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ITC596 IT Risk Management

Published : 09-Sep,2021  |  Views : 10

Question:

1)Provide a brief overview of the case study and prepare a diagram for the ENISA Big Data security infrastructure.
2) Out of the ‘’Top threats’’ which threat would you regard to be the most significant and why
3) Identify and discuss the key Threat Agents. What could be done to minimize their impact on the system Based on the data provided, discuss the trends in threat probability.
4) How could the ETL process be improved Discuss.
5) To sum up, should ENISA be satisfied with its current state of IT Security Why Or Why not.

Answer:

Risk analysis and security is considered as important for an organization to implement effective operations as well as integration of improving the system. In this point of view, improvement of the project would help to incorporate the procedure of advancement of operations and in addition apply successful capacities inside the specific organization. In addition, operational processing can be suggested keeping in mind the end goal to shape risk analysis related with the association. The operational preparing can be suggested with a specific end goal to shape investigation of dangers may be confronted by the associations at the season of performing operations and in addition capacities in light of advancement of operations for mix of capacities for strategies of the undertaking.

The report would help the way toward coordinating the capacities and operations of the association so as to create risk assessment as well as analysis. Along with these, it would tend assessing the part of innovation for execution of effective risk through breaking down the contextual study of ENISA. In this aspect, practicing big data strategy would improve operations inside the organization. Then again, the utilization of big data in the organization has distinguished the issues and additionally dangers of security for the undertaking. Consequently, examination of dangers of big data technique for ENISA would depict agents of threats.

1. Scenario of Big Data security infrastructure

The enterprise had deployed big data analytics keeping in mind the end goal to create compelling operations and development of the organization. ENISA deployed big data strategy inside the enterprise with a specific end goal to increase competitive advantage (Patil & Seshadri, 2014). In this viewpoint, risk and threat management should be effectively implied for creating powerful development of operations. Big data threats would bring about advancement of incidental threats for ENISA in incorporating the framework inside the organization.

The undertaking is considered as one of the efficient system for security, which is proficient observing the particular stream of the operations inside the endeavor and additionally suggest productive security framework inside the enterprise (Sagiroglu & Sinanc, 2013). In any case, protection in huge information is considered as central point assuming a pivotal part in implantation of advancement show for ENISA. In this viewpoint, operations of the undertaking would be profoundly upgraded through use of enormous information procedure inside the association.

In addition, ENSIA had implied ICT based solutions enhancing security works with a specific end goal to oversee enormous information procedure in the project. Thuraisingham (2015) stated that various proprietors are giving different models to the change of the ICT devices in the enterprise including information proprietors, information transformers as well as computation. These models help in giving compelling management if the data is not secured in the organization (Vatsalan et al. 2017). There are different practices that are analytics in the enterprise for overseeing risk and management of information utilized the association. The procedure of operating in the organizations suggested in the risk management for procuring the security of data and information in the organization. Therefore, the advancement of the risk management evaluation helps in keeping up the security of the information and data in the association.

1.2 Big Data security infrastructure for ENISA

The system of the ENISA has been appropriately organized of operating properly in the big data strategy. Accordingly, the big data infrastructure helped in keeping up the data sources, storage of data as well as analytics with registering models under the introduction layer. The big data security infrastructure has been readied utilizing Ms-Visio by keeping up the design of the enormous information security system is given below.

design of the enormous information security system                                           ENISA Big Data security infrastructure diagram

                                                              (Source: Created by author)

The layered structure of ENISA is able to keep up the big data implementation and reconciliation for keeping up the improvement of the system in the organization (Wu et al. 2014). The successful execution of the big data analytics has helped in building up the organization in the market. There are different layers of the enormous information including the information sources, investigation, information stockpiling, and introduction layer and computing models. The operations of the big data infrastructure have been capable to eliminate the security threats in the database of the organization.

The security data of the organization has been keeping up the security of the information and data of the association (Baumer, 2017). There are different security protocols utilized by the organization in the market including Ranger, Encryption, KNOX as well as Firewall. This safety effort helps in keeping up the security of the big data infrastructure of ENISA. The particular capacity identified with the database of the ENISA has been appeared in the table underneath:

Security Function

Description

Big data structure layer of the ENISA

Components in big data structure layer of the ENISA

KNOX

It provides particular solution as well as real time protection of data sources when added (Cardenas et al. 2013). In addition, the KNOX gives effective control of the strategies implied for developing the enhanced control of the functions in terms of security.

Data Sources layer

Data Sources layer consists of components  of streaming data from the sensors as well as unstructured data and semi-structured data, along with structured data

Ranger

It is authorization system assisting in making limitation for the user access in big data system, defined by the Ranger policies. The user needs to request to Ranger  to receive the authenticated entry into specific system

Analytics as well as Computing Models layer

And Integration Process layer

 

 

Integration Process layer consists of the components of ETL and Messaging

 

Encryption

Encryption is considered as the most secure way in order to protect data from unknown as well as unauthenticated source. In this aspect, the data can be modified through cryptography technique resulting useless for different users.

Data Storage layer

Data Storage layer consists of No/New SQL databases as well as Distributed File System along with RDF stores

Firewall

Firewall is considered as one of the best protection for the particular network associated with security issues.

Presentation layer

It includes the components of Web Browser, Mobile Devices as well as Web Services

Table 1: Security functions for ENISA Big Data framework

(Source: Created by author)

2. Top Threat in the ENISA

The threats associated with ENISA big data strategy of the organization have been delineated by the accidental threats, technical threats, threats to the organization and distinctive legitimate treats (Chen & Zhang, 2014). These sorts of threats are exceptionally common in the enterprise. Accordingly, there are different techniques made to moderate these issues in the organization. The prevention to the normal management of the organization has been kept up by the operations in the market. There are different risks as well as threats for the ENISA have been given in the forbidden organization beneath:

Threat Types

Examples of the Risk Classification

Accidental Threats

Destruction of records and leaks of data through web application, loss of storage as well as loss of sensitive information, inadequate design as well as planning threat

Deliberate Threats

Deliberate threats related to network traffic issues and interception of server as well as information interception

Organization Threat

The threats related to organization including shortage of IT skills

Legal Threats

Legal threats are violating regulation and failure to encounter contractual needs and abuse of personal data as well as judiciary orders.

Table 2: Threats and Risk of the ENISA Organization

(Source: Created by author)

The risks to the big data analysis in the organization have been a noteworthy risk for the organization the market. The threats of technology incorporate lack of data and business failure. Authorization manhandle and vindictive code era in the organization. These thetas can be likewise ordered by focused assaults, email hacking and data fraud in the organization. Along these lines, there are a few systems arranged for keeping up the security from these dangers on the organization (Chen et al., 2014). The risk innovation mishandle has been the most common threat for the ENISA in the market. The digital world has been experienced this threat everywhere throughout the world. The data has made much loss for the organization in the market. The affectability if the information and data has been proactive in the organization that has made threats the information and data of the organization in the market. The sensitivity of the database of the organization has been causing the loss of information of the organization.

3. Key Threat Agents and their Impact Reduction Options

The technological mishandle risk in the ENISA has been portrayed by the hole if the data, social engineering issues, dissent of administration, directed assaults and control of data in the company. The key dangers of the ENISA are Human mistakes, individual increase and technology.

Technology

The technology is an essential factor in the improvement of the effective operations in the ENISA. The change in the technological domain of the organization may help in securing the information and data of the organization in the market (Demchenko et al., 2013). The technological arrangement of the break of information and data in the association has ready to keep up the tact of the strategies. The ramifications of the innovative issues in the organization have given powerful improvement in the effective stream of operations in the organization. The recognized technological issues in the organization has been legitimately examined for the finding the methodologies to relieve them.

Human generated errors

The human mistakes are the main considerations as the obstructions in the organization. The framework coordinated operations have ready to deal with the security threats associated with the management of the company. The errors that are made by the human cohesiveness are making issues for the company (Enisa.europa.eu, 2017). There are different human mistakes including data block attempt, replay if messages, capturing, unapproved information breaks and control of hardware. The human including the workers and different staffs of the organization controls these issues.

Designing Errors

The designing errors are portrayed because of the systematic in the enterprise. These designing mistakes are affirmed by the implications of the operational handling. These errors are set up for the basic assessment for the advancement of the association. In this way, the business operations are dependable to the administration of the organization. For instance, threats in planning change of information, unreliable sources of data and disappointment in the business procedure.

Key Threat Agents

Examples

Impact Reduction Options

Technology

Data leaks through web application, device or storage loss and loss of sensitive information, loss of cloud data

Utilization of the latest technology of Big Data Implementation as well as Security Measures

Human Errors

Data interception, replay of the messages, hijacking session, unauthorized data breaches, manipulation of the information

Use of enhanced IT skills for developing and using IT deployment principles

Designing Errors

Failure of business process failure, planning threat as well as change of data by mistake along with unreliable information source

Use of the design enhancement technology to develop effective flow of big data implementation

Table 3: Key threat agents

(Source: Created by author)

Trends in threats probability

The analysis of the patterns in threat probability has been a basic part of the risk evaluation processing the company (Hashem et al., 2015). The pattern in the risk likelihood includes the improvement of the operations for the incorporation. The examination of the threat management in the company can be implemented for moderating the dangers engaged with the risk likelihood.

4. Enhancement of ETL process 

ENSIA had confronted numerous execution issues in enhancing the database of the organization in the market (Kao et al., 2014). The ETL procedure in the organization can be enhanced in the different procedure that is talked about underneath:

Usage of minimum data

The batch processing has depleted a sensible measure of memory stockpiling by pulling a lot of information and data for operations in the ENISA. The extraction of least some of the information and data are important for the advancement of the operation in ENISA.

Avoidance of row-by-row lookup

The procedure of the ETL for the most part utilizes push by-push query methodology for performing data operations in the organization (Kim et al., 2014). Despite the fact that it is a period taking procedure contrasted with the mass stacking process. The mass stacking process the alternative of ETL is useful and process quick and substantial measure of information volumes in information operations.

5. Justification of IT security in ENISA 

The IT security of ENISA is produced for the keeping up the operation of the organization in the market. The assurance of information and data in the organization has been fundamental objective if the organization in the current market (Kshetri, 2014). The principle components in the security in ENISA incorporate Ranger, Firewall, KNOX and Encryption. These components have been legitimately introduced I the security layers of the organization in the market.

The current structure of the company has been legitimately kept up for securing the information and data in the organization. The usage of the IPS/IDS has helped in ensuring system invasion by distinguishing and keeping the entrance to the ENISA database.

Conclusion 

It can be presumed that the security of the ENISA has been a slanting case in the market. The organizational structure has prompted security dangers in the organization. The effect of the enormous information examination in the organization has helped in keeping up the security of the information and data of the organization. The mass stacking procedure of the ETL has helped in giving quick handling speed dodging the column by-push lookup in the methodologies. The KNOX, Ranger, Firewall, Encryption, and IDS/IPS are useful in ensuring the system invasion by identifying and keeping the entrance to the database of ENISA

References

Baumer, B. S. (2017). A Grammar for Reproducible and Painless Extract-Transform-Load Operations on Medium Data. arXiv preprint arXiv:1708.07073.

Cardenas, A. A., Manadhata, P. K., & Rajan, S. P. (2013). Big data analytics for security. IEEE Security & Privacy, 11(6), 74-76.

Chen, C. P., & Zhang, C. Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275, 314-347.

Chen, M., Mao, S., & Liu, Y. (2014). Big data: A survey. Mobile Networks and Applications, 19(2), 171-209.

Demchenko, Y., Grosso, P., De Laat, C., & Membrey, P. (2013, May). Addressing big data issues in scientific data infrastructure. In Collaboration Technologies and Systems (CTS), 2013 International Conference on (pp. 48-55). IEEE.

Enisa.europa.eu. (2017). Big Data Threat Landscape — ENISA. [online] Available at: https://www.enisa.europa.eu/publications/bigdata-threat-landscape [Accessed 5 Sep. 2017].

Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98-115.

Kao, R. R., Haydon, D. T., Lycett, S. J., & Murcia, P. R. (2014). Supersize me: how whole-genome sequencing and big data are transforming epidemiology. Trends in microbiology, 22(5), 282-291.

Kim, G. H., Trimi, S., & Chung, J. H. (2014). Big-data applications in the government sector. Communications of the ACM, 57(3), 78-85.

Kshetri, N. (2014). Big data? s impact on privacy, security and consumer welfare. Telecommunications Policy, 38(11), 1134-1145.

Patil, H. K., &Seshadri, R. (2014, June). Big data security and privacy issues in healthcare. In Big Data (BigData Congress), 2014 IEEE International Congress on (pp. 762-765). IEEE.

Sagiroglu, S., &Sinanc, D. (2013, May). Big data: A review. In Collaboration Technologies and Systems (CTS), 2013 International Conference on (pp. 42-47). IEEE.

Thuraisingham, B. (2015, March). Big data security and privacy. In Proceedings of the 5th ACM Conference on Data and Application Security and Privacy (pp. 279-280). ACM.

Vatsalan, D., Sehili, Z., Christen, P., & Rahm, E. (2017). Privacy-Preserving Record Linkage for Big Data: Current Approaches and Research Challenges. In Handbook of Big Data Technologies (pp. 851-895). Springer International Publishing.

Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE transactions on knowledge and data engineering, 26(1), 97-107.

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