An Efficient Fuzzy Self-Classifying Clustering based Framework for Cloud Security

Abstract

Though cloud computing has become an attractive technology due to its openness and services, it brings several security hazards towards cloud storage. Since the distributed nature of clouds is achieved through internetworking technologies, clouds suffer from all the vulnerabilities by which networking also suffers. In essence, data stored in clouds are vulnerable to attacks from intruders. But, no single technique can provide efficient intrusion detection. In this paper, we propose fuzzy self-classifying clustering based cloud intrusion detection system which is intelligent to gain knowledge of fuzzy sets and fuzzy rules from data to detect intrusions in a cloud environment. Its efficiency is explained by comparing with other three cloud intrusion detection systems. Using a standard benchmark data from a CIDD (Cloud Intrusion Detection Dataset), experiments are conducted and tested. The results are presented in terms of success rate accuracy.

[Retracted] Construction of Social Security Fund Cloud Audit Platform Based on Fuzzy Data Mining Algorithm

“…At present, the computer audit technology in data acquisition, data conversion, data processing, and data analysis has been a breakthrough function in software in the following aspects: risk assessment, audit plan, paper review, fraud check/prevention and supervision, audit schedule, audit papers, audit report, project management, and problem tracking [5,6]. Domestic research on cloud audit of social security funds started late and is still in the exploratory stage.…”

“…Based on the fuzzy logic operation of neural network, the Sigmoid function is selected, and the membership function is realized by neural network. 6 Complexity…”

II-Learn—A Novel Metric for Measuring the Intelligence Increase and Evolution of Artificial Learning Systems

“…In the following, k denotes the iteration-best agent; L k is the length of the tour performed by the agent k. The iteration-best agent update of pheromones is indicated in Eqs. (7) and (8):…”

“…Intelligent systems have been successfully applied for the solution of a variety of difficult practical problems, such as medical diagnosis [1][2][3][4][5][6], intrusion detection [7], network traffic anomalies detection [8], multisensor battlefield reconnaissance simulation [9], local semantic indexing for resource discovery on overlay networks [10], distributed reasoning for context-aware service [11] and real-time water demand management [12]. Given a problem, its solving difficulty can be considered from different viewpoints, for example, from the human and the computational viewpoint.…”

A Neighbor Propagation Clustering Algorithm for Intrusion Detection

“…It is urgently needed to detect network intrusions and curb these attacks. The essence of intrusion detection is to quickly detect the intrusion behaviors from a large amount of data, and provide the response mechanism of the solutions to these intrusions [1]. To date, many different techniques have been introduced to improve the detection of network intrusions.…”