Fog-Assisted SDN Controlled Framework for Enduring Anomaly Detection in an IoT Network
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Ian Welch | Abdul Basit | Saad Qaisar | Saad B. Qaisar | Qaisar Shafi | Abigail Koay | I. Welch | A. Basit | Qaisar Shafi | Abigail M. Y. Koay
[1] Mahmoud Ammar,et al. Journal of Information Security and Applications , 2022 .
[2] Filip De Turck,et al. Network Function Virtualization: State-of-the-Art and Research Challenges , 2015, IEEE Communications Surveys & Tutorials.
[3] Evangelos P. Markatos,et al. An active splitter architecture for intrusion detection and prevention , 2006, IEEE Transactions on Dependable and Secure Computing.
[4] Arputharaj Kannan,et al. Decision tree based light weight intrusion detection using a wrapper approach , 2012, Expert Syst. Appl..
[5] Sotiris Ioannidis,et al. MIDeA: a multi-parallel intrusion detection architecture , 2011, CCS '11.
[6] Mahesh Chandra Govil,et al. A comparative analysis of SVM and its stacking with other classification algorithm for intrusion detection , 2016, 2016 International Conference on Advances in Computing, Communication, & Automation (ICACCA) (Spring).
[7] Bu-Sung Lee,et al. Software defined network based adaptive routing for data replication in Data Centers , 2013, 2013 19th IEEE International Conference on Networks (ICON).
[8] Adam Dunkels,et al. Contiki - a lightweight and flexible operating system for tiny networked sensors , 2004, 29th Annual IEEE International Conference on Local Computer Networks.
[9] Pavle Vuletic,et al. A transparent and scalable anomaly-based DoS detection method , 2016, Comput. Networks.
[10] Jiang Zhu,et al. Fog Computing: A Platform for Internet of Things and Analytics , 2014, Big Data and Internet of Things.
[11] Yuting Zhang,et al. Reduction of quality (RoQ) attacks on Internet end-systems , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..
[12] John C. Grundy,et al. An Analysis of the Cloud Computing Security Problem , 2016, APSEC 2010.
[13] Giovanni Chiola,et al. Slow DoS attacks: definition and categorisation , 2013, Int. J. Trust. Manag. Comput. Commun..
[14] VARUN CHANDOLA,et al. Anomaly detection: A survey , 2009, CSUR.
[15] J. Stephen Judd,et al. Neural network design and the complexity of learning , 1990, Neural network modeling and connectionism.
[16] Laizhong Cui,et al. When big data meets software-defined networking: SDN for big data and big data for SDN , 2016, IEEE Network.
[17] S. Kumar,et al. Smurf-based Distributed Denial of Service (DDoS) Attack Amplification in Internet , 2007, Second International Conference on Internet Monitoring and Protection (ICIMP 2007).
[18] Richard R. Brooks,et al. Deceiving entropy based DoS detection , 2015, Comput. Secur..
[19] Mark Crovella,et al. Mining anomalies using traffic feature distributions , 2005, SIGCOMM '05.
[20] Jugal K. Kalita,et al. A multi-step outlier-based anomaly detection approach to network-wide traffic , 2016, Inf. Sci..
[21] Ailton Akira Shinoda,et al. Using Mininet for emulation and prototyping Software-Defined Networks , 2014, 2014 IEEE Colombian Conference on Communications and Computing (COLCOM).
[22] Andrei V. Gurtov,et al. SDN Based Inter-Technology Load Balancing Leveraged by Flow Admission Control , 2013, 2013 IEEE SDN for Future Networks and Services (SDN4FNS).
[23] Byrav Ramamurthy,et al. Network Innovation using OpenFlow: A Survey , 2014, IEEE Communications Surveys & Tutorials.
[24] Thierry Turletti,et al. A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks , 2014, IEEE Communications Surveys & Tutorials.
[25] Tom H. Luan,et al. Fog Computing: Focusing on Mobile Users at the Edge , 2015, ArXiv.
[26] Khin Mi Mi Aung,et al. A loss-free multipathing solution for data center network using software-defined networking approach , 2012, 2012 Digest APMRC.
[27] Ibrahim Khalil,et al. Design and implementation of a secure cloud-based billing model for smart meters as an Internet of things using homomorphic cryptography , 2017, Future Gener. Comput. Syst..
[28] Gaurang Panchal,et al. Behaviour Analysis of Multilayer Perceptrons with Multiple Hidden Neurons and Hidden Layers , 2011 .
[29] B. B. Gupta,et al. Taxonomy of DoS and DDoS attacks and desirable defense mechanism in a Cloud computing environment , 2017, Neural Computing and Applications.
[30] Munesh Chandra Trivedi,et al. Detection techniques of DDoS attacks: A survey , 2017, 2017 4th IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (UPCON).
[31] Klara Nahrstedt,et al. Safety, Security, and Privacy Threats Posed by Accelerating Trends in the Internet of Things , 2020, ArXiv.
[32] Victor C. M. Leung,et al. FADE: Forwarding Assessment Based Detection of Collaborative Grey Hole Attacks in WMNs , 2013, IEEE Transactions on Wireless Communications.
[33] Lida Xu,et al. The internet of things: a survey , 2014, Information Systems Frontiers.
[34] R. R. Rejimol Robinson,et al. Ranking of machine learning algorithms based on the performance in classifying DDoS attacks , 2015, 2015 IEEE Recent Advances in Intelligent Computational Systems (RAICS).
[35] Narmeen Zakaria Bawany,et al. DDoS Attack Detection and Mitigation Using SDN: Methods, Practices, and Solutions , 2017, Arabian Journal for Science and Engineering.
[36] B. B. Gupta,et al. Security in Internet of Things: issues, challenges, taxonomy, and architecture , 2017, Telecommunication Systems.
[37] Nour Moustafa,et al. UNSW-NB15: a comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set) , 2015, 2015 Military Communications and Information Systems Conference (MilCIS).
[38] Laura Galluccio,et al. SDN-WISE: Design, prototyping and experimentation of a stateful SDN solution for WIreless SEnsor networks , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).
[39] Basil S. Maglaris,et al. Combining OpenFlow and sFlow for an effective and scalable anomaly detection and mitigation mechanism on SDN environments , 2014, Comput. Networks.
[40] Raouf Boutaba,et al. PolicyCop: An Autonomic QoS Policy Enforcement Framework for Software Defined Networks , 2013, 2013 IEEE SDN for Future Networks and Services (SDN4FNS).
[41] Rodrigo Roman,et al. Mobile Edge Computing, Fog et al.: A Survey and Analysis of Security Threats and Challenges , 2016, Future Gener. Comput. Syst..
[42] Jugal K. Kalita,et al. An empirical evaluation of information metrics for low-rate and high-rate DDoS attack detection , 2015, Pattern Recognit. Lett..
[43] Tao Zhang,et al. Fog and IoT: An Overview of Research Opportunities , 2016, IEEE Internet of Things Journal.
[44] Yonghong Chen,et al. DDoS Detection Method Based on Chaos Analysis of Network Traffic Entropy , 2014, IEEE Communications Letters.
[45] Atay Ozgovde,et al. How Can Edge Computing Benefit From Software-Defined Networking: A Survey, Use Cases, and Future Directions , 2017, IEEE Communications Surveys & Tutorials.
[46] Winston Khoon Guan Seah,et al. A new multi classifier system using entropy-based features in DDoS attack detection , 2018, 2018 International Conference on Information Networking (ICOIN).
[47] Hui Li,et al. A Parallel Intrusion Detection System for High-Speed Networks , 2004, ACNS.