An Efficient Fuzzy-Based Hybrid System to Cloud Intrusion Detection

Abstract Cloud is a collection of resources such as hardware, networks, servers, storage, applications, and interfaces to provide on-demand services to customers. Since access to cloud is through internet, data stored in clouds are vulnerable to attacks from external as well as internal intruders. In order to preserve privacy of the data in cloud, several intrusion detection approaches, authentication techniques, and access control policies are being used. The common intrusion detection systems are predominantly incompetent to be used in cloud environments. In this paper, the usage of type-2 fuzzy neural network based on genetic algorithm is discussed to incorporate intrusion detection techniques into cloud. These systems are intelligent to gain knowledge of fuzzy sets and fuzzy rules from data to detect intrusions in a cloud environment. Using a standard benchmark data from a cloud intrusion detection dataset experiments are done, tested, and compared with other existing approaches in terms of detection rate accuracy, precision, recall, MSE, and scalability.

[1]  Hiroyuki Watanabe,et al.  Application of a fuzzy discrimination analysis for diagnosis of valvular heart disease , 1994, IEEE Trans. Fuzzy Syst..

[2]  Fabrizio Baiardi,et al.  CIDD: A Cloud Intrusion Detection Dataset for Cloud Computing and Masquerade Attacks , 2012, 2012 Ninth International Conference on Information Technology - New Generations.

[3]  T. Martin McGinnity,et al.  Design for Self-Organizing Fuzzy Neural Networks Based on Genetic Algorithms , 2006, IEEE Transactions on Fuzzy Systems.

[4]  Sam Kwong,et al.  Anomaly intrusion detection using multi-objective genetic fuzzy system and agent-based evolutionary computation framework , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

[5]  Sudhir N. Dhage,et al.  Intrusion detection system in cloud computing environment , 2011, ICWET.

[6]  Md. Abu Naser Bikas,et al.  An Implementation of Intrusion Detection System Using Genetic Algorithm , 2012, ArXiv.

[7]  Ching-Chang Wong,et al.  A hybrid clustering and gradient descent approach for fuzzy modeling , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[8]  Hai Jin,et al.  A VMM-based intrusion prevention system in cloud computing environment , 2013, The Journal of Supercomputing.

[9]  Shigeo Abe,et al.  Function approximation based on fuzzy rules extracted from partitioned numerical data , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[10]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[11]  Antonio González Muñoz,et al.  Multi-stage genetic fuzzy systems based on the iterative rule learning approach , 1997 .

[12]  Ajith Abraham,et al.  Intrusion Detection Using Ensemble of Soft Computing Paradigms , 2003 .

[13]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[14]  Vijay Varadharajan,et al.  Intrusion Detection Techniques for Infrastructure as a Service Cloud , 2011, 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing.

[15]  Carla Merkle Westphall,et al.  Intrusion Detection for Grid and Cloud Computing , 2010, IT Professional.

[16]  D.M. Mount,et al.  An Efficient k-Means Clustering Algorithm: Analysis and Implementation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Chia-Feng Juang,et al.  A Self-Evolving Interval Type-2 Fuzzy Neural Network With Online Structure and Parameter Learning , 2008, IEEE Transactions on Fuzzy Systems.

[18]  Sabyasachi Patra,et al.  Machine Learning Approach for Intrusion Detection on Cloud Virtual Machines , 2013 .

[19]  I. Burhan Türksen,et al.  Discrete Interval Type 2 Fuzzy System Models Using Uncertainty in Learning Parameters , 2007, IEEE Transactions on Fuzzy Systems.

[20]  Jerry M. Mendel,et al.  Centroid of a type-2 fuzzy set , 2001, Inf. Sci..

[21]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[22]  Ebrahim H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Hum. Comput. Stud..

[23]  Syuan-Yi Chen,et al.  Robust Control of an LUSM-Based Xhbox-Yhbox-theta Motion Control Stage Using an Adaptive Interval Type-2 Fuzzy Neural Network , 2009, IEEE Trans. Fuzzy Syst..

[24]  Yinghua Lin,et al.  Using fuzzy partitions to create fuzzy systems from input-output data and set the initial weights in a fuzzy neural network , 1997, IEEE Trans. Fuzzy Syst..

[25]  Chien-Hsing Chou,et al.  Short Papers , 2001 .

[26]  Oscar Castillo,et al.  A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks , 2009, Inf. Sci..

[27]  Hussein A. Abbass,et al.  An adaptive genetic-based signature learning system for intrusion detection , 2009, Expert Syst. Appl..

[28]  Hossein Shirazi,et al.  An Intelligent Intrusion Detection System Using Genetic Algorithms and Features Selection , 2010 .

[29]  Dimitar Filev,et al.  Generation of Fuzzy Rules by Mountain Clustering , 1994, J. Intell. Fuzzy Syst..

[30]  Mostaque Md. Morshedur Hassan.  Current Studies On Intrusion Detection System, Genetic Algorithm And Fuzzy Logic , 2013, ArXiv.

[31]  Russell C. Eberhart,et al.  Implementation of evolutionary fuzzy systems , 1999, IEEE Trans. Fuzzy Syst..

[32]  Dijiang Huang,et al.  NICE: Network Intrusion Detection and Countermeasure Selection in Virtual Network Systems , 2013, IEEE Transactions on Dependable and Secure Computing.

[33]  Stephen L. Chiu,et al.  Fuzzy Model Identification Based on Cluster Estimation , 1994, J. Intell. Fuzzy Syst..

[34]  M. Rajalakshmi,et al.  An Intelligent Genetic Algorithm for Mining Classification Rules in Large Datasets , 2013, Comput. Informatics.

[35]  V. Kavitha,et al.  A survey on security issues in service delivery models of cloud computing , 2011, J. Netw. Comput. Appl..

[36]  Germano Lambert-Torres,et al.  A genetic-based neuro-fuzzy approach for modeling and control of dynamical systems , 1998, IEEE Trans. Neural Networks.

[37]  Aboul Ella Hassanien,et al.  Artificial Immune System Inspired Intrusion Detection System Using Genetic Algorithm , 2012, Informatica.