 선택하는 문제이다. 기존 VNF 배치 문제를 다룬 연구들은 자체 모델 및 솔루션을 제공하지만, 일반화된 VNF 배치 최적화 시뮬레이터는 아직 다루어지지 않았다. 따라서 본 논문에서는 입력 및 출력을 일관되게 정의하는 VNF 배치 시뮬레이터를 제안한다. 본 시뮬레이터는 개발자와 연구원이 VNF 배치 알고리즘 개발에 효과적으로 활용할 수 있다.
Tri-Hai Nguyen; Myungsik Yoo. A VNF Placement Optimization Framework for Network Function Virtualization. The Journal of Korean Institute of Communications and Information Sciences 2019, 44, 1956 -1960.
AMA StyleTri-Hai Nguyen, Myungsik Yoo. A VNF Placement Optimization Framework for Network Function Virtualization. The Journal of Korean Institute of Communications and Information Sciences. 2019; 44 (10):1956-1960.
Chicago/Turabian StyleTri-Hai Nguyen; Myungsik Yoo. 2019. "A VNF Placement Optimization Framework for Network Function Virtualization." The Journal of Korean Institute of Communications and Information Sciences 44, no. 10: 1956-1960.
Network Function Virtualization (NFV) can reduce significantly capital and operating costs for communication service providers by shifting network functions from dedicated hardware to Virtual Network Functions (VNFs). VNF placement problem is one of the challenges in NFV. Current studies are limited in the practical applicability. To tackle this problem, we study the optimal VNF placement in NFV with symmetrical, two-way traffic and reusable VNF instances. The problem is formulated as a Mixed-Integer Linear Programming (MILP) model. Then, a simulation is conducted using a real-world network service to show the performance of the proposed model.
Tri-Hai Nguyen; Jaejin Lee; Myungsik Yoo. A Practical Model for Optimal Placement of Virtual Network Functions. 2019 International Conference on Information Networking (ICOIN) 2019, 239 -241.
AMA StyleTri-Hai Nguyen, Jaejin Lee, Myungsik Yoo. A Practical Model for Optimal Placement of Virtual Network Functions. 2019 International Conference on Information Networking (ICOIN). 2019; ():239-241.
Chicago/Turabian StyleTri-Hai Nguyen; Jaejin Lee; Myungsik Yoo. 2019. "A Practical Model for Optimal Placement of Virtual Network Functions." 2019 International Conference on Information Networking (ICOIN) , no. : 239-241.
Tri-Hai Nguyen; Myungsik Yoo. Lightweight Simulator for NFV Management and Orchestration. The Journal of Korean Institute of Communications and Information Sciences 2018, 43, 1676 -1681.
AMA StyleTri-Hai Nguyen, Myungsik Yoo. Lightweight Simulator for NFV Management and Orchestration. The Journal of Korean Institute of Communications and Information Sciences. 2018; 43 (10):1676-1681.
Chicago/Turabian StyleTri-Hai Nguyen; Myungsik Yoo. 2018. "Lightweight Simulator for NFV Management and Orchestration." The Journal of Korean Institute of Communications and Information Sciences 43, no. 10: 1676-1681.
Network Function Virtualization (NFV) is a concept that is shifting network functions from dedicated hardware to software known as Virtual Network Functions (VNFs) running on commodity hardware. The deployment and operational behavior requirements of VNF are described by a deployment template called VNF Descriptor (VNFD). In order to deploy a new VNF, operators and VNF vendors have to manually prepare a VNFD template which may have typos and unexpected errors. To overcome this tedious and error-prone task, we propose a VNFD generator web application to automatically create a VNFD template that the operators and VNF vendors can quickly validate and deploy the VNFs. The experiment is conducted in Tacker, which is an open-source NFV management and orchestration service in the OpenStack cloud platform, to demonstrate the feasibility of the proposed web application.
Tri-Hai Nguyen; Myungsik Yoo. A VNF Descriptor Generator for Tacker-based NFV Management and Orchestration. 2018 International Conference on Information and Communication Technology Convergence (ICTC) 2018, 260 -262.
AMA StyleTri-Hai Nguyen, Myungsik Yoo. A VNF Descriptor Generator for Tacker-based NFV Management and Orchestration. 2018 International Conference on Information and Communication Technology Convergence (ICTC). 2018; ():260-262.
Chicago/Turabian StyleTri-Hai Nguyen; Myungsik Yoo. 2018. "A VNF Descriptor Generator for Tacker-based NFV Management and Orchestration." 2018 International Conference on Information and Communication Technology Convergence (ICTC) , no. : 260-262.
Tri-Hai Nguyen; Myungsik Yoo. Workflow Policy-Based VNF Monitoring Model in Tacker-Based NFV System. The Journal of Korean Institute of Communications and Information Sciences 2018, 43, 1483 -1488.
AMA StyleTri-Hai Nguyen, Myungsik Yoo. Workflow Policy-Based VNF Monitoring Model in Tacker-Based NFV System. The Journal of Korean Institute of Communications and Information Sciences. 2018; 43 (9):1483-1488.
Chicago/Turabian StyleTri-Hai Nguyen; Myungsik Yoo. 2018. "Workflow Policy-Based VNF Monitoring Model in Tacker-Based NFV System." The Journal of Korean Institute of Communications and Information Sciences 43, no. 9: 1483-1488.
Network Function Virtualization (NFV) uses the IT virtualization technologies to decouple network functions from proprietary hardware so that they can be run in software on commercial off-the-shelf hardware platform. By leveraging NFV, communications service providers can provide Virtual Customer Premises Equipment (vCPE) solutions, which reduce the number and cost of physical hardware appliances required at the customer premises for hosting connectivity and other value-added features. In this paper, we discuss three deployment approaches in the vCPE platform, i.e., centralized vCPE, distributed vCPE, and hybrid vCPE. In addition, an experiment is conducted to measure the resource usage in different vCPE deployment models.
Tri-Hai Nguyen; Trinh Nguyen; Myungsik Yoo. Analysis of deployment approaches for virtual customer premises equipment. 2018 International Conference on Information Networking (ICOIN) 2018, 289 -291.
AMA StyleTri-Hai Nguyen, Trinh Nguyen, Myungsik Yoo. Analysis of deployment approaches for virtual customer premises equipment. 2018 International Conference on Information Networking (ICOIN). 2018; ():289-291.
Chicago/Turabian StyleTri-Hai Nguyen; Trinh Nguyen; Myungsik Yoo. 2018. "Analysis of deployment approaches for virtual customer premises equipment." 2018 International Conference on Information Networking (ICOIN) , no. : 289-291.
With the rapid growth of Internet of Things technologies, the management and control of Internet of Things networks face remarkable challenges. As such, software-defined networking, which decouples the control layer from data layer, results in various advantages. An association of software-defined networking and Internet of Things, which is referred to as software-defined Internet of Things, provides a robust platform to improve the management and control abilities of Internet of Things networks. However, these benefits have resulted in an increase in the number of malicious attacks on logically centralized controllers. For that reason, we have performed a specific vulnerability analysis in the link service, where the controller learns network topology through discovering every link between switches. In addition, we demonstrate link spoofing attacks on the link service, and discuss a hybrid countermeasure to address this security problem.
Tri-Hai Nguyen; Myungsik Yoo. A hybrid prevention method for eavesdropping attack by link spoofing in software-defined Internet of Things controllers. International Journal of Distributed Sensor Networks 2017, 13, 1 .
AMA StyleTri-Hai Nguyen, Myungsik Yoo. A hybrid prevention method for eavesdropping attack by link spoofing in software-defined Internet of Things controllers. International Journal of Distributed Sensor Networks. 2017; 13 (11):1.
Chicago/Turabian StyleTri-Hai Nguyen; Myungsik Yoo. 2017. "A hybrid prevention method for eavesdropping attack by link spoofing in software-defined Internet of Things controllers." International Journal of Distributed Sensor Networks 13, no. 11: 1.
In recent years, the number of mobile devices is increasing rapidly. Meanwhile, the amount of malicious software is rising almost exponentially, alongside the diversity and complexity of malware. The flexibility of Software-Defined Networking (SDN) provides an opportunity to develop a malware detection model in more efficient and flexible manner. In this paper, we propose a network behavior-based malware detection system for mobile devices in SDN which is composed of three algorithms including IP Blacklist, Connection Success Ratio, Connection Rate algorithms. The experiment demonstrates that the proposed system is feasible and effective.
Tri-Hai Nguyen; Myungsik Yoo. A behavior-based mobile malware detection model in software-defined networking. 2017 International Conference on Information Science and Communications Technologies (ICISCT) 2017, 1 -3.
AMA StyleTri-Hai Nguyen, Myungsik Yoo. A behavior-based mobile malware detection model in software-defined networking. 2017 International Conference on Information Science and Communications Technologies (ICISCT). 2017; ():1-3.
Chicago/Turabian StyleTri-Hai Nguyen; Myungsik Yoo. 2017. "A behavior-based mobile malware detection model in software-defined networking." 2017 International Conference on Information Science and Communications Technologies (ICISCT) , no. : 1-3.
The Internet of Things is a network of physical devices consisting of embedded systems and sensors that interact with each other and connect to the Internet, and the quick growth of the Internet of Things industry has resulted in complex inter-networking on the Internet. Software-defined networking is a recent advance in computer networking that redefines the network paradigm for future communication, and the advantages of software-defined networking can also be applied to Internet of Things, namely as software-defined Internet of Things. In this article, we investigate the vulnerability of the software-defined Internet of Things platform device manager, which monitors the connected Internet of Things devices in the network. Although being the one that performs one of the most crucial services, the device managers in current primary controllers have a big security issue as they do not include any device verification, authentication, or authorization routines. Consequently, the device manager accepts all the changes of device information made by other devices, which leads to potential attacks as demonstrated in this article. To address this problem, a comprehensive and lightweight countermeasure is proposed and its effectiveness is verified through experiments.
Tri-Hai Nguyen; Myungsik Yoo. Analysis of attacks on device manager in software-defined Internet of Things. International Journal of Distributed Sensor Networks 2017, 13, 1 .
AMA StyleTri-Hai Nguyen, Myungsik Yoo. Analysis of attacks on device manager in software-defined Internet of Things. International Journal of Distributed Sensor Networks. 2017; 13 (8):1.
Chicago/Turabian StyleTri-Hai Nguyen; Myungsik Yoo. 2017. "Analysis of attacks on device manager in software-defined Internet of Things." International Journal of Distributed Sensor Networks 13, no. 8: 1.
Influence maximization is the problem of finding a subset of nodes that maximizes the spread of information in a social network. Many solutions have been developed, including greedy and heuristics based algorithms. While the former is very time consuming that might be impractical in many cases, the later is feasible in terms of computational time, but its influence spread is not guaranteed because of limitations in the algorithm. In this study, we propose a new heuristic algorithm which considers the propagation probabilities of nodes in the network individually and takes into account the effect of multi-hop neighbors, thus, it can achieve higher influence spread. A realistic network model with non-uniform propagation probabilities between nodes is assumed in our algorithm. We also examine the optimal number of hops of neighbors to be considered in the algorithm. Experiments using real-world social networks showed that our proposed method outperformed the previous heuristic-based approaches.
Duy-Linh Nguyen; Tri-Hai Nguyen; Trong-Hop Do; Myungsik Yoo. Probability-Based Multi-hop Diffusion Method for Influence Maximization in Social Networks. Wireless Personal Communications 2017, 93, 903 -916.
AMA StyleDuy-Linh Nguyen, Tri-Hai Nguyen, Trong-Hop Do, Myungsik Yoo. Probability-Based Multi-hop Diffusion Method for Influence Maximization in Social Networks. Wireless Personal Communications. 2017; 93 (4):903-916.
Chicago/Turabian StyleDuy-Linh Nguyen; Tri-Hai Nguyen; Trong-Hop Do; Myungsik Yoo. 2017. "Probability-Based Multi-hop Diffusion Method for Influence Maximization in Social Networks." Wireless Personal Communications 93, no. 4: 903-916.
Software-Defined Networking (SDN) allows scalable and flexible network management without requiring expensive hardware changes. However, this technology is relatively new and creates novel security risks. In this paper, we investigate the vulnerability of link discovery service in SDN controller, which is a critical service provided by the control layer for the proper functioning of applications and network services. We also discuss the potential attacks on link discovery service, which are verified via experiments.
Tri-Hai Nguyen; Myungsik Yoo. Analysis of link discovery service attacks in SDN controller. 2017 International Conference on Information Networking (ICOIN) 2017, 259 -261.
AMA StyleTri-Hai Nguyen, Myungsik Yoo. Analysis of link discovery service attacks in SDN controller. 2017 International Conference on Information Networking (ICOIN). 2017; ():259-261.
Chicago/Turabian StyleTri-Hai Nguyen; Myungsik Yoo. 2017. "Analysis of link discovery service attacks in SDN controller." 2017 International Conference on Information Networking (ICOIN) , no. : 259-261.
Software-Defined Networking (SDN) is a novel paradigm in networking that changed the way the conventional networks are built and managed. The idea of SDN is based upon the dissociation of the control plane from networking devices to better optimize each. The control of the whole network becomes the responsibility of the controller. In an SDN network, locations of all hosts can be monitored with the host tracking service (HTS) in SDN controller. However, HTS may not support host authentication mechanisms. In this paper, we reveal that an attacker could attack this vulnerability of HTS, which could lead to host impersonation attack, man-in-the-middle attack, and denial-of-service attack. In addition, we also discuss and propose the possible countermeasure for this issue.
Tri-Hai Nguyen; Myungsik Yoo. Attacks on host tracker in SDN controller: Investigation and prevention. 2016 International Conference on Information and Communication Technology Convergence (ICTC) 2016, 610 -612.
AMA StyleTri-Hai Nguyen, Myungsik Yoo. Attacks on host tracker in SDN controller: Investigation and prevention. 2016 International Conference on Information and Communication Technology Convergence (ICTC). 2016; ():610-612.
Chicago/Turabian StyleTri-Hai Nguyen; Myungsik Yoo. 2016. "Attacks on host tracker in SDN controller: Investigation and prevention." 2016 International Conference on Information and Communication Technology Convergence (ICTC) , no. : 610-612.