Techniques to Detect DoS and DDoS Attacks and an Introduction of a Mobile Agent System to Enhance it in Cloud Computing

Security in cloud computing is the ultimate question that every potential user studies before adopting it. Among the important points that the provider must ensure is that the Cloud will be available anytime the consumer tries to access it. Generally, the Cloud is accessible via the Internet, what makes it subject to a large variety of attacks. Today, the most striking cyber-attacks are the flooding DoS and its variant DDoS. This type of attacks aims to break down the availability of a service to its legitimate clients. In this paper, we underline the most used techniques to stand up against DoS flooading attacks in the Cloud

A survey of intrusion detection techniques in Cloud

Cloud computing provides scalable, virtualized on-demand services to the end users with greater flexibility and lesser infrastructural investment. These services are provided over the Internet using known networking protocols, standards and formats under the supervision of different managements. Existing bugs and vulnerabilities in underlying technologies and legacy protocols tend to open doors for intrusion. This paper, surveys different intrusions affecting availability, confidentiality and integrity of Cloud resources and services. It examines proposals incorporating Intrusion Detection Systems (IDS) in Cloud and discusses various types and techniques of IDS and Intrusion Prevention Systems (IPS), and recommends IDS/IPS positioning in Cloud architecture to achieve desired security in the next generation networks

Packet filter performance monitor (anti-DDOS algorithm for hybrid topologies)

DDoS attacks are increasingly becoming a major problem. According to Arbor Networks, the largest DDoS attack reported by a respondent in 2015 was 500 Gbps. Hacker News stated that the largest DDoS attack as of March 2016 was over 600 Gbps, and the attack targeted the entire BBC website. With this increasing frequency and threat, and the average DDoS attack duration at about 16 hours, we know for certain that DDoS attacks will not be going away anytime soon. Commercial companies are not effectively providing mitigation techniques against these attacks, considering that major corporations face the same challenges. Current security appliances are not strong enough to handle the overwhelming traffic that accompanies current DDoS attacks. There is also a limited research on solutions to mitigate DDoS attacks. Therefore, there is a need for a means of mitigating DDoS attacks in order to minimize downtime. One possible solution is for organizations to implement their own architectures that are meant to mitigate DDoS attacks. In this dissertation, we present and implement an architecture that utilizes an activity monitor to change the states of firewalls based on their performance in a hybrid network. Both firewalls are connected inline. The monitor is mirrored to monitor the firewall states. The monitor reroutes traffic when one of the firewalls become overwhelmed due to a HTTP DDoS flooding attack. The monitor connects to the API of both firewalls. The communication between the rewalls and monitor is encrypted using AES, based on PyCrypto Python implementation. This dissertation is structured in three parts. The first found the weakness of the hardware firewall and determined its threshold based on spike and endurance tests. This was achieved by flooding the hardware firewall with HTTP packets until the firewall became overwhelmed and unresponsive. The second part implements the same test as the first, but targeted towards the virtual firewall. The same parameters, test factors, and determinants were used; however a different load tester was utilized. The final part was the implementation and design of the firewall performance monitor. The main goal of the dissertation is to minimize downtime when network firewalls are overwhelmed as a result of a DDoS attack

A new framework to alleviate DDoS vulnerabilities in cloud computing

In the communication age, the Internet has growing very fast and most industries rely on it. An essential part of Internet, Web applications like online booking, e-banking, online shopping, and e-learning plays a vital role in everyday life. Enhancements have been made in this domain, in which the web servers depend on cloud location for resources. Many organizations around the world change their operations and data storage from local to cloud platforms for many reasons especially the availability factor. Even though cloud computing is considered a renowned technology, it has many challenges, the most important one is security. One of the major issue in the cloud security is Distributed Denial of Service attack (DDoS), which results in serious loss if the attack is successful and left unnoticed. This paper focuses on preventing and detecting DDoS attacks in distributed and cloud environment. A new framework has been suggested to alleviate the DDoS attack and to provide availability of cloud resources to its users. The framework introduces three screening tests VISUALCOM, IMGCOM, and AD-IMGCOM to prevent the attack and two queues with certain constraints to detect the attack. The result of our framework shows an improvement and better outcomes and provides a recovered from attack detection with high availability rate. Also, the performance of the queuing model has been analysed

DCDIDP: A distributed, collaborative, and data-driven intrusion detection and prevention framework for cloud computing environments

With the growing popularity of cloud computing, the exploitation of possible vulnerabilities grows at the same pace; the distributed nature of the cloud makes it an attractive target for potential intruders. Despite security issues delaying its adoption, cloud computing has already become an unstoppable force; thus, security mechanisms to ensure its secure adoption are an immediate need. Here, we focus on intrusion detection and prevention systems (IDPSs) to defend against the intruders. In this paper, we propose a Distributed, Collaborative, and Data-driven Intrusion Detection and Prevention system (DCDIDP). Its goal is to make use of the resources in the cloud and provide a holistic IDPS for all cloud service providers which collaborate with other peers in a distributed manner at different architectural levels to respond to attacks. We present the DCDIDP framework, whose infrastructure level is composed of three logical layers: network, host, and global as well as platform and software levels. Then, we review its components and discuss some existing approaches to be used for the modules in our proposed framework. Furthermore, we discuss developing a comprehensive trust management framework to support the establishment and evolution of trust among different cloud service providers. © 2011 ICST

Intrusion detection and prevention of web service attacks for software as a service:Fuzzy association rules vs fuzzy associative patterns

Cloud computing inherits all the systems, networks as well asWeb Services’ security vulnerabilities, in particular for software as a service (SaaS), where business applications or services are provided over the Cloud as Web Service (WS). Hence, WS-based applications must be protected against loss of integrity, confidentiality and availability when they are deployed over to the Cloud environment. Many existing IDP systems address only attacks mostly occurring at PaaS and IaaS. In this paper, we present our fuzzy association rule-based (FAR) and fuzzy associative pattern-based (FAP) intrusion detection and prevention (IDP) systems in defending against WS attacks at the SaaS level. Our experimental results have validated the capabilities of these two IDP systems in terms of detection of known attacks and prediction of newvariant attacks with accuracy close to 100%. For each transaction transacted over the Cloud platform, detection, prevention or prediction is carried out in less than five seconds. For load and volume testing on the SaaS where the system is under stress (at a work load of 5000 concurrent users submitting normal, suspicious and malicious transactions over a time interval of 300 seconds), the FAR IDP system provides close to 95% service availability to normal transactions. Future work involves determining more quality attributes besides service availability, such as latency, throughput and accountability for a more trustworthy SaaS

Economic Denial of Sustainability Attacks Mitigation in the Cloud

Cyber security is one of the most attention seeking issues with the increasing advancement of technology specifically when the network availability is threaten by attacks such as Denial of Service attacks (DoS), Distributed DoS attacks (DDoS), and Economic Denial of Sustainability (EDoS). The loss of the availability and accessibility of cloud services have greater impacts than those in the traditional enterprises networks. This paper introduces a new technique to mitigate the impacts of attacks which is called Enhanced DDoS-Mitigation System (Enhanced DDoS-MS) that helps in overcoming the determined security gap. The proposed technique is evaluated experimentally and the result shows that the proposed method adds lower delays as a result of the enhanced security. The paper also suggests some future directions to improve the proposed framework