A Review-Botnet Detection and Suppression in Clouds

Internet security problems remain a major challenge with many security concerns such as Internet worms, spam, and phishing attacks. Botnets is well-organized distributed network attacks, consist of a large number of bots that generate huge volumes of spam or launch Distributed Denial of Service (DDoS) attacks on victim hosts. Botnet attacks degrade the status of Internet security. Clouds provide botmaster with an ideal environment of rich computing resources where it can easily deploy or remove C&C server and perform attacks.  It is of vital importance for cloud service providers to detect botnet,  prevent attack,  and trace back to the botmaster.  It also becomes necessary to detect and suppress these bots to protect the clouds. This paper provides the various botnet detection techniques and the comparison of various botnet detection techniques. It also provides the botnet suppression technique in cloud. Keywords: Cloud computing, network security, botnet, botmmaster, botnet detection, botnet suppressio

Autonomic Cloud Computing: Open Challenges and Architectural Elements

As Clouds are complex, large-scale, and heterogeneous distributed systems, management of their resources is a challenging task. They need automated and integrated intelligent strategies for provisioning of resources to offer services that are secure, reliable, and cost-efficient. Hence, effective management of services becomes fundamental in software platforms that constitute the fabric of computing Clouds. In this direction, this paper identifies open issues in autonomic resource provisioning and presents innovative management techniques for supporting SaaS applications hosted on Clouds. We present a conceptual architecture and early results evidencing the benefits of autonomic management of Clouds.Comment: 8 pages, 6 figures, conference keynote pape

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

Shuffling Based Mechanism for DDoS Prevention on Cloud Environment

Cloud Computing has evolved as a new paradigm in which users can use on-demand services, according to their needs. However, security concerns are primary obstacles to a wider adoption of clouds. Newly born concepts that clouds introduced, such as multi-tenancy, resource sharing and outsourcing, create new challenges for the security research. DDoS (Distributed Denial of service) attack is the biggest threat to the cloud since it affects the availability of services. There are a lot of techniques proposed by various researchers to prevent DDoS attacks on a cloud infrastructure. We are using a Shuffling Based approach for preventing DDoS in the cloud environment. This approach is reactive and uses the resource elasticity of the cloud. The aim of this technique is to save the maximum number of benign clients from the attack through shuffling. For assignment of clients to the replica servers, we are using a greedy algorithm. Every time we call this algorithm, we estimate the number of malicious clients using a proposed random function for that round of shuffle. We have shown that we can save a desired percentage of benign clients from the ongoing attacks after some shuffles. To detect the attack on each server, a detector is deployed that uses an entropy-based approach for detecting DDoS. A significant deviation in entropy represents the DDoS attack. We have also performed some tests to select the suitable attributes for entropy-based DDoS detection in different type of DDoS attacks. So in our work we have worked on both detection and prevention of DDoS on cloud infrastructur