CLOUD COMPUTING AND BIG DATA ANALYTICS 1. Divya Priya Dharsini.A 2.Announcia.C 1,2.Computer Science And Engineering SSM InstituteOfEngineering AndTechnology Dindigul 1. divya5dpd@gmail.com 2. announci27@gmail.com Abstract: Cloud Computing and Big Data Analytics is a new concept which provides a good solution for Cloud Security, Load Balancing (down time) and Massive Storage Techniques. In current market the cloud security is a major factor in the cloud computing environment. Extensive cloud security and load balancing shows that the proposed schemes provably high-priority security, high efficient data storage, and is fully considering the load balancing of all servers and the network conditions, thus achieving reasonable resource allocation and scheduling. The term BIG DATA refers to the massive amounts of digital information on abort companies and governments in and externalsurroundings of the world. In this paper we high-light top three big data specific security and privacy challenges are Secure data storage and transaction logs, Real-Time security / compliance monitoring, and End-point input validation / Filtering. KeyWords:cloud security, big data, load balancing. 1. INTRODUCTION: Cloud Computing is simplified terms can be understood as the storing, processing and use of data on remotely located computers accessed over the internet. The world wide web makes information available everywhere and to anyone, cloud computing makes computing power available anywhere and to anyone like the web, cloud computing is a technological development that has been ongoing for some time and will continue to develop. The cloud makes it possible for you can to access your information from anywhere at any time. One requirement is that you need to have an internet connection in order to access the cloud.this means that if you want to look at a specific document you have housed in the cloud, you must first establish an internet connection either through a wireless or wired internet or a mobile broadband connection. The benefit is that you can access that same document from wherever you are with any device that can access the internet. These devices could be a desktop, laptop, tablet, or phone. This can also help your business to function more smoothly because anyone who can connect to the internet and your cloud can work on documents, access software, and store data. Imagine picking up your smartphone and downloading a.pdf document to review instead of having to stop by the office to print it or upload it to your laptop. This is the freedom that the cloud can provide for you or your organization. Cloud computing is a subscription-based service where you can obtain networked storage space and computer resources. One way to think of
cloud computing is to consider your experience with email. Your email client, if it is Yahoo!, Gmail, Hotmail, and so on, takes care of housing all of the hardware and software necessary to support your personal email account. When you want to access your email you open your web browser, go to the email client, and log in. The most important part of the equation is having internet access. Your email is not housed on your physical computer; you access it through an internet connection, and you can access it anywhere. If you are on a trip, at work, or down the street getting coffee, you can check your email as long as you have access to the internet. Your email is different than software installed on your computer, such as a word processing program. When you create a document using word processing software, that document stays on the device you used to make it unless you physically move it. An email client is similar to how cloud computing works. Except instead of accessing just your email, you can choose what information you have access to within the cloud. The term Big Data refers to the massive amounts of digital information companies and governments collect about us our surroundings. Every day, we create 2.5 quintillion bytes of data-so much that 90% of the data in the world today has been created in the last two years alone.our hope is that this paper will spur action in this research and development community to collaboratively increase focus on the leading to greater security and privacy in big data platforms. 1.MODELS AND PROVIDERS The first thing you must look into is the security measures that your cloud provider already has in place. These vary from provider to provider and among the various deployment models of clouds. A. Deployment models in cloud: 1.Public Cloud - A public cloud can be accessed by any subscriber with an internet connection and access to the cloud space. 2. Private Cloud - A private cloud is established for a specific group or organization and limits access to just that group. 3.Community Cloud - A community cloud is shared among two or more organizations that have similar cloud requirements. 4. Hybrid Cloud - A hybrid cloud is essentially a combination of at least two clouds, where the clouds included are a mixture of public, private, or community. example: cloud bursting B. Cloud Providers Software as a Service(SaaS) A SaaS provider gives subscribes access to both resource and applications. SaaS makes it unnecessary for you to have a physical copy of software to install on your devices SaaS also makes it easier to have the some software on all of your devices at once by accessing it on the cloud.example: Salesforce.com Platform as a Service(PaaS) A PaaS system goes a level above the Software as a Service setup. A PaaS provider gives subscribers access to the components that they require to develop and operate applications over the internet. example: Google Apps Infrastructure as a Servise(IaaS) An IaaS agreement, as the name states, deals primarily with computational infrastructure. In an IaaS agreement, the subscriber completely outsources the storage and resources, such as hardware and software, that they need. Example: Amazon s EC2 Essential characteristics On demand self service
Broad network access Resource pooling Rapid elasticity Measured service About Big Data Big Data involves the gathering and analysis of data on a large scale. The data can come from our purchase records, digital photos, social media posts, mobile phone GPS signals etc. Supermarkets use big data to send money-off vouchers and offers for products they know their customers will like. II. ARCHIRECTURE OF CLOUD COMPUTING Mainly focused on data storage security in cloud computing The data centers with high configurations like more powerful processors, high data rate memories and some tera bytes of hard drives are used Even though the cloud infrastructures are much powerful and reliable broad range of internal and external threats for data integrity still exist A. Data Storage and access Rank Index Score Country 1 100 United States 2 91 Canada 3 86 Germany 4 85 Hong Kong 5 82 United Kingdom 6 81 Sweden 7 80 Qatar 8 78 South Africa 9 76 France 10 73 Australia 11 71 Singapore 12 70 Brazil 13 67 Netherlands 14 64 Spain 15 62 Russia 16 61 Poland
17 60 Ireland 18 56 China 19 54 Japan 20 51 India B. Trational Backup vs Next Generation Backup C. BIG DATA The rising importance of big-data computing stems from advances in many differenttechnologies: Sensors: Digital data are being generated by many different sources, including digitalimagers(telescopes, video cameras, MRI machines), chemical and biological sensors(microarrays, environmental monitors), and even the millions of individuals andorganizations generating web pages. Computer networks: Data from the many different sources can be collected into massivedata sets via localized sensor networks, as well as the Internet. Data storage: Advances in magnetic disk technology have dramatically decreased the costof storing data. For example, a one-terabyte disk drive, holding one trillion bytes of data,costs around $100. As a reference, it is estimated that if all of the text in all of the books inthe Library of Congress could be converted to digital form, it would add up to only around20 terabytes. Cluster computer systems: A new form of computer systems, consisting of thousands of"nodes," each having several processors and disks, connected by high-speed local-areanetworks, has become the chosen hardware configuration for data-intensive computingsystems. These clusters provide both the storage capacity for large data sets, and thecomputing power to organize the data, to analyze it, and to respond to queries about thedata from remote users. Compared with traditional highperformance computing (e.g.,supercomputers), where the focus is on maximizing the raw computing power of a system,cluster computers are designed to maximize the reliability and efficiency with which theycan manage and analyze very large data sets. The "trick" is in the software algorithms cluster computer systems are composed of huge numbers of cheap commodityhardware parts, with scalability, reliability, and programmability achieved by new softwareparadigms. Cloud computing facilities: The rise of large data centers and cluster computers hascreated a new business model, where businesses and individuals can rent storage andcomputing capacity, rather than making the large capital investments needed to constructand provision large-scale computer installations. For example, Amazon Web Services(AWS) provides both network-accessible storage priced by the gigabyte-month andcomputing cycles priced by the CPU-hour. Just as few organizations operate their ownpower plants, we
can foresee an era where data storage and computing become utilitiesthat are ubiquitously available. Data analysis algorithms: The enormous volumes of data require automated or semiautomatedanalysis techniques to detect patterns, identify anomalies, and extractknowledge. Again, the "trick" is in the software algorithms - new forms of computation,combining statistical analysis, optimization, and artificial intelligence, are able to constructstatistical models from large collections of data and to infer how the system should respondto new data. For example, Netflix uses machine learning in its recommendation system,predicting the interests of a customer by comparing her movie viewing history to astatistical model generated from the collective viewing habits of millions of other customers. D. Technology and Appliocation Challenge Much of the technology required for big-data computing is developing at a satisfactory ratedue to market forces and technological evolution. For example, disk drive capacity isincreasing and prices are dropping due to the ongoing progress of magnetic storagetechnology and the large economies of scale provided by both personal computers and largedata centers. Other aspects require more focused attention, including: High-speed networking Cluster computer programming Extending the reach of cloud computing Machine learning and other data analysis techniques Widespread deployment Security and privacy SYSTEM ANALYSIS E. Existing System To securely introduce an effective third party auditor (TPA), the following two fundamental requirements have to be met: 1) TPA should be able to efficiently audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user; 2) The third party auditing process should bring in no new vulnerabilities towards user data privacy. F. Proposed System In this paper, we utilize the public key based homomorphic authenticator and uniquely integrate it with random mask technique to achieve a privacy-preserving public auditing system for cloud data storage security while keeping all above requirements in mind. To support efficient handling of multiple auditing tasks, we further explore the technique of bilinear aggregate signature to extend our main result into a multi-user setting, where TPA can perform multiple auditing tasks simultaneously. Extensive security and performance analysis shows the proposed schemes are provably secure and highly efficient. We also show how to extent our main scheme to support batch auditing for TPA upon delegations from multi-users. In this paper, we highlight the top ten big data specific security and privacy challenges. Secure computations in distributed programming frameworks. Security best practices for non-relational data stores. Secure data storage and transaction logs. End-point input validation/filtering. Real- time security /compliance monitoring. Scalable and composable privacypreserving data mining and analytics. Cryptographically enforced access control and secure communication. Granular access control. Granular audits. Data provenance.
G. Cloud management Cloud computing succeeds or fails based on the quality of its systems management. Enterprise Private PaaS requires highly sophisticated automation in order to manage the vast amount of computing power, huge data sets and highly virtualized IT services. label, present them within parentheses. Do not label axes only with units. In the example, write Magnetization (A/m) or Magnetization {A[m(1)]}, not just A/m. Do not label axes with a ratio of quantities and units. For example, write Temperature (K), not Temperature/K. III. CONCLUSION While security emerges as a major concern among those whorespond to cloud computing surveys, the key tounderstanding security in cloud computing is to realize that the technology is not new, or untested. It represents the logical progression to outsourcing of commodity services to many ofthe same trusted IT providers we have already been using for years. Examples of previous cloud computing capabilities include hosted mainframes (more than 40 years), hosted file and mail servers (AT&T, IBM in the early 90 s), and software services like SalesForce.com. Cloud computing, which we define as enabling and delivering computing services (computing power, data storage, network bandwidth and application software) over a network on an as needed basis, has been evolving and continues to evolve. So moving IT elements into the cloud becomes a natural next step. Cloud computing is the logical move for services to take as more established parts of IT are commoditized. Not moving to cloud computing will mean you are paying more than your competitors for the same commodity. Unless your organization is in the business of doing security, it is likely to be less secure than your cloud provider. Work with the provider to determine its attention to security. Compare it to your current levels of actual security to make sure the provider is achieving parity or better levels of security. Remember that the security of the cloud should be equal to the most risky client that the provider has. Risk assessment is the key to cloud security. Require your cloud computing partner to provide you with its risk assessment and how it intends to mitigate any issues found. If the cloud provider does not have a seasoned clientfacing CSO, CISO, or equivalent security person, be very careful. It is a sign that it doesn t take security
seriously enough.schedulemandatorymonthlydiscussions with the cloud provider stop security person. This discussion should flow both ways with no hidden items. The cloud provider should have the ability to map its policy and procedures to any security mandate or security driven contractual obligation you face. Pay attention to your cloud provider s adherence to secure coding practices. If it does not have a good story around the discipline it uses to write code, run away. Cloud security is part of the inevitable progression of IT. It must be embraced by organizations to stay competitive. Companies who approach cloud computing in a mature manner need not be afraid about entering the cloud because of security concerns. Dealing with security in the cloud is no more difficult than addressing it internally. And there are steps you can take that can make cloud security just as effective or even more so as your internal IT.Practical Guide to CloudComputingSecurity. IV. REFERENCES [1] Lewis, Grace. Cloud Computing: Finding the Silver Lining, Not the Silver Bullet. http://www.sei.cmu.edu/newsitems/cloudcompu ting.cfm [2] Jansen, Wayne & Grance, Timothy. Guidelines on Security and Privacy in Public Cloud Computing. National Institute of Standards and Technology, 2011. [3] NIST - Effectively and Securely Using the Cloud Computing Paradigm http://www.govinfosecurity.com/external/reg13 88 [4]. Cloud Security Alliance CSA Guidance v1.0 http://www.cloudsecurityalliance.org/guidance [5] http://www-01.ibm.com/software/data/bigdata. [6] http://www.nytimes.com/2012/03/29/technology /new-us- research-will-aim-at-flood-ofdigital-data.html [7] http://csrc.nist.gov/publications/drafts/800145/d raftsp800-145_cloud-definition.pdf.