Program Title Btec Computing Unit Title Computing Research Project.pdf

PROGRAM TITLE: BTEC ComputingUNIT TITLE: Computing Research ProjectASSIGNMENT NUMBER: 1

ASSIGNMENT NAME: Computing Research ProjectSUBMISSION DATE:

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2 The method approaches 8

2.1 The concept of secondary and primary research 8

2.2 Primary and secondary research approaches 8

3 Qualitative, quantitative, and mixed research methods 9

3.1 Qualitative and quantitative research 9

3.2 Mixed studies 9

4 Approach and application of research methods 10

II Conduct and analyse research relevant to computing research project.111 Direct Interview Questions 11

2 Survey Questions 13

3 Assessment of the cost of conducting interview and survey methods 15

4 Evaluate the method of implementation based on an ethical perspective 16

5 Analysis data 17

6 Discuss merits, limitations, and pitfalls of approaches to data collection and analysis 25

7 Critically evaluate research methodologies and processes in application to a computing research project tojustify chosen research methods and analysis 27

III Critically evaluate research methodologies and processes in application to a computingresearch project to justify chosen research methods and analysis.301 Evaluation research goals 30

2 Consider limits and potential risks 31

3 Make recommendations 33

IV Reflect on the application of research methodologies and concepts.351 Discuss the effectiveness of research methods applied, for meeting objectives of the computing researchproject 35

2 Discuss alternative research methodologies and lessons learnt in view of the outcomes 38

3 Demonstrate reflection and engagement in the resource process, leading to recommended actions for futureimprovement 41

3.2 Methodology Evaluation 42

3.3 Ethical Perspective 42

3.4 Merits, Limitations, and Pitfalls: 42

3.5 Research Methodologies and Processes: 42

3.6 Overall Recommendations 42

I Examine appropriate research methodologies and approaches as part of theresearch process.

1 Research Proposal

1.1 Context

and important than ever The concept of "Big Data" has become a fundamental factor forthe development of various industries and organizations Big data is not just a hugeamount of information generated from many different sources, but also refers to the useand processing of this data to make smart decisions and provide insights more aboutglobal trends and patterns Pearson's "Introduction to theme" article on Big Data touchedon the importance of capturing big data and how it has changed the way we accessinformation and knowledge Big data is not only a valuable resource but also brings withit many challenges and opportunities In this context, the two specific topics we havechosen to study are "Legal and ethical trade-offs" and "Cyber security risks" on networksecurity) The first topic raises questions about the balance between the use of big data toachieve business goals and the personal rights and ethics of using personal information.The second topic focuses on the cybersecurity risks that the collection, storage andprocessing of big data can bring Protecting critical information from attacks andvulnerabilities is a matter of concern We will dive into these issues and provide adetailed look at how these topics affect the use of big data and how they can impacttechnology, business, and society We will look at both the benefits and risks that thesetopics bring With the theoretical background and context of Big Data mentioned inPearson's "Introduction to theme" article, we hope that further research on "Legal andethical trade-offs" and "Cyber security risks" " will contribute to our understanding ofhow big data is changing the way we live and work.

1.2 Reason for choosing topic

- Our choice of the two topics "Legal and ethical trade-offs" and "Cyber security risks" isnot only based on their importance in the world of big data but also comes from interestand awareness extensively on these issues Here's why we chose these topics forresearch:

o Legal and Ethical Trade-offs:

The ever-increasing volume of data has raised many privacy, privacy, and ethicalissues We are interested in how the use of big data can bring about trade-offsbetween business goals and legal and ethical limitations By delving deeper intothis issue, we hope to be able to offer multiple perspectives on the current andfuture situation of big data use in an increasingly legal and ethical context.complicated.

o Cyber Security Risks:

Cybersecurity is one of the most important challenges facing the digital society.With big data becoming more and more popular, it becomes more and more

investigate the cybersecurity risks that the use of big data presents, from systemintrusions to misuse of personal information By digging deeper into this, we hopeto contribute to figuring out how to protect data and information fromincreasingly sophisticated cybersecurity threats.

o Our selection is based not only on general research goals, but also on our desire totruly understand the challenges and opportunities that Big Data presents Webelieve these topics will provide a multi-dimensional perspective and promotedeep thinking about how big data impacts our lives.

1.3 Method

- To conduct research on the topics of "Legal and Ethical Trade-offs" and "CybersecurityRisks" in the context of big data, we will use a research methodology that combinesdocument analysis and real-world research land This approach will allow us to furtherexplore the legal, ethical and cybersecurity aspects related to the use of big data.

reports, books and documents from reputable international organizations in the field ofbig data, legal and security networks security.

undergone testing and are recognized by the research community or experts in theirrespective fields This ensures the accuracy and reliability of the information we use.

sources We will review the legal and ethical documents related to the use of big data Atthe same time, we will learn about cybersecurity threats and safeguards in today's digitalenvironment The collected information will be analyzed and compared to give a clearerand more detailed view of the issues posed.

1.4 Expected results

- Our ultimate goal in researching "Legal and Ethical Trade-offs" and "Cyber SecurityRisks" is to have a clear view of the implications and solutions related to the use of bigdata in legal, ethical, and cybersecurity environments Here are the expected results wehope to achieve:

balance between business interests and the protection of privacy and personal ethics Wehope to be able to identify key points that organizations need to consider to ensure theiruse of big data remains compliant with legal and ethical guidelines.

o For the topic "Cyber Security Risks," we expect to be able to analyze and evaluatecybersecurity threats related to the use of big data We will learn about possible

help us recommend effective security measures to deal with these risks.o Proposed solutions and problem-solving processes: Based on the collected and

analysed results, we hope to be able to propose specific solutions to balancebusiness interests and legal and ethical principles For cybersecurity, we'll reviewsecurity measures and procedures to protect data from attacks.

o The end result we want is to be able to provide specific recommendations andprocedures so that organizations and individuals can safely, legally and ethicallyuse big data in the digital environment become today.

2 The method approaches

2.1 The concept of secondary and primary research

and data, namely secondary research and primary research.

existing data sources and documents These can be articles, books, research reports,academic papers, and other sources of information that have been previously published.Secondary research focuses on analyzing and synthesizing available information to drawnew conclusions or clarify issues related to the research topic.

source to answer specific research questions Primary research methods include survey,interview, direct observation, experiment, and many other data collection activities.Primary research allows researchers to interact directly with data and gather newinformation, making their own analyzes and assessments.

and knowledge Secondary research is often used to set context and make availableinformation available, while primary research allows the researcher to generate new dataand perform further analyses.

2.2 Primary and secondary research approaches

o Document analysis: Read, summarize and analyze documents such as books,articles, research reports.

o Synthesis: Synthesize information from multiple sources to create an overview ofthe research topic.

o These methods allow researchers to gather information from sources or usealready existing information to generate research knowledge and outcomes Acombination of primary and secondary research can provide a comprehensiveview of a research problem.

3 Qualitative, quantitative, and mixed research methods.

3.1 Qualitative and quantitative research

properties and semantics of phenomena or events This method does not measure orcount variables, but instead analyzes and describes attributes, facts, opinions, sentiments,or aspects that cannot be quantified Examples: content analysis, discussion analysis, casestudies.

variables in terms of numbers and data This method relies on statistics to analyzerelationships between variables and draw conclusions based on digitized data Forexample, a survey of the number of people using a particular service, which measurescustomer satisfaction through a score system.

- As such, qualitative research focuses on descriptive properties and semantics, whilequantitative research focuses on measurement and analysis of digitized data Thecombination of both methods can help deepen understanding of a research problem anddraw thoughtful conclusions.

3.2 Mixed studies

and quantitative research in a single research process This method aims to exploit theadvantages of both types of research to provide a richer and more comprehensive view ofa research problem.

the semantics, context, and characteristics of the research phenomenon Then,quantitative data are collected to measure the extent and relationship between specificvariables Results from both types of data are combined to provide a more comprehensiveconclusion about the research problem.

- Mixed research can provide benefits such as broadening the scope and breadth ofresearch insights, verifying and enhancing the reliability of results However, the conductof mixed studies requires careful consideration to ensure the integrity and logic of themethod.

4 Approach and application of research methods

from text documents, images, or qualitative data.

- Discussion analysis: Analyse discussions and responses to understand participants'opinions and views.

research problem The choice between methods should be based on the specific researchobjectives and questions.

II Conduct and analyse research relevant to computing research project.1 Direct Interview Questions

- Direct Interview Questions for "Legal and Ethical Trade-offs":

o Question 1: "The use of Big Data often involves collecting and analysing personalinformation How do you perceive the trade-offs between business interests andprotecting individuals' privacy and ethics in the context of Big Data?"

Respondent: John Smith, Data Privacy Analyst

Information: John believes that there is a delicate balance betweenbusiness interests and privacy/ethical concerns He emphasizes theimportance of clear data usage policies and consent mechanisms.o Question 2: "From your perspective, what legal and ethical frameworks or

regulations are necessary to ensure responsible use of Big Data?"Respondent: Sarah Johnson, Legal Expert

Information: Sarah highlights the need for comprehensive data protectionlaws and strict enforcement mechanisms She also discusses the role ofethical guidelines in the industry.

o Question 3: "What are some specific examples of situations where you'veobserved trade-offs between business interests and the protection of personalprivacy and ethics in the use of Big Data?"

Respondent: Maria Lopez, Data Ethics Researcher Information: Mariashares a case study about a retail company using customer data withoutclear consent, highlighting the ethical concerns it raised.

o Question 4: "In your opinion, what role do transparency and informed consentplay in addressing legal and ethical challenges associated with Big Data use?"

Respondent: David Brown, Privacy Advocate Information: Davidemphasizes the importance of transparent data practices and informedconsent mechanisms to mitigate legal and ethical issues.

- Interview Questions for "Cyber Security Risks" (Continued):

o Question 1: "Can you provide an example of an effective cybersecurity measureor strategy that has successfully mitigated risks associated with Big Data usage inan organization?"

Interviewee: Emily White, IT Security Consultant

Information: An effective cybersecurity measure to minimize the risksassociated with using Big Data within an organization is to implement astrict access control system and continuous monitoring We havesuccessfully implemented a Zero Trust model in our environment.

We have established strict rules that determine access rights basedon the "least user permissions needed" principle Even people withaccess to Big Data must be continuously authenticated, and we usetechnologies like MFA (Multi-Factor Authentication) to protectaccounts from credential theft.

Additionally, we have implemented continuous monitoring to trackuser activity and Big Data workflows Our monitoring system is

that the problem can be handled before it causes majorconsequences.

Additionally, we have trained employees on recognizing andresponding to cybersecurity threats Employee awareness andskills play an important role in protecting our Big Data from riskysituations.

o Question 2: "What do you see as the most significant cybersecurity threatemerging in the context of Big Data over the next five years, and how canorganizations prepare for it?"

Interviewee: Mark Davis, Cybersecurity Analyst

Information: One of the main threats that I predict will emerge in the BigData landscape in the coming year is increased user-side attacks Hackersare increasingly focusing on compromising personal information and useraccounts to access Big Data This poses a major threat of importantinformation leaks and privacy violations.

To prepare for this threat, organizations need to strengthen securityat the user level This includes implementing multi-layeredsecurity measures such as MFA, monitoring user activity to detectsigns of attacks, and training users on common compromisetechniques.

Additionally, data encryption during transmission and storage isimportant to prevent man-in-the-middle attacks and protectimportant data from unauthorized access I encourageorganizations to continually evaluate and update their securitymeasures to ensure effectiveness and compliance with newcybersecurity standards.

o Question 3: "Can you provide an example of an effective cybersecurity measureor strategy that has successfully mitigated risks associated with Big Data usage inan organization?"

Interviewee: Emily White, IT Security Consultant

Information: One cybersecurity measure we have implemented to mitigatethe risks associated with the use of Big Data is to establish an effectivedata protection and classification system We have identified andclassified important data types, such as customer information, accountinformation, and important content data.

We apply different security measures depending on the type ofdata, such as strong encryption for sensitive data This systemhelps us focus strong protection on the most important parts of BigData, while also helping to reduce the cost and effort ofunnecessary security for less important data.

Additionally, we have deployed an advanced intrusion detectionand monitoring solution to monitor any suspicious Big Databehavior This helps us detect and handle risks as they arise,

organization's Big Data.

o Question 4: "What do you see as the most significant cybersecurity threatemerging in the context of Big Data over the next five years, and how canorganizations prepare for it?"

Interviewee: Mark Davis, Cybersecurity Analyst

Information: Over the next year, I predict that the most importantcybersecurity threat will be the rise of attacks from partner and vendorrelationships in the context of Big Data Hackers will try to take advantageof affiliate relationships to penetrate the system and obtain importantinformation.

To prepare for this threat, organizations need to place specialemphasis on assessing and enhancing security within the supplychain This includes ensuring that your partners and suppliers alsocomply with high cybersecurity standards and implementingsecurity measures such as periodic security checks and encryptionof transmitted data.

Organizations should also perform regular security testing to detectand fix potential vulnerabilities in their systems Furthermore,employee training and increased cybersecurity awarenessthroughout the organization will play an important role inpreventing threats from partnerships.

2 Survey Questions

Survey Questions for "Cyber Security Risks":

Survey Question 1: In the process of collecting and processing big data, whatspecific cybersecurity risks has your organization identified?

F.Information Warfare and Disinformation.Preliminary Assessment:

Survey Question 2: How does your organization ensure the security of big data asit is transmitted over networks or stored on systems?

Survey Results:

A Data encryption B.Firewalls.

C Two-factor authentication (2FA).D.Access rights management.E.Update and patch security holes.F Continuous monitoring.G.Implement a strict security policy.H.Backup and recovery.

J Periodic security reviews.Preliminary Assessment:

most concerning in the context of Big Data use?Survey Results:

A.Data breachesB.Phishing attacksC.Insider threatsD.Malware attacksE.DDoS attacks

Preliminary Assessment: Respondents are most concerned about databreaches and malware attacks in the context of Big Data use.

Survey Question 4: What specific measures have been implemented to prevent ordetect cyber-attacks involving big data?

Survey Results:

A.Intrusion Detection System (IDS) and Application IntrusionDetection B.System (WAF).

C.Security monitoring system (SIEM)

D.Network traffic monitoring system and User behaviormonitoring.

E.Behavioral analytics based on machine learning and artificialintelligence (AI/ML)

F.Regular system and application updates and Penetration Testing Survey Question 5: How much damage do data-related cybersecurity attackscause?

Survey Results:

A Leaking personal information.B Loss of important business information.C Loss of reputation and money.D Stagnation in business activities.Survey Questions for "Legal and Ethical Trade-offs":

Survey Question 6: What existing legal frameworks are in place to adequatelyaddress the ethical challenges created by the use of big data?

G.International agreements.H.Ethical guidelines and standards.J.Data breach notification laws.

Survey Question 7: What are the standardized ethical guidelines specific to theuse of Big Data that have been widely adopted, in addition to legal regulations?

Survey Responses:

A Internet Privacy Decree (Privacy by Design).B ISO/IEC 27001 standard.

C.Open Data Standard.

D AI Data Ethics Guidelines (AI Ethics Guidelines).F Ethical principles of Big Data Analytics.

Survey Question 8: How can we ensure that an organization's use of big data doesnot violate ethical principles or cause negative consequences for society?

Survey Responses:

legally and transparently.

B.Collect data legally and transparently.C Carry out the ethics assessment process.

D.Training and awareness and use of security and riskmanagement technologies.

E.Continuous Testing and Evaluation, Continuous Testing andEvaluation and Community Engagement.

Survey Question 9: Which organizations already have employee training andawareness programs related to data ethics and legal compliance in the context ofBig Data?

Survey Responses:A Google.B.Microsoft.C.IBM.

D.Facebook (Meta Platforms, Inc).E Amazon.

F.Universities and Research Institutions.G.Professional Organizations.

3 Assessment of the cost of conducting interview and survey methods.

diverse personnel costs (researchers, Cyber Security experts, lawyers, ethics experts),specialized software and tools, and costs of sending collection teams collecting data tomultiple locations, survey or questionnaire distribution costs, project management costs,and technical support costs.

o Detailed and accurate: Survey and interview methods allow collecting detailedinformation from experts and participants This is especially important in thefields of Big Data and Cyber Security, where accuracy is crucial.

o Explore and gain insight: This method allows you to explore non-obvious aspectsand gain a deeper understanding of the problem you study You can ask open-ended questions, seek out different perspectives, and identify hidden factors.o Direct feedback from participants: By having direct contact with participants, you

have the opportunity to gather their opinions, feedback, and suggestions This canhelp clarify and refine research over time.

o Suitable for unique projects: If your research project is unique and cannot useexisting sources of information, this method may be the best choice It allows youto generate new and unique data.

o Adjust over time: This method allows you to change the research direction andproject questions based on preliminary results and direct feedback fromparticipants, which makes the project more flexible.

o Require detailed and accurate information: In the field of Big Data and CyberSecurity, the accuracy and depth of information are important factors Survey andinterview methods allow you to collect detailed and accurate information fromexperts and participants, helping you better understand important aspects of thetopic.

o Project complexity and uniqueness: If your project is unique and informationcannot be found easily from an existing source, this method may be a goodchoice It allows you to generate new and unique data that meets your uniqueresearch needs.

o Explore and gain insight: This method allows you to explore non-obvious aspectsand gain a deeper understanding of the problem you study You can ask open-ended questions, seek out different perspectives, and identify hidden factors.o Direct feedback from participants: By having direct contact with participants, you

have the opportunity to gather opinions, feedback, and suggestions from them.This can help clarify and adapt research over time, ensuring that it meets theactual needs of participants.

o Adjust over time: This method allows you to change the research direction andproject questions based on preliminary results and direct feedback fromparticipants, which makes the project more flexible and scalable ability to adaptto changes in the field of research.

Criteria Interviews and Surveys Experimental Research

Research Objective andNature:

Typically used to collect

related to hiring staff,preparing questions and

management Costs mayvary depending on the scaleand scope of the research.

Often has lower costscompared to conductinginterviews and surveysbecause you mainly need toprepare and execute theexperiment with controlledfactors.

time for data collection,especially when dealing withmultiple participants.

Can be conducted within arelatively short time frame,

Offers the ability to controlvariables rigorously to

accuracy and researchvalidity.

4 Evaluate the method of implementation based on an ethical perspective.

o Ensure that all participants have the right to choose to participate or withdrawwithout any pressure or disadvantages They should also be fully informed aboutthe purpose, methods, and potential risks of the research.

o Ensure that participants have independence in deciding to participate and are notinfluenced by any coercion.

o Seek informed consent from all participants before collecting data This includesproviding comprehensive and clear information about the research's objectives,methods, and potential risks so they can make an informed decision to participate.

o Ensure that personal data of participants is protected and processed securely,preventing any intrusion into their privacy.

o Ensure that all research materials and information are distributed fairly and areaccessible to all participants, regardless of geographical location or language.

o Allow participants the right to withdraw from participation or requestmodifications in data collection if they deem it necessary.

o If necessary, ensure participant anonymity and data confidentiality.

o Provide technical support and ensure that participants understand theirparticipation and the importance of the research.

o Consider all potential impacts of the research, including effects on privacy,autonomy, and personal ethics of the participants.

o Ensure that the research complies with all relevant legal regulations and ethicalstandards related to the use of big data and participant involvement.

o Ensure that the research objectives do not harm or disadvantage participants andadhere to ethical research principles, such as the Belmont principles.

o Examine and disclose all sources of funding and potential conflicts of interest thatmay affect the independence and integrity of the research.

5 Analysis data

Survey Questions for "Cyber Security Risks":

Survey Question 1: In the process of collecting and processing big data, whatspecific cybersecurity risks has your organization identified?

the specific cybersecurity risks their organizations have identified in theprocess of collecting and processing big data The most common response,by far, is Sensitive Data Leakage, with 66.5% of respondents selecting thisoption This is likely due to the fact that big data often contains sensitiveinformation, such as personal data or financial data If this data is leaked,it could have serious consequences for the organization and its customers.

The next most common response is Insecure Analysis and Processing,with 13.4% of respondents selecting this option This refers to the risk thathackers could exploit vulnerabilities in the systems used to analyze andprocess big data This could allow them to access or modify the data, or todisrupt the operations of the systems.

The other options on the chart are also important cybersecurity risks toconsider Ransomware Attacks (12.1%) could encrypt an organization'sbig data, making it unusable until a ransom is paid Ineffective AccessControl (7.9%) could allow unauthorized users to access sensitive data.Dependency on Third Parties (7.9%) could introduce risks if the third-party vendors that an organization uses to collect or process big data arenot secure And Information Warfare and Disinformation (6.6%) couldinvolve using big data to manipulate public opinion or spread falseinformation.

Overall, the chart shows that there are a number of cybersecurity risks thatorganizations need to be aware of when collecting and processing bigdata It is important to take steps to mitigate these risks, such as byimplementing strong security controls, training employees oncybersecurity best practices, and having a plan for responding tocyberattacks.

Survey Question 2: How does your organization ensure the security of big data asit is transmitted over networks or stored on systems?

their organizations ensure the security of big data as it is transmitted overnetworks or stored on systems.

The most common response, with 54.8% of respondents, is J Periodicsecurity reviews This suggests that organizations place a high value onregularly assessing their big data security posture and making sure thattheir controls are effective.

Analyzing the remaining options:

E Update and patch security holes (12.6%) and A Data encryption(11.7%): These highlight the importance of proactive measures tomaintain system integrity and data confidentiality.

D Access rights management (9.6%): Focuses on controllingaccess to sensitive data, another crucial aspect of big data security.

The following options received lower percentages but should stillbe considered:

B Firewalls (6.7%): A fundamental layer of network defense,albeit not sufficient alone.

C Two-factor authentication (2FA) (3.3%): Adds an extra layer ofsecurity for user access, potentially underutilized.

F Continuous monitoring (2.5%): Can play a vital role in detectingand responding to threats promptly, potentially undervalued.

G Implement a strict security policy (2.1%): Having a clearframework for security practices is crucial, though the lowpercentage suggests room for improvement in policyimplementation.

H Backup and recovery (1.3%): Essential for disaster recovery butmay not be prioritized for ongoing data security.

I User training and awareness (0.8%): Surprisingly low, as userbehavior can significantly impact big data security.

Overall: Organizations are taking big data security seriously, but there's afocus on periodic reviews over continuous monitoring and user training.Technical controls like data encryption and patching are prioritized, butaccess control and user awareness could be strengthened Some essentialareas like backup and recovery and strict security policies seemunderemphasized based on the survey results.

Survey Question 3: "Which of the following cybersecurity risks do you considermost concerning in the context of Big Data use?

cybersecurity risk they consider most concerning in the context of big datause Here's a breakdown of the results:

Most concerning risks: DDoS attacks (59%): This is the most concerningrisk for the majority of respondents DDoS attacks can overwhelm anorganization's systems with traffic, making them unavailable to legitimateusers This can disrupt operations and cause financial losses Malwareattacks (37%): Malware can be used to steal, corrupt, or delete data It canalso be used to spy on users or take control of their systems Malwareattacks are a major concern for organizations that collect and storesensitive data.

Other concerns:

Data breaches (15.5%): A data breach is an unauthorized access toor disclosure of data Data breaches can have serious consequencesfor organizations, including financial losses, reputational damage,and legal liability.

Insider threats (10.5%): Insider threats are security threats thatcome from within an organization They can be caused byemployees, contractors, or even vendors Insider threats can bedifficult to detect and prevent, and they can cause significantdamage.

Less concerning risks:

Phishing attacks (3.4%): Phishing attacks are attempts to trickusers into revealing sensitive information, such as passwords orcredit card numbers While phishing attacks can be a problem, theyare not as big of a concern for big data security as other threats.Overall: The chart shows that organizations are most concerned aboutcybersecurity risks that can disrupt operations or cause data loss This isunderstandable, as big data is often critical to an organization's operations.The chart also shows that organizations are somewhat concerned aboutdata breaches and insider threats, but less concerned about phishingattacks.

Survey Question 4: What specific measures have been implemented to prevent ordetect cyber-attacks involving big data?

the specific measures they have implemented to prevent or detectcyberattacks involving big data.

Most common measures:

A Intrusion Detection System (IDS) and Application IntrusionDetection System (WAF) (54.8%): This is the most commonmeasure, with over half of respondents indicating they useIDS/WAF systems These systems monitor network traffic andapplication activity for suspicious patterns that could indicate anattack.

C Security monitoring system (SIEM) (27.2%): SIEM systemscollect and analyze data from various security sources to provide aholistic view of an organization's security posture They can helpto detect and respond to security incidents in real-time.

Other common measures:

D Network traffic monitoring system and User behaviormonitoring (17.4%): These systems monitor network traffic anduser activity to identify anomalies that could indicate an attack.

E Behavioral analytics based on machine learning and artificialintelligence (12.8%): This is a relatively new technology that usesmachine learning to analyze data and identify patterns that couldindicate an attack.

F Regular system and application updates and Penetration Testing(10.4%): Keeping systems and applications up to date with thelatest security patches is essential for preventing cyberattacks.Penetration testing can help to identify vulnerabilities in systemsbefore they are exploited by attackers.

Less common measures:

B Data encryption (6.2%): Encrypting data at rest and in transitcan help to protect it from unauthorized access.

G Data loss prevention (DLP) (4.1%): DLP systems can help toprevent data from being leaked or exfiltrated from an organization.Overall: The chart shows that organizations are taking a variety ofmeasures to prevent and detect cyberattacks involving big data The mostcommon measures focus on monitoring network traffic, user activity, andsystem logs for suspicious activity However, it is important to note thatno single measure is foolproof, and a layered approach to security isessential.

The chart shows the results of a survey that asked respondents how muchdamage data-related cybersecurity attacks cause The chart uses a pie chartto represent the percentage of each type of damage.

Main results:

The biggest loss is business interruption (70.3%) This may includeloss of access to data, loss of ability to deliver services or products,or loss of customer trust.

Other types of losses include loss of personal information (11.7%),loss of important business information (10.5%), and loss of money(10.5%).

Conclude: the results of this survey show that data-related cybersecurityattacks can cause serious damage to organizations Organizations needstrong security measures to protect their data from attack.

Survey Questions for "Legal and Ethical Trade-offs":

Survey Question 6: What existing legal frameworks are in place to adequatelyaddress the ethical challenges created by the use of big data?

The chart shows the results of a survey question asking what existing legalframeworks are in place to adequately address the ethical challengescreated by the use of big data.

Here are some observations I can make about the chart:

The most popular answer, with 36.7% of the vote, is C HealthInsurance Portability and Accountability Act (HIPAA) This

privacy of patients' medical data However, it is important to notethat HIPAA only applies to certain types of data, and it does notaddress all of the ethical challenges raised by big data.

The next most popular answer, with 17.7% of the vote, is A.General Data Protection Regulation (GDPR) The GDPR is aEuropean Union law that gives individuals more control over theirpersonal data It is a more comprehensive law than HIPAA, but itis not in effect in the United States.

The other answer choices received smaller percentages of the vote.This suggests that there is no single legal framework that is seen asbeing adequate to address the ethical challenges of big data.Overall, the chart suggests that there is a need for more comprehensivelegal frameworks to address the ethical challenges of big data HIPAA andthe GDPR are a good start, but they do not go far enough Other legalframeworks, such as those that protect consumer privacy and preventdiscrimination, may also need to be strengthened.

Survey Question 7: What are the standardized ethical guidelines specific to theuse of Big Data that have been widely adopted, in addition to legal regulations?

o The pie chart shows the results of a survey about standardized ethical guidelinesspecific to the use of Big Data, in addition to legal regulations The survey wasconducted with 79 respondents.

o Evaluation: Based on the analysis mentioned, the following observations can bemade about the chart:

First, standardized ethical guidelines specific to the use of Big Data arestill not widely adopted The most popular guideline is the Ethicalprinciples of Big Data Analytics with 31.6%, followed by the ISO/IEC27001 standard with 22.8% These guidelines are all developed byreputable organizations, but they are still not widely implemented inpractice.

Second, standardized ethical guidelines specific to the use of Big Dataneed to be further developed and disseminated These guidelines need tobe designed to address the specific ethical challenges of using Big Data,such as protecting privacy, preventing discrimination, and ensuringtransparency and accountability.

Survey Question 8: How can we ensure that an organization's use of big data doesnot violate ethical principles or cause negative consequences for society?