In recent times, I've encountered a principle known as cloud computing, a model that simplifies user access to data and computing power on a demand basis. The main objective of cloud computing is to accommodate users' growing needs by decreasing dependence on human resources, minimizing expenses, and enhancing the speed of data access. Nevertheless, preserving security and privacy in cloud computing systems pose notable challenges. This issue arises because these systems have a distributed structure, which is susceptible to unsanctioned access - a fundamental problem. In the context of cloud computing, the provision of services on demand makes them targets for common assaults like Denial of Service (DoS) attacks, which include Economic Denial of Sustainability (EDoS) and Distributed Denial of Service (DDoS). These onslaughts can be classified into three categories: bandwidth consumption attacks, specific application attacks, and connection layer attacks. Most of the studies conducted in this arena have concentrated on a singular type of attack, with the concurrent detection of multiple DoS attacks often overlooked. This article proposes a suitable method to identify four types of assaults: HTTP, Database, TCP SYN, and DNS Flood. The aim is to present a universal algorithm that performs effectively in detecting all four attacks instead of using separate algorithms for each one. In this technique, seventeen server parameters like memory usage, CPU usage, and input/output counts are extracted and monitored for changes, identifying the failure point using the CUSUM algorithm to calculate the likelihood of each attack. Subsequently, a fuzzy neural network is employed to determine the occurrence of an attack. When compared to the Snort software, the proposed method's results show a significant improvement in the average detection rate, jumping from 57% to 95%.

翻译：摘要：近期，笔者接触了一种称为云计算的原则，该模型简化了用户按需访问数据与计算资源的模式。云计算的核心目标是通过降低对人力的依赖、减少开支并提升数据访问速度，来满足用户日益增长的需求。然而，在云计算系统中维护安全性与隐私性构成了显著挑战。这一问题源于此类系统的分布式架构，易遭受未经授权的访问——此为根本性缺陷。在云计算场景中，按需提供服务的特点使其成为常见攻击的目标，如拒绝服务攻击（包括经济拒绝可持续性攻击与分布式拒绝服务攻击）。这些攻击可分为三类：带宽消耗型攻击、特定应用型攻击及连接层攻击。现有研究多数聚焦于单一攻击类型，往往忽视了多种DoS攻击的同步检测。本文提出一种适用于识别HTTP泛洪、数据库泛洪、TCP SYN泛洪及DNS泛洪四类攻击的可行方法。目标在于构建一种通用算法，使其能高效检测全部四种攻击，而非为每种攻击分别设计独立算法。该技术通过提取内存使用率、CPU使用率及输入/输出计数等十七项服务器参数，并监测其变化，利用CUSUM算法定位失效点以计算每种攻击的发生概率；继而采用模糊神经网络判定攻击是否发生。与Snort软件相比，所提方法的平均检测率从57%显著提升至95%。