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The Computer Paradigm: Cloud Computing Add in library

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Describe about Cloud Computing?


Cloud Computing

Introduction to Cloud Computing 

The computer paradigm is known as Cloud computing, where the huge systems pool are connected in networks that are public or private, to give dynamically scalable application infrastructure, storage of file and data. With the arrival of this technology, the computation cost, storage content and application and delivery is decreased considerably. Cloud computing is the practical method to experience benefits of cost those are direct and it has potential for data center transformation from the set-up of capital-intensive to the environment that is variable priced. The thought of cloud computing is found on the very fundamental principal of ‘reusability of capabilities of IT. Cloud services examples contain storage of online file, networking sites those are social, applications of online business and webmail. (Meinel, 2009)

2.1.2 Service Architecture 

Essentially, 3 service types can get from the provider of cloud service.

Infrastructure as a service- This service provider tolerates all the servers cost, back-ups, storage and equipment of networking equipment.

Platform as a service- This service provider only gives a solutions stack or a platform for the users. It supports the saving of user’s investment on software and hardware.

Software as a service- This service provider will provide the users the service so that they can use their software, particularly any type of software applications.

Deployment Models 

With the majority of organizations which are pointing on cloud leveraging in order to cut the expenditure from capital and control of the operating costs, there is insistent raise in business for adoption of cloud. There are mainly 4 models for cloud deployment, which are described below with best business scenarios to opt each one. These models got recommendation from the NIST (National Institute of Standards and Technology). (Westphall, 2010)

The Private Cloud

In this model it doesn’t carry much in terms of efficiency of cost: it is comparable to managing, building and its own infrastructure. Thus, it brings the value that is tremendous from the security point of view. Throughout their primary adaptation to cloud, most of the organizations countenance challenges and have concerns that are related to security of data.

The Public Cloud

This deployment model represents hosting of true cloud. In this model, infrastructure and services are given to a variety of clients. The example of public cloud is Google. In this service we can be giving the vendor free of charge or on basis of license policy which is pay-per-user.

For the business requirements this model is the best suitable wherein it is needed to handle spikes of load, SaaS applications hosting, testing the applications and explore interim developing of infrastructure.

The Hybrid Cloud

In this model businesses will get help for taking benefit of data hosting and secured applications on the private cloud, whereas still enjoying benefits of cost by maintaining shared applications and data on public cloud. We can use this model for cloud bursting and handling, which refers to the scenario where the existing cloud infrastructure that is private is not capable to support load spikes and needs the fallback choice to handle the load.

The Community Cloud

In the model of community deployment, the infrastructure of cloud is shared by various organizations with the similar compliance considerations and policy. This supports further to decrease costs as compared to the private cloud, as it will be shared by bigger group.

Several government of state-level departments needing access to the similar data that is relating to local information or population related to the infrastructure, like electrical stations, roads, hospitals, etc., can exploit the cloud community to help data and applications. (Canonico, 2010)


Intrusion Detection System

Introduction to Intrusion Detection System 

Intrusion system of detection plays a significant role in perseverance and security of system for active defense alongside attacks of intruder hostile for any organization of IT and business. IDS execution in computing of cloud needs a approach of virtualization-based, scalable and efficient. In computing of cloud, user application and data is hosted on service providers of cloud has cloud user and remote servers the incomplete control over its resources and data. In few cases, the IDS administration in cloud turns into the cloud provider responsibility.

Service Architecture 

We initiate the CIDSS (Cloud Intrusion Detection System Service) to conquer the significant challenge of maintaining the client protected from attacks of cyber. It is considered based on service model of software for security of any of the Cloud based user.

  • Intrusion Detection Service Agent: This is the light weight agent, single reason equipment - dedicated software or hardware - integrated within the network of user to collect essential data.

  • Cloud Computer Service Component: In this agent it collects messages. It formats all the messages and send them to IDSC as per grouping constrains described for the messages. (Boncheva,  2007)

  • Intrusion Detection Service Component: This is answerable for the intrusion detection. Below are 4 sub components which are playing main rule in the IDSC.

  • Collector: Collector is answerable for reading all data that is received by CCSC, items selected for interest, and forwarding to the suitable analysis engine.

  • Analysis Engine: This is the sophisticated decision and mechanism for pattern matching. It analysis data that came from collector and it matches it to known activity patterns stored in signature database.

  • Event Publisher: This is the standardized interface to give the unified view of outcome report for the users as analysis engine would be an independent procedure which can be executed using IDS. (Mell, 2001)

Deployment Models 

An IDS is collected of numerous components:

  • Security events will generated by Sensors.

  • Monitor events and alerts console and control all the sensors.

  • Central Engine records events that are logged by sensors in the database and use the system of rules to produce alerts from received security events.

Based on objective that are protected or the source of information, IDS can be confidential into Intrusion Detection System of Host-based and Intrusion Detection System of Network-based. (Wespi,  1999)

Host-Based Intrusion Detection System: This was primary type of software of intrusion detection to be considered, with the unique system of target being the computer mainframe where interaction outside was uncommon. In addition the advantages obtained when exploiting this IDS model, there are few drawbacks, which depress deploying IDS Host-based:

  • IDSs Host-based are harder to handle, as data must be managed and configured for each host monitored.

  • Since the sources of data and the engines analysis for IDSs Host-based exist in the host targeted by attacks, the IDS can be disabled and attacked as part of attack.

  • IDSs Host-based use the resources of computing of the hosts they are examining, consequently inflicting the cost performance on monitored systems.

Network-Based Intrusion Detection System: This focus further greatly on network than the precise host. This IDS attacks detects by analyzing and capturing packets of network. (Lockhart, 2007)

IDS implementation in Private Cloud Environment 

Giving security in Environment of Cloud needs more than authentication of user with digital certificates or passwords and its data transmission confidentiality. We can execute Intrusion Detection in 3 ways as clarify below—

Traditional Host based IDS: The primary choice is the traditional detection system of host intrusion (HIDS). HIDS will be used on VM, as well as the hypervisor/host. The HIDS on VM could be monitored, supported and deployed by user. The HIDS on hypervisor should be accountability of provider. (Goscinski, 2011)

Traditional Network based IDS: The second choice is the traditional detection system of network intrusion (NIDS). This kind of deployment is very useful in detecting few attacks on the hypervisor and VMs. It does, though, have numerous drawbacks. The primary one is that it will not support when it comes to attacks within the network of virtual that runs completely within hypervisor. Secondly, it has few inadequate visibilities into host itself.

Hypervisor based IDS: The third choice would be the use of a system of intrusion detection which runs at the layer of hypervisor but is not exactingly the HIDS for hypervisor. One of the promising technologies in this area is the use of VM introspection. This type of IDS allows you to monitor and analyze communications between VMs, between hypervisor and VM and within the hypervisor based virtual network. The advantage of hypervisor-based ID is the availability of information, as it can see basically every. (Grance, 2009)


Computing of Cloud is the paradigm shift in which computing it is moved away from computers that are personal and still the single application server of an  enterprise to the cloud‘ of computers. The cloud is the server pool that is virtualized which can give the unusual resources of computing of their clients. Users of this system need only be concerned with the computing service being asked for.

In this paper we mainly concentrate on Analysis of Intrusion Detection System (IDS) For Cloud Computing. The concept is still evolving, and new methodologies are nowadays considered to belong to cloud computing. The main advantage in using virtualization in IDS is the isolation of the monitored environment, providing an added layer of security and preventing threats having access to user information or to disable protection in the underlying system. (Heikkurinen, 2005)



[1] S. Roschke, F. Cheng, and C. Meinel, 2009, “Intrusion detection in the cloud,” Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing. IEEE, 2009, pp. 729–734.

[2] K. Vieira, A. Schulter, C. Westphall, and C. Westphall, 2010, “Intrusion detection for grid and cloud computing,” It Professional, vol. 12, no. 4, pp. 38–43,.

[3] C. Mazzariello, R. Bifulco, and R. Canonico, 2010, “Integrating a network ids into an open source cloud computing environment”.

[4] V. Marinova-Boncheva,  2007, “A short survey of intrusion detection systems,” vol. 58, pp. 23–30.

[5] R. Bace and P. Mell, 2001, Intrusion detection systems, US Dept. of Commerce, Technology Administration, National Institute of Standards and Technology.

[6] H. Debar, M. Dacier, and A. Wespi, 1999, “Towards a taxonomy of intrusion-detection systems,” Computer Networks, vol. 31, no. 8, pp. 805–822.

[7] A. Lockhart, 2007, Network security hacks, ser. Hacks series.

[8] R. Buyya, J. Broberg, and A. Goscinski, 2011, Cloud Computing Principles and Paradigms, vol. 81.

[9] P. Mell and T. Grance, 2009, “The nist definition of cloud computing,” National Institute of Standards and Technology, vol. 53, no. 6.

[10] S. Subashini and V. Kavitha, 2011, “A survey on security issues in service delivery models of cloud computing,” Journal of Network and Computer Applications, vol. 34, no. 1, pp. 1– 11.

 [11] L. Youseff, M. Butrico, and D. Da Silva, 2008, “Toward a unified ontology of cloud computing,” in Grid Computing Environments Workshop, GCE’08, pp. 1– 10.

[12] F. Gagliardi, B. Jones, F. Grey, M. Bégin, and M. Heikkurinen, 2005, “Building an infrastructure for scientific grid computing: status and goals of the egee project,” Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 363, no. 1833, p. 1729.


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