Provide a brief overview of the case study and prepare a diagram for the ENISA Big Data security infrastructure.
For the situation investigation of ENISA, there is an elaboration on dangers that are identified with Big Data. There has been highly picked up footing inside most recent couple of years and consequently the information stockpiling and data innovation has been expected to assume a genuine part on a few new viewpoints in the general public (Marinos, 2013). The perspectives that must be create and influenced by the improvement of data innovation and Big information are nourishment security, wellbeing security, atmosphere and assets that are proficient to vitality, shrewd transport framework and savvy urban communities. The potential effect of the Big Data has been recognized by the European Commission by distinguishing the vital approach in the Big Data. The information is accordingly possible to the financial drive in the authoritative framework. In the field of science and research there is additionally a huge effect of the Big Data that keeps on raising. In this way, numerous offices and foundation everywhere throughout the globe are wanting to dispatch the Big Data ventures for better misuse of information examination and distributed computing. Innovations of Big Data can likewise be utilized as a part of the use of military field, for example, battle pleasing or battling virtual or genuine psychological warfare. Along these lines distinguishing and gathering the data from heterogeneous sources from any genuine recorded or open sources has an extraordinary effect (Marinos, Belmonte &Rekleitis, 2014). Cutting edge and very novel ICT frameworks are utilized as a part of the approach of Big Data. Yet, increment in the utilization of this Big Data innovation has likewise as often as possible expanded the odds of digital assaults, information breaks and hacking. The increments of this sort of difficulties are both slanting the number in complex and effect. By increment in the quantity of ease of use of Big Data in business and associations, the aggressors get motivating forces for creating and practices assaults against Big Data examination. This innovation has additionally the capacity to be utilized as a device that battles the digital dangers by offering security and protection experts that has important bits of knowledge in occurrence administration and dangers. ENISA conveys the range of this Threats Landscapes in the field of Big Data investigation, by the contributions from the ENISA Threat Landscape exercises. The contextual analysis examines about the design, the benefit scientific classification of Big Data, ENISA danger scientific classification the focused on group of onlookers of Big Data approach, the procedure by which the contextual investigation has been done, holes of the examination lastly prescribing the approach.
Distributed computing is portrayed as the foundation layer of Big Data framework in ENISA. This may meet the framework prerequisite like the versatility, cost-adequacy and the capacity to scale here and there (Marinos, Belmonte &Rekleitis, 2014). The security framework of Big Data framework in ENISA takes after:
Out of the ‘’Top threats’’ which threat would you regard to be the most significant and why?
The various types of dangers as per the gathering are:
Risk Group: Eavesdropping, Interception and Hijacking
Risk Group: Nefarious Activity/Abuse
Identity extortion
Denial of administration
Malicious code/programming/movement
Generation and utilization of rebel declaration
Unauthorized exercises/Misuse of review instruments/Abuse of approvals
Business process disappointment (Lévy-Bencheton et al., 2015)
Risk Group: Legal
Breach of enactment/Abuse of individual information/Violation of laws or directions
Skill lack
Agreeing the examination of the three dangers bunches the most noteworthy risk is the “Listening stealthily, Interception and Hijacking”, since the most information and security dangers are identified with this danger confronts greatest troubles, similar to the information breaches, hacking, digital assault and some more. Influencing the most private and classified assets of the organization (Cho et al., 2016). The principle assaults by this risk bunches are Leakage of Information/sharing because of human blunder, Leaks of information by means of Web applications (unsecure APIs), lacking outline and arranging or inaccurate adjustment and Interception of data. The commitment of keen gadgets and PC stage from the phenomenal systems administration to the Big Data may posture protection concern where a person’s area, exchange and other conduct are recorded carefully (Scott et al., 2016). This danger specialist is antagonistic in nature. Their objective is essentially monetary benefit having higher ability level. Cybercriminals can be sorted out on a neighborhood, national or even worldwide level. These specialists are socially and politically inspired people utilizing the system or the PC framework for challenging and advancing reasons for the harm (Wang, Anokhin&Anderl, 2017). Prominent sites are for the most part being focused alongside knowledge organizations and military establishments.
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.
Agreeing the ENISA danger Landscape, the risk specialist is depicted as “somebody or something with better than average capacities, a reasonable aim to show a risk and a record of past exercises in such manner” (Barnard-Wills, Marinos&Portesi, 2014). The association utilizing Big Data application must know about the dangers that are rising and from which risk bunches that they have a place. There are classifications by which the danger operators have been isolated in:
Partnerships: This classification alludes to the undertakings or associations that may draw in or adjust any strategies that might be exploitative and hostile to the venture. These are the threatening risk operators having the thought process to assemble upper hand over the contenders. The association for the most part sorts their principle targets and centering over the size and segments the undertakings have abilities to the region of essentialness, and from the territory of innovative perspective to human building insight in the field of mastery (Brender& Markov, 2013).
Digital Criminals: This risk operator is threatening in nature. Their objective is essentially monetary profit having higher aptitude level (Le Bray, Mayer &Aubert, 2016). Cybercriminals can be sorted out on a nearby, national or even worldwide level.
Digital psychological oppressors: The inspiration of this risk operator can either be religious or political, that extends the movement taking part in digital assaults. The objectives that are favored by the digital psychological oppressors are fundamentally finished basic framework like in media transmission, vitality generation or open human services framework (Olesen, 2016). This perplexing framework is by and large picked since disappointment of this association makes as mayhem and cause extreme effect in the legislature and society.
Content kiddies: These specialists utilize the contents and the projects created since these are for the most part incompetent, that assaults the system or the PC frameworks and additionally sites.
Online social programmers (hacktivists): These specialists are socially and politically inspired people utilizing the system or the PC framework for dissenting and advancing reasons for the harm (Bugeja, Jacobsson&Davidsson, 2017). Prominent sites are for the most part being focused alongside insight organizations and military establishments.
Representatives: Sometime the workers for the disintegration of the organization get to the organization’s assets from inside and subsequently unfriendly and non-antagonistic specialists both of these can considered to the representative. This operator incorporates staffs, operational staffs, temporary workers or security watchmen of the organization (Belmonte Martin et al., 2015). A lot of information is required for this sort of dangers, which causes them in setting the viable assault against the advantages of the organization.
Country expresses: these operators for the most part have hostile abilities in digital security and may utilize it over an endeavor.
Securing the Big Data resources by utilizing pertinent strategies and procedures in the association. There has been a mutual duty regarding the protection, security and framework administration of each association. Since, the specialists focus on the fundamental partners of the Big Data concentrating on the substantial measure of datasets (Belmonte Martin et al., 2015). After a watchful development of the life cycle of Big Data there ought to be point of checking and demonstrating the right conduct. There can be achievement in merchants submitted by the outsider, applying safety efforts and consequently stay refreshed and centered.
On the premise of the information gave the pattern in the risk likelihood it has been clarified that:
How could the ETL process be improved? Discuss.
The dangers scientific categorization as created by the ENISA Threat Landscape (ETL) Group and this incorporates dangers that are pertinent for the advantages of the Big Data and these can be enhances by the accompanying ways:
To sum up, should ENISA be satisfied with its current state of IT Security? Why? Or Why not?
According to the ENISA Big Data there are few focuses on the security framework:
There are a few sorts of difficulties distinguishes in the security arrangement of Big Data. These difficulties must need information security, control availability of information and information sifting (Lykou, 2016). As said by the ENISA there are a few issues with respect to colossal measure of information control that is past the preparing energy of items in Security data and Event Management (SIEM).
Truly, ENISA be happy with its present territory of IT Security. There are holes in information insurance because of the dangers and secrecy of sensor information streams. In instances of character extortion, the movement caught and the Big Data examination helps in encouraging the security interruption by fortifying the normal systems and on additionally look into in the required fields. In year 2009 the ENISA has chosen to refresh and survey the dangers and advantages for higher reflection to the present circumstance of the association. It has been recognized that the fundamental hazard that is by utilizing distributed computing has not changed but rather there has been a choice of reproducing the dangers having the point of making the depictions much uniform (Lévy-Bencheton et al., 2015). There has been a presentation of legitimate and information security parts of Big Data and distributed computing. There is a continuation of checking the improvement identified with the dangers and danger of distributed computing and as needs be refresh the Risk Assessment.
Conclusion
This report goes for investigating the way that innovative headway for huge information can meet and incorporate innovative progressions in security. This ought not be considered as a comprehensive introduction of all accessible and conceivable strategies, but instead as an endeavor to take this exchange a stage forward and to connect with every single significant partner in a more humanistic information security driven investigation improvement in Big Data.
References
Barnard-Wills, D. (2014). ENISA Threat Landscape and Good Practice Guide for Smart Home and Converged Media. ENISA (The European Network and Information Security Agency).
Barnard-Wills, D., Marinos, L., &Portesi, S. (2014). Threat landscape and good practice guide for smart home and converged media. European Union Agency for Network and Information Security, ENISA.
Belmonte Martin, A., Marinos, L., Rekleitis, E., Spanoudakis, G., &Petroulakis, N. E. (2015). Threat Landscape and Good Practice Guide for Software Defined Networks/5G.
Brender, N., & Markov, I. (2013). Risk perception and risk management in cloud computing: Results from a case study of Swiss companies. International journal of information management, 33(5), 726-733.
Bugeja, J., Jacobsson, A., &Davidsson, P. (2017, March). An analysis of malicious threat agents for the smart connected home. In Pervasive Computing and Communications Workshops (PerCom Workshops), 2017 IEEE International Conference on (pp. 557-562). IEEE.
Cho, H., Yoon, K., Choi, S., & Kim, Y. M. (2016). Automatic Binary Execution Environment based on Real-machines for Intelligent Malware Analysis. KIISE Transactions on Computing Practices, 22(3), 139-144.
Gorton, D. (2015). IncidentResponseSim: An agent-based simulation tool for risk management of online Fraud. In Secure IT Systems (pp. 172-187). Springer, Cham.
Karchefsky, S., & Rao, H. R. (2017). Toward a Safer Tomorrow: Cybersecurity and Critical Infrastructure. In The Palgrave Handbook of Managing Continuous Business Transformation (pp. 335-352). Palgrave Macmillan UK.
Le Bray, Y., Mayer, N., &Aubert, J. (2016, April). Defining measurements for analyzing information security risk reports in the telecommunications sector. In Proceedings of the 31st Annual ACM Symposium on Applied Computing(pp. 2189-2194). ACM.
Lehto, M. (2015). Phenomena in the Cyber World. In Cyber Security: Analytics, Technology and Automation (pp. 3-29). Springer International Publishing.
Lévy-Bencheton, C., Marinos, L., Mattioli, R., King, T., Dietzel, C., &Stumpf, J. (2015). Threat landscape and good practice guide for internet infrastructure. Report, European Union Agency for Network and Information Security (ENISA).
Lévy-Bencheton, C., Marinos, L., Mattioli, R., King, T., Dietzel, C., &Stumpf, J. (2015). Threat landscape and good practice guide for internet infrastructure. Report, European Union Agency for Network and Information Security (ENISA).
Lykou, G. (2016). Critical Infrastructure Protection: Protecting Public Welfare.
Marinos, L. (2013). ENISA Threat Landscape 2013: Overview of current and emerging cyber-threats. Heraklion: European Union Agency for Network and Information Security Publishing. doi, 10, 14231.
Marinos, L., Belmonte, A., &Rekleitis, E. (2014). ENISA Threat Landscape Report 2013. European Union Agency for Network and Information Security.
Marinos, L., Belmonte, A., &Rekleitis, E. (2014). ENISA Threat Landscape 2015. Heraklion, Greece: ENISA. doi, 10, 061861.
Olesen, N. (2016). European Public-Private Partnerships on Cybersecurity-An Instrument to Support the Fight Against Cybercrime and Cyberterrorism. In Combatting Cybercrime and Cyberterrorism (pp. 259-278). Springer International Publishing.
Rhee, K., Won, D., Jang, S. W., Chae, S., & Park, S. (2013). Threat modeling of a mobile device management system for secure smart work. Electronic Commerce Research, 13(3), 243-256.
Scott, K. (2016, November). Phobic Cartography: a Human-Centred, Communicative Analysis of the Cyber Threat Landscape.
Wang, Y., Anokhin, O., &Anderl, R. (2017). Concept and use Case Driven Approach for Mapping IT Security Requirements on System Assets and Processes in Industrie 4.0. Procedia CIRP, 63, 207-212.
Essay Writing Service Features
Our Experience
No matter how complex your assignment is, we can find the right professional for your specific task. Contact Essay is an essay writing company that hires only the smartest minds to help you with your projects. Our expertise allows us to provide students with high-quality academic writing, editing & proofreading services.
Free Features
Free revision policy
$10Free bibliography & reference
$8Free title page
$8Free formatting
$8How Our Essay Writing Service Works
First, you will need to complete an order form. It's not difficult but, in case there is anything you find not to be clear, you may always call us so that we can guide you through it. On the order form, you will need to include some basic information concerning your order: subject, topic, number of pages, etc. We also encourage our clients to upload any relevant information or sources that will help.
Complete the order form
Once we have all the information and instructions that we need, we select the most suitable writer for your assignment. While everything seems to be clear, the writer, who has complete knowledge of the subject, may need clarification from you. It is at that point that you would receive a call or email from us.
Writer’s assignment
As soon as the writer has finished, it will be delivered both to the website and to your email address so that you will not miss it. If your deadline is close at hand, we will place a call to you to make sure that you receive the paper on time.
Completing the order and download