Indian stock market is inching towards new technologies based on big data and they are greener and efficient for the informative decision marking. Decision making and forecasting in the Stock market is largely based on the summary of information from all nook and corners of the globe. In the global village era, big data analytics in the stock market will play crucial role. Till now, sharing of data and information among Indian market players are very less. Due to this, decisions may become gambling. Use of big data analytics in the stock markets are keeping pace and due to it a new school of thought regarding security of analytics data is the major challenge. Indian market has its own socio ' economic challenges like low education rate, poverty, malnutrition etc. Human Index parameters are very low. Because of these challenges, stock market is business of very few players. Traditionally, active intermediaries in the market are working under a close environment where sharing of data for the decision making is less. Indian national exchanges like NSE (National Stock Exchange) and BSE (Bombay Stock Exchange) is shifting towards cloud computing. Efficient market hypothesis advocates reaction in the market of all information. For the stable and efficient market, it's quite compulsory that data must be integrated at the large extent and to be shared among every stack holders. Cloud computing data inculcates many challenges also like ownership, security and authenticity of data. Security of cloud based stock market data is the major concern and need to address properly. Cloud computing is providing many benefits like SaaS, IaaS, Pay as you go etc but cloud computing used in the stock market decision making process is different from other computational areas. In this, Data is not meant as prices of the stock but it is an integrative approach of stock prices, socio ' economic and political factors. Data of the stock market under the cloud computing is open shared between many players. Multi read and multi write simultaneously creates new discussion over distributed computing system. There is a great chance for the data misbehavior that leads to miscalculation and wrong decision. For the benefit of all stack holders and investors, a new security framework is required. This paper deals with the security and authenticity issues of the stock market data under the cloud based technology by user revocation.
Information security is the major concern for the investors of the stock markets and Indian stock market is not an exception. Quality of decision is solely based on the information and its processing capabilities. Integration of big data in the stock market analytics created a vacuum between real individual database security and big data based cloud security model. Decisions are based on integrated information comes from all corners of life. Sharing of information is common in the efficient informative market. In the sharing information environment, security concerns like privacy of data requires more customized information security framework. This paper introduces model of information security which deals with security issues of shared information of stock market with efficient user revocation in the cloud.
Cloud based integration of financial data are facing great challenges on various fronts. Various security models had been introduced for big data security. Implementation of these security models in the cloud based stock market is the major cause of concern. These technologies in the stock market need more customization to fit in the Indian financial market. Our model is divided into five major parts and its all are integrated to form a big data security model for the stock market data. In fig. 02, model of stock market data security with revocation of user in the cloud frame is being proposed. In this figure, heterogeneous and temporal big data is integrated and transfer to the cloud. First part of the model dealt with the Identification of the data. Heterogeneous and unstructured data has been stored by different agencies like RBI, Stock exchanges, news agencies, PR agencies etc. They are storing data as per their needs and demands. Ownership table in the second part of the model is directly mapped with the heterogeneous data stored by different agencies and they are fruitful for the decision makers. Identification and ownership issue of the data is solved by the graphical mapping process between data and ownership table. Cloud server is responsible to maintain ownership table and mapped with the heterogeneous data of interest.
Authorization and Authentication management mechanism can be developed with the password system. Encryption technique in the password will increase and maintain confidentiality of the system. Each database (where data is being stored individually) has its own security mechanism, so that to authorization and authentication of the data, a common platform of passwords has been developed. Common password for the individual database will provide access to the respective database. Protocols and algorithms are needs to be customized according to the framework of this security model. Analytical and statistical tools like SPSS, R etc is required to analyze this integrated data for the forecasting of the stock market. Security breach may occur while fetching data from all nook and corners of the big data. Every user has its own password to access the data and if there is any unauthorized user can try to fetch the data in between then revocation of the user will saved the system. In this user revocation mechanism, each authorized user has its own time stamping as well as authorization code. User can only access data according to the time and identification. In the broader green cloud model we show that ownership can't be transferred and owners are not agreeing to transfer its data. So, mechanism which integrates data by retention of ownership of the data will more applicable. In the third part of the model, we associate third party auditor is one of the mechanisms. In this mechanism, a new neutral third has assigned after the consensus of all the owners and it plays a role of authenticator. It will also maintain confidentiality. In the online payment system, a role of middleware infrastructure providers are playing similar role to connect bank account. In this system, bank account details are kept confidential and transaction happens. In the stock market scenario, big data is introduced and required to take decisions. In the next part of the model, market regulator and other user will be able to customize it further as per its need and used a secure system of cloud security. Now entire data will be launched in the cloud server and Cloud server will be responsible to maintain ownership table, security management protocols, authentication tools, analytical tools and existing cloud technologies like HDFS, Pig, Hive etc. This data can be transferred to the user after validation and verification of the third party auditor's clearance. To maintain security and ownership of the data, key based revocation methodology is come into play. Market regulators and all other users like intermediaries and investors have defined domain to excess data. This can be maintained and revoked by the key based revocation method. Analytical based tool in the cloud will help to generate customized reports for the decision making with the check by revocation. There are more than 83, 000 intermediaries registered with the Indian stock market regulators. One of the major jobs of these intermediaries is to provide analytical data to the investors. All data can be provided in the big data environment with introduction of key based user revocation security model. In this green model, data from all walks of life which has the capability to affect the market can be introduced by integration and provided through the cloud. Security introduction in the cloud model will generate confidence among investors
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