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Annotated Bibliography: Database Management System

Question

Task:The purpose of this assignment is to support Learning Outcome 5 for this topic Survey and evaluate a selection of emerging database technologies.

You are required required to read some classic and up-to-date research papers (at least 6) on the one of the topics listed at the end of this document. Compose an annotated bibliography of research papers that relate to the issue so your annotated bibliography will help you (and others) to have a good resource to evaluate and think about the relevance and quality of material on the topic.

Topic

  • Data Integration, Metadata Management, and Interoperability
  • Data integrity, accuracy, currency and quality
  • Database archiving
  • Database evolution
  • Database migration
  • Database Privacy and Security
  • Databases for Distributed and Mobile Systems
  • Non relational databases - Graph Databases
  • Hybrid transactional analytic databases
  • Real time databases and business intelligence
  • Spatio-temporal databases

Answer

Annotated Bibliography
Abouelmehdi, K., Beni-Hessane, A., & Khaloufi, H. (2018). Big healthcare data: preserving security and privacy. Journal Of Big Data, 5(1). doi: 10.1186/s40537-017-0110-7

Big Data has emerged as one of the emerging Database Management System technologies which are used to store and organize the data sets in abundant data volumes. The authors have carried out the research work to discuss the role of the Big Data technology in the field of healthcare. Also, the security and privacy aspects are discussed and analyzed in the research work. The authors have used a combination of the methodologies, such as qualitative and quantitative research methods to conduct the research process. The privacy and security issues in Big Data are explained with the aid of the Big Data lifecycle. The lifecycle is composed of four essential components as data collection, data transformation, data modeling, and knowledge creation. Each of these aspects has their own set of security and privacy risks. The probability of the risks in the data collection and data modeling phases is high. On the other hand, data transformation phase is not exposed to many of the security attacks and the knowledge creation phase may have moderate level of risks and attacks. The authors have also cited the difference between the security and privacy issues which are often used as the interchangeable terms. The details of the technologies to get rid of these security and privacy issues are included in the research work. Authentication, encryption, data masking, and access control are some of these security controls that may be applied. The article is selected for annotated bibliography as it aptly describes the Database Management System security and privacy issues along with the countermeasures. The use of graphical elements is also done correctly.

Kuang, L., Zhu, Y., Li, S., Yan, X., Yan, H., & Deng, S. (2018). A Privacy Protection Model of Data Publication Based on Game Theory. Security And Communication Networks, 2018, 1-13. doi: 10.1155/2018/3486529

The authors in the research work have described the need for Database Management System that at present times associated to privacy concerns that may be resolved through the model proposed. The use and application of sensor application technologies has increased the need for data collection and analysis. However, these applications are usually developed by the third-parties which may bring up the issues of data privacy risks and attacks. Game theory is one of the mechanisms that can provide resolution to such privacy issues. It is the theory that provides the mechanisms of resolving the conflicts and achieving an equilibrium solution for the underlying problem. The use of quantitative research technique is done to establish a privacy protection model for the purpose of data publication. The model proposed by the authors comprises of service development and service update as the two essential components. The research article is included in the annotated bibliography as it aptly covers the research theme.

Maple, C. (2017). Security and privacy in the internet of things. Journal Of Cyber Policy, 2(2), 155-184. doi: 10.1080/23738871.2017.1366536

There are a number of emerging technologies that have come up in the recent times. One such technology is Internet of Things (IoT). All of these technologies that have come up make use of data as one of the essential components. Data acts as the fuel for these technologies to run and carry out specific sets of operations. Therefore, massive volumes of data sets are associated with these technologies and concepts. In the case of IoT services and applications, data is one of the most significant components. The authors have conducted qualitative research processes to determine the security and privacy issues associated with the IoT Database Management System and have come up with certain measures that may be taken to control these issues. The security issues are listed and described on the basis of the industry domains, for example, the security concerns in the healthcare field are different from the security issues for autonomous vehicles, and likewise. Similarly, the privacy challenges associated with the IoT data and applications are specified in the research work. There are certain challenges that are associated with the IoT data sets and applications that lead to the presence of certain vulnerabilities in the system. For instance, low-power and low area aspects are used by the malicious entities to give shape to the attacks. There are certain recommendations included to control and prevent the security attacks. For example, the use of biometric based authentication systems is suggested so that the issues can be controlled. There are no graphical elements used in the research work which is one of the negative points detected and could have been improved upon.

Matturdi, B., Zhou, X., Li, S., & Lin, F. (2014). Big Data security and privacy: A review. China Communications, 11(14), 135-145. doi: 10.1109/cc.2014.7085614

Big Data has emerged as one of the essential components in the business organizations of the present times. It has become essential that the data sets that are collected for analysis and storage are adequately handled. However, there are a number of security and privacy issues that get associated with the Database Management System and Big Data sets. The prevention and control of these security and privacy issues is essential to make sure that the data handling is carefully done. The authors have used qualitative research methods to describe numerous security and privacy issues associated with Big Data. There is also a number of data collection techniques used to conduct the research. Surveys and questionnaires are used as the primary technique for collecting the data sets for research. Some of the security and privacy issues related with Big Data comprise of malware attacks, network security attacks, denial of service attacks, and various other. It is necessary that these security risks and attacks are controlled. It is also essential that the countermeasures to put a check on these risks are put in place. For example, the implementation of the anti-malware tools, anti-denial tools etc. shall be done. The authors have referred the published journals and articles to conduct the research and have also cited the same in the research work. There is good use of graphs and charts done in the research work. The visual elements add to the readability of the content included.

Okman, L., Gal-Oz, N., Gonen, Y., Gudes, E., & Abramov, J. (2011). Security Issues in NoSQL Databases. 2011IEEE 10Th International Conference On Trust, Security And Privacy In Computing And Communications. doi: 10.1109/trustcom.2011.70

In the present era, the need for cloud computing and distributed applications has increased. This is because the users of a particular application are spread all across the globe. It is necessary that the accessibility to the global users is ensured. There are massive volumes of data that are now stored in the distributed databases to make sure that the availability and scalability is enhanced at all times. There are a number of non-relational databases that have emerged in the market as an outcome. These databases are referred as NoSQL databases as they do not make use of SQL as the database query language. There are numerous benefits that these databases have provided to the users and the business organizations. The authors have discussed the security aspect of these NoSQL databases. There are a number of security issues that have been observed in these databases and it has become necessary to put a check on these security issues. Cassandra and Mongo DB are the two most popular NoSQL Database Management System and the security aspect of these databases is discussed and explained in the research work. The authors have made use of exploratory research technique to determine the architecture, features, functionalities, and security controls involved in these databases. The implications of the security issues and attacks on the business organizations and the end-users are also discussed in the journal article. The authors have provided the diagrams and screenshots of the databases so that the users may relate and understand the arguments that are put across. Also, the citations of the references utilized in the research work are also included so that the background search can be easily made. There could have been better use of tables and charts in the research work.

Sun, Y., Zhang, J., Xiong, Y., & Zhu, G. (2014). Data Security and Privacy in Cloud Computing. International Journal Of Distributed Sensor Networks, 10(7), 190903. doi: 10.1155/2014/190903

Cloud Computing has emerged as one of the necessary technologies for the business firms in the present times. This is because the need of distributed architecture and computing has increased with the expansion of digitization and globalization. The authors in the research work have discussed some of the popular cloud models that are used by the business firms. Some of these include public cloud, Platform as a Service (PaaS) cloud, hybrid cloud, private cloud, Software as a Service (SaaS) cloud model, and Infrastructure as a Service (IaaS) cloud. These cloud models have a cloud database wherein the data sets and information pieces are stored. There are specific security and privacy issues associated with each of these cloud models. Some of the major security and privacy issues make use of the networks as the threat agents. The malicious entities carry out unauthorized monitoring of the networks and give shape to the attacks, such as man in the middle attacks and eavesdropping attacks. There are also other forms of security issues that are carried out in terms of malware attacks, denial of services attacks, breaching of the data sets, and others. The authors have proposed a security framework designed on the basis of Radio Frequency Identification (RFID) to maintain the security and privacy of the data sets. The use of encryption is also encouraged by the authors to ensure that the security and privacy is always maintained. Homomorphic encryption, encrypted search and databases, distributive storage, hybrid storage, data concealment, and deletion confirmation are some of the techniques proposed to safeguard the confidentiality of the data sets used on the Database Management System. Reliable storage agreement and reliability of the hard-drive are the measures proposed to control the availability issues. The authors have not made use of many charts, table, diagrams, or other graphical elements in the research work. This is one area that could be improved upon.

Sun, Z., Strang, K., & Pambel, F. (2018). Privacy and security in the big data paradigm. Journal Of Computer Information Systems, 1-10. doi: 10.1080/08874417.2017.1418631

Big Data has developed as one of the fundamental parts in the business associations of the present occasions. It has turned out to be essential that the data sets that are gathered for investigation and capacity are properly dealt with. Nonetheless, there are various security and privacy issues that get related with the Big Data sets. The counteractive action and control of these security and privacy issues is basic to ensure that the data in action is protected at all times. The authors have utilized exploratory and qualitative research strategies to depict various security and privacy issues related with Big Data. There is likewise various data accumulation methods used to lead the examination. Domain analysis and surveys are utilized as the essential procedure for gathering the data sets for research. A portion of the security and privacy issues related with Big Data involve malware assaults, insider threats, denial of service assaults, and network-based security attacks. It is important that these security dangers and assaults are controlled. It is likewise fundamental that the countermeasures to keep an eye on these security & privacy risks are set up. For instance, the execution of the anti-malware devices, anti-denial instruments and so on must be done. The authors have made use of the distributed journals and articles to lead the research and have additionally referred to the academic journals and domain specific content. There is great utilization of diagrams and graphs done in the examination work. The visual components add to the lucidness of the substance included. The article was selected for annotated bibliography as Big Data is one of the emerging Database Management System technologies of the recent times in the area of data handling and management. It is necessary that the security aspects of the technology are carefully analysed. Database annotated bibliography assignments are being prepared by our database assignment help experts from top universities which let us to provide you a reliable assignment help online service.

References
Abouelmehdi, K., Beni-Hessane, A., & Khaloufi, H. (2018). Big healthcare data: preserving security and privacy. Journal Of Big Data, 5(1). doi: 10.1186/s40537-017-0110-7

Kuang, L., Zhu, Y., Li, S., Yan, X., Yan, H., & Deng, S. (2018). A Privacy Protection Model of Data Publication Based on Game Theory. Security And Communication Networks, 2018, 1-13. doi: 10.1155/2018/3486529

Maple, C. (2017). Security and privacy in the internet of things. Journal Of Cyber Policy, 2(2), 155-184. doi: 10.1080/23738871.2017.1366536

Matturdi, B., Zhou, X., Li, S., & Lin, F. (2014). Big Data security and privacy: A review. China Communications, 11(14), 135-145. doi: 10.1109/cc.2014.7085614

Okman, L., Gal-Oz, N., Gonen, Y., Gudes, E., & Abramov, J. (2011). Security Issues in NoSQL Databases. 2011IEEE 10Th International Conference On Trust, Security And Privacy In Computing And Communications. doi: 10.1109/trustcom.2011.70

Sun, Y., Zhang, J., Xiong, Y., & Zhu, G. (2014). Data Security and Privacy in Cloud Computing. International Journal Of Distributed Sensor Networks, 10(7), 190903. doi: 10.1155/2014/190903

Sun, Z., Strang, K., & Pambel, F. (2018). Privacy and security in the big data paradigm. Journal Of Computer Information Systems, 1-10. doi: 10.1080/08874417.2017.1418631

Database Management Annotated Bibliography Assignment


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