Techniques For Domain Discovery Over Hidden Databases

Microsoft Access hides important database technology to help beginner users create and work on small database applications and their underlying databases and to simplify the user’s experience when using

Course Description This course covers database concepts. Topics include data analysis, the principal data models with emphasis on the relational model, entity-relationship diagrams, database design, normalization, and database administration. Policies Faculty and students will be held responsible for understanding and adhering to all policies contained within the following two documents: • • University policies: You must be logged into the student website to view this document. Instructor policies: This

As we’ve moved further into the twenty-first century, our world and society has been immersed into the digital world. With this digitization of our culture we have created a new resource, data. Data has become king in the Age of Intelligence, it fuels most of what technology companies use to make money. Companies like Google, Facebook, Amazon, ect. have leveraged their vast amounts of data generated by the millions of internet users to better advertise and attract more users. Surprisingly most of this data collection is created and aggregated unbeknownst to the users. This is where the problems start to show themselves. When users are generating 2.5 quintillion bytes of data each day, as estimated by IBM,(https://www-01.ibm.com/software/data/bigdata/what-is-big-data.html),

Data mining is the process of discovering and interpreting meaningful, previously hidden patterns in data. Extensively used in financial services, customer relationship management and retail, data mining helps alleviate data overload, by extracting value from volume. Furthermore, the focus of data mining is on the process, not a particular technique, used to make reasonably accurate predictions. “The recent emergence of data mining technology to analyze vast amounts of data opens new threats to information privacy”. (Brankovic & Estivill-Castro 1999, Clifton & Marks 1996, Estivill-Castro, Brankovik & Dowe 1999) There are many pieces of academia some that will be identified in this paper that identify such privacy risks and the ethical and legal ramifications that acquiesce

Connolly and Carolyn (2004) define a database as a structureordesign that consists of theclient’s data as well as metadata. It is also a persistent, logicallycoherentrepository of inherentlymeaningful data that is relevant to someaspects of therealworld. The database consists of data organized in a systematicway, anditallowseasy retrieval of information, analysis, updating andoutput of data. Thatdata can be in theform of graphics, scripts, reports, text, tables, andsoon. Most of thecomputerapplications are databases at their core. Manycompaniesusuallyhave a lot of data, andsotheyhavebig databases that can handlethatlargeamount of data. It is wherenothe database administratorcomes into playtopensurepropermanagement of the database sothatthe organizational data is safe from anyintrudersor data corruption (Jones, 2014). The database is whatcontrolsthedata of theentireorganization, andany tampering of the databases can culminate to the stoppage of businessoperations.

The storage integrity and query integrity of a database are two of the most important functions that providers can offer, in addition to complex encryption and firewalls to provide additional security in the virtual environment. Each provider can offer a streamlined plan to implement a database solution along

A busy executive with a data integrity mind set has to control information coming in, through its processing phases and ending in the customers hands as a usable product. Free from any modification and as accurate as it can possibly be, If they get the information at all. (DOS in mind). Information

A key problem that arises in any mass collection of data is that of confidentiality. The need for privacy preserving is sometimes due to law [3] or can be motivated by business interests. However, sharing of data can be beneficial to others and give mutual gain. A key utility of large databases today is research, whether it is scientific or economic and market oriented. For example, medical field has much to gain by pooling data for research. Despite the potential gain, this is often not possible due to the confidentiality issues which arise. So the privacy of the one’s confidential data should be preserve from other corporate or public sectors.

RDBMSs are a common choice for the storage of information in new databases used for financial records, manufacturing and logistical information, personnel data, and other applications since the 1980s. Relational databases have often replaced legacy hierarchical databases and network databases because they are easier to understand and use. However, relational databases have received unsuccessful challenge attempts

An organisation(data owner) which lacks the expertise or computational resources required for data mining can outsource its data mining tasks to third party service provider(server).But there are various security issues associated with this kind of outsourcing because the server can misuse the data provide by the organisation directly or by extracting frequents patterns from it. However, both data and the association

This paper will discuss databases, forms and reports. Why has the use of databases increased dramatically? What factors should be considered when designing a database and why? How would you go about designing forms and reports from scratch? In conclusion, a summation will be given along with closing thoughts.

Abstract—Fast Distributed Mining (FDM) which generates a small number of candidate set and substantially reduce the number of messages to be passed at mining association rules. Distributed data mining offers a way by data can be shared without compromising privacy. A protocol for secure mining of association rules in horizontally distributed databases. The main ingredients in the existing protocol are two novel secure multi-party algorithms-one that computes the union of private subsets that each of the interacting players hold and another that tests the inclusion of an element held by one player in a subset held by another. In order to improve the performance of the system it presents the subgroup discovery concept in this system. The paper present secure protocols for the task of top-k subgroup discovery on horizontally partitioned data. In this setting, all sites use the same set of attributes and the quality of every subgroup depends on all databases. Subgroup discovery is the task of finding subgroups of a

This type of search use case is useful in identifying the tables and entries with confidential/certified data which can be a huge loss in case of an attack.

The Internet has numerous features and are evolving concurrently. However, the focus of this research paper is directed on the Internet Naming System. Numerous individuals and associations have realized the importance of the Internet in their daily operations. To respond to this effect, people are signing up for emails, websites and other features, which Internet offers to them for interface and communication with the rest of the world. All these activities need to be uniquely identified and hence, the work is currently overwhelming. The naming of the current database and other features has been a challenge. For a while now, the Domain Naming System

NoSQL Databases also referred as Not only SQL databases. These NoSQL database have these days gained much attention and reputation because of their performance and high scalability. The advantage of NoSQL database is to store efficiently unstructured data. These days use of e-commerce websites, social networking sites etc. has been increased. These usage made to create the need to store the large data. Some companies have adopted NoSQL databases, as their data is growing. Dynamo, Big table, Voldemort, Cassandra are the NoSQL databases that are used by Amazon, Google, and LinkedIn and Facebook respectively. Facing these huge data has become challenging for Relational Database Management Systems. Hence NoSQL database came into existence. Mostly Relational Database Management System satisfies ACID properties, through NoSQL database we can achieve high level of Scalability and performance. As a lot of sensitive data is stored in NoSQL databases security issues becomes growing concerns.