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In this course you have effectively written a mock chapter 1 and 3 as well as a theoretical framework and literature review funnel

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In this course you have effectively written a mock chapter 1 and 3 as well as a theoretical framework and literature review funnel. It is time to show off your hard work in the form of a paper showcase using the official  dissertation template. The purpose of this extra credit is two-fold. One is to celebrate your accomplishments in this course, but the other is to familiarize you with the university's expectations for a published dissertation.

Directions:

1. Use the attached dissertation template to copy over your chapters 1 and 3 and your chapter two theoretical framework and funnel into the template.
   1. UC Dissertation template, APA 7th edition V9.15.docx
2. Post your completed paper to the 8.2 discussion board.

A reply is not necessary to earn the extra credit, but you are welcome to reply to others. This is worth 10 bonus points.

Your Approved Dissertation Title Here The entire document should be double spaced with Times 12 Font. Type your dissertation approved title on line 5. For the header, Type: your abbreviated title in all capital letters. (No more than 50 characters, including spaces). The page number is also in the header, flush right starting with 1. 1 Your Approved Dissertation Title Here in Upper and Lowercase Letters First and Last Name Type only your first and last name on line 6. Do not list other degrees. University of the Cumberlands Type University of the Cumberlands on line 7. Month and Year of Graduation Month and Year only should be typed on line 8. Your Approved Dissertation Title Here Include a copy of the signed form. 2 Approval for Recommendation This dissertation is approved for recommendation to the faculty and administration of the University of the Cumberlands. Dissertation Chair: Dissertation Evaluators: 3 Your Approved Dissertation Title Here Acknowledgements is where you thank those who have helped you achieve this goal. Acknowledgments There are many to whom a debt of gratitude is owed for their assistance in conducting this research…. (It is appropriate to thank key faculty, friends, and family members, as well as ministers and God. It is advisable to limit the comments to one page) 4 Your Approved Dissertation Title Here Abstract This study examined the differences……………… Do not indent the first paragraph in the abstract. No longer than 250 words. The word “Abstract” should be centered and typed in 12-point Times New Roman. 5 Your Approved Dissertation Title Here Table of Contents Chapter One: Introduction Overview……………………………………………………………………………...1 Background and Problem Statement………………………………………………….2 6 Your Approved Dissertation Title Here List of Tables Table 1: Name of the Table…………………………………………………………………1 7 Your Approved Dissertation Title Here List of Figures Figure 1: Name of the Figures …………………………………………………………………1 8 Your Approved Dissertation Title Here Chapter One Introduction Overview Indent each new paragraph. Write an overview to your study here. Background and Problem Statement Indent each new paragraph. Write your background and problem statement here. Purpose of the Study Indent each new paragraph. Write your next section here. Significance of the Study Indent each new paragraph. Write your next section here. Discuss the link to leadership in the purpose and significance of the study. Research Questions Indent each new paragraph. Write your next section here. Theoretical Framework Indent each new paragraph. Write your next section here. Limitations of the Study Indent each new paragraph. Write your next section here. Assumptions Indent each new paragraph. Write your next section here. Definitions Transformational leadership: The………(in-text citation) Summary For definitions, state the term in italics followed by a colon. The actual definition should be without italics. All definitions should include an in-text citation for the reference source. Indent each new paragraph. Write your summary of chapter one here. 9 Your Approved Dissertation Title Here The literature review should be a minimum of 20 pages of synthesized literature but will normally require many more pages. Chapter Two Review of Literature Introduction Indent your introduction. Introduce your thesis map here for your dissertation topic and literature review you will cover. Main Heading (level 2 heading) Subheading should be flush left, Bold italic, Title Case Heading (level 3 heading) Subheading should be indented, boldfaced, Title Case Heading, ending with a period. (level 4 heading) Summary 10 Your Approved Dissertation Title Here Chapter Three Procedures and Methodology Introduction Indent each new paragraph. Write your next section here. Research Paradigm Discuss if the study is qualitative or quantitative in the research paradigm. Indent each new paragraph. Write your next section here. Research Design Indent each new paragraph. Write your next section here. Sampling Procedures and or/ Indent each new paragraph. Write your next section here. Data Collection Sources Indent each new paragraph. Write your next section here. Statistical Tests Indent each new paragraph. Write your next section here. Summary Indent each new paragraph. Write your next section here. In Data Collection Resources section, reference Informed Consent and IRB approval placed in Appendices. 11 Your Approved Dissertation Title Here Chapter Four Research Findings Introduction Indent each new paragraph. Write your next section here. Participants and Research Setting Indent each new paragraph. Write your next section here. Analyses of Research Questions Indent each new paragraph. Write your next section here. Supplementary Findings (if any) Indent each new paragraph. Write your next section here. Summary Indent each new paragraph. Write your next section here. List and number research questions one at a time. 12 Your Approved Dissertation Title Here Chapter Five Summary, Discussion, and Implications Introduction Indent each new paragraph. Write your next section here. Practical Assessment of Research Questions Indent each new paragraph. Write your next section here. Limitations of the Study Indent each new paragraph. Write your next section here. Indent each new paragraph. Write your next section here. Implications for Future Study Indent each new paragraph. Write your next section here. Summary Indent each new paragraph. Write your next section here. In the Practical Assessment of Research Question section, focus in this section on how your research question findings align or differ from scholarly published literature on the topic. Discuss the link to leadership. 13 Your Approved Dissertation Title Here All citations and references must match throughout the dissertation. Follow APA guidelines on formatting. References References with hyperlinks such as to retrieval sources or DOIs, should include the “live” link to the source. 14 Your Approved Dissertation Title Here Appendix A Tables Appendices – This section contains tables, figures, and possible data sources that could not be placed in the text of the paper due to its size, as well as copies of consent forms and IRB letters. 15 Your Approved Dissertation Title Here Appendix B Figures 16 Your Approved Dissertation Title Here Appendix C Consent Forms Include a copy of the letter/form used to obtain consent from participants in the study. Do not include consent forms from organizations that provided permission to gather data. 17 Your Approved Dissertation Title Here Appendix D IRB Approval Cyber Security in Healthcare Research topic: Enhancing Cyber Security in Healthcare -With the Help of Machine Learning Research question: How can machine learning help to improve and protect cybersecurity in learning? Cybersecurity in health care involves protecting medical information, technologies, and new medical processes by introducing programs, data, and devices from unauthorized access. Over the years, technology has improved, which has significantly impacted many national sectors. For instance, in healthcare, cybersecurity has played an essential role in its improvement; not only has it helped the organization protect its patient safety and security, but it has also ensured that it is effective and quality health care to every patient. Health care organizations are more vulnerable and are significantly targeted by cyber-attack because they have expensive information and high intelligence value. Health care organizations have essential information such as patients' protected health care information, personal identification information, for example, intellectual properties, social security number, and financial information like credit card and bank accounts' numbers; this are data that are highly targeted by the cyber attacker (Tschider el at 2017). Hacking health care records causes high risks to patients' privacy, safety, and care delivery. For these reasons, health care organizations need to develop machine learning that will improve and provide cybersecurity. Machines' learning means giving computers the ability to access security threats in your organization and focus on valuable and strategic tasks. Medical organizations can enhance cybersecurity in health care with the help of machine learning in the following ways. First, machine learning has algorithms that detect hackers faster through agency networks and stops attacks; this protects health care organizations from cyber-attack and hacking of important information. Secondly, machine learning help health analyst to detect seizures, analyze networks protection of endpoints and protect vulnerable information from being assessed. Machine learning systems filter data and go through human analyst and gives alert in case of attacks. Additionally, machine learning detects repetitive tasks; this ensures that the staff focuses on more crucial work and focuses on high-value decision-making activities. Machine learning can protect many health organizations from cyber-attacking actions. Reference Tschider, C. A. (2017). Enhancing cybersecurity for the digital health marketplace. Annals Health L., 26, 1. 1 Quantitative Instrument For Research 2 Research question How machine learning helps in the improvement and protection of cyber security in Healthcare. Cybersecurity in health care involves protecting medical information, technologies, and new medical processes by introducing programs, data, and devices from unauthorized access. Over the years, technology has improved, which has significantly impacted many national sectors. For instance, in healthcare, cybersecurity has played an essential role in its improvement; not only has it helped the organization protect its patient safety and security, but it has also ensured that it is effective and quality health care to every patient. The following is a quantitative research instrument used to collect various types of data. What has the presence of high-volume data sets for multiple clients incorporated? o Increasingly common third-party involvement. o Big data multiplies the probability of harm. o All of the above. What has encouraged organizations to o Technological advancements. produce connected digital health services? o Rising demand to develop low-cost care solutions. o All of the above. What percentage of the people owns a o 64% smartphone in the US? o 22% o 44% 3 How has the high percentage of people owning smartphones affected the possibilities o It has sparked the tremendous growth in digital health care. for delivering health care and improving o It has led to data loss. general health? o It has improved clarity of organizations. o It has precipitated increased risks. How many mobile healthcare applications o 165,000 had been developed by the year 2015? o 150,000 o 100,000 o 50,000 What are the fields which were focused on by o Women's health and pregnancy. the mobile healthcare applications? o Medication reminders and information. o Disease-specific treatment. o All of the above. What do the digital health industry offer for malevolent actors? o Limitless chances for sensitive data disclosure and financial benefit. o Limited chances for sensitive data disclosure and financial benefit. What is the value of health data type for an o $10 illegal trade per record? o $4 o $5 o $20 4 What percentage of medical data is involved o 45% in theft incidents? o 44% o 22% o 64% What percentage of health data is affected by o 44% data breaches? o 22% o 12% o 10% How many data records were breached in the o One billion. year 2014? o Three billion o Four billion. o Ten billion How many data records were breached in the o Eighty million year 2015? o Ten million o One million o Two million How many research topics were consulted for o 3 this particular study? o 4 o 7 o 1 How many papers were evaluated for this o 17 particular study? o 23 o 15 5 o 11 o 5 years How many years have passed since the o 3 years worldwide digital health broke out at a o 7 years breakneck pace? o 4 years What are the advances that have led to the o Internet of Things (IoT) breakthrough in digital health sector? o Increased smartphone penetration. o Big Data investment o All of the above What has increased the risk of cybersecurity threats exploiting system vulnerabilities? o Significant investments in technologies. o Improved eHealth. o Improved patient connectivity. What are the dangers brought about by the o Health data loss. advancement in eHealth technology? o Patient physical safety being jeopardized. o All of the above. Reason for the choice of the quantitative instrument above. For each instance stated above, the study is focused on quantifying the variable; enhancing cybersecurity in the healthcare sector. Parameters used in measurement are the only factors that changes. Each instance states a diverse quantitative sample question that requires to be 6 determined using a different parameter. The answers for the quantitative survey questions defines purposes for the research and also quantifies the various topics of analysis. References Tyagi, A. (2021). Healthcare-Internet of Things and Its Components: Technologies, Benefits, Algorithms, Security, and Challenges. In Optimizing Health Monitoring Systems With Wireless Technology (pp. 258-277). IGI Global. https://www.igi-global.com/chapter/healthcare-internet-of-things-and-its-components/267408 Durneva, P., Cousins, K., & Chen, M. (2020). The current state of research, challenges, and future research directions of blockchain technology in patient care: Systematic review. Journal of medical Internet research, 22(7), e18619. https://www.jmir.org/2020/7/e18619 Morabito, R., Cozzolino, V., Ding, A. Y., Beijar, N., & Ott, J. (2018). Consolidate IoT edge computing with lightweight virtualization. Ieee network, 32(1), 102-111. 7 https://ieeexplore.ieee.org/abstract/document/8270640 Peregrin, T. (2021). Managing HIPAA Compliance Includes Legal and Ethical Considerations. Journal of the Academy of Nutrition and Dietetics, 121(2), 327-329. https://jandonline.org/article/S2212-2672(20)31501-X/fulltext Abstract 1 Abstract Bibliographic Citation Tschider, C. A. (2017). Enhancing cybersecurity for the digital health marketplace. Annals Health L., 26, 1. Author Qualifications Professor Charlotte Tschider lectures at the Loyola University Chicago School of Law as an assistant professor. Her principal research interests are in artificial intelligence, cybersecurity law, and information privacy, with a particular emphasis on the global healthcare industry. For nearly two decades, Tschider worked for Carlson Wagonlit Travel, Target Corporation, and most lately, Medtronic Corporation in different upper consultative and management capacities in IT, privacy, cybersecurity, and legal compliance. She is a Certified CISSP from ISC2 and an IAPP Certified Information Privacy Professional (CIPP) for both the United States and Canada. Research Concern The worldwide digital health market has risen at a breakneck pace in the last five years, thanks to advances in IoT, increased smartphone penetration, and Big Data investment. Major players in eHealth have lately made significant investments in technologies that improve patient Abstract 2 connectivity and convenience while also increasing the risk of cybersecurity threats exploiting system vulnerabilities. While eHealth technologies assist both healthcare providers and patients, they also introduce new dangers, which could result in both health data loss and patient physical safety being jeopardized. Because of the presence of high-volume data sets for multiple clients, often linked over the open Network or home networks with unknown settings, the combination of technology connectivity with increasingly common third-party involvement via the cloud, Software as a Service (SaaS), and big data multiplies the probability of harm. This article will explore the potential vulnerabilities connected with various health information systems in order to develop a comprehensive solution to the prevalent cybersecurity threats now afflicting the healthcare industry in the United States. Research Purpose This paper aims to demystify the science of cybersecurity and proposes a common-sense approach to improve clarity for organizations developing medical device products for the digital health industry. The author describes the existing context for regulatory activity and the conditions precipitating increased risk. She also describes in detail duplicative and frequently incomplete coverage within the existing regulatory framework regulated by the FDA and the OCR. Finally, the author proposes an adapted FDA regulatory framework to simplify and clarify the regulation of the digital health marketplace. Precedent Literature Organizations have been encouraged to produce connected digital health services as a result of technological advancements and rising demand to develop low-cost care solutions. With 64% of persons in the United States owning a smartphone, the possibilities for delivering health Abstract 3 care and improving general health have sparked tremendous growth in the digital healthcare sector. By 2015, 165,000 mobile health applications had been developed, with 22% of them focused on women's health and pregnancy, medication reminders and information, and diseasespecific treatment (DELOITTE, 2015). For malevolent actors, the digital health industry offers nearly limitless chances for sensitive data disclosure and financial benefit. Health data is now the most valuable data type for an illegal trade sale, fetching $10 per record; medical data is involved in 45 percent of identity theft incidents, and health data is affected in 44% of data breaches (Kristen, 2014). Health data is used by hackers and other hostile actors to submit bogus medical claims to insurance companies, file tax returns, and acquire other perks, such as free medicines. In 2014, one billion personal data records were breached in a single year, setting a new record; in 2015, Anthem, Inc. revealed a massive data breach affecting eighty million health insurance subscribers, the greatest compromise involving health information to date (Mills & Harclerode, 2017). Research Methodology The review looked at research articles that had been published in scientific journals in the areas of healthcare systems, potential vulnerabilities of healthcare systems, and possible solutions from 1993 to 2019. A search of ten electronic databases was conducted using a set of keywords, including cybersecurity and healthcare systems. Instrumentation Based on the three research topics, the publications were grouped into three primary categories. 17 papers were evaluated. The studies were largely cross-sectional in nature and Abstract 4 focused on the vulnerabilities of healthcare systems to cyber threats as well as potential solutions. Findings According to the study, the current legal framework governing the digital health sector is insufficient to mitigate and manage cybersecurity risk. Even though a framework could strengthen cybersecurity in the digital health business, there is presently no clear and comprehensive regulatory duty. Furthermore, the study found that the FTC, ONC, OCR, and FDA, have overlapping administrative duties, resulting in a lack of clear cybersecurity direction and accountability for digital health providers, leaving institutions with very few choices other than creating regulations irregularly and autonomously. Furthermore, because it is a pull, demand-side compliance paradigm, the HIPAA model cannot adequately regulate digital health cybersecurity. Conclusion The digital health marketplace demands a clear, balanced approach to consumer protection and data privacy in the face of an upsurge in digital health service and product investment increasingly acknowledged cybersecurity risks and a disjointed regulatory framework. While both legal and technology experts have advocated for enhanced cybersecurity action and investigation, neither has taken a multi-disciplinary strategy, combining technology and law to establish a regulatory framework for digital health. The framework needed to protect patients while also providing a clear vision for firms manufacturing digital health services and products will be created by exploiting present digital US FD processes with increased Abstract monitoring. The Federal Food, Drug, and Cosmetic Act are well-positioned to oversee cybersecurity in the digital health business in the United States. 5 Abstract 6 References Kristen Fischer, (Sept. 28, 2014). The7 Biggest Health Data Breaches in the US (So Far), HEALTHLINE. Retrieved from: http://www.healthline.com/health-news/seven-biggesthealth-data-breaches092814; DELOITTE (2015). Accelerating the Adoption of Connected Health. Retrieved from: http://www.del oitte.com. Mills, J. L., & Harclerode, K. (2017). Privacy, Mass Intrusion, and the Modern Data Breach. Fla. L. Rev., 69, 771. Research Methodology 1 Chapter III: Research Methodology 2 Chapter III: Research Methodology Introduction As the technology advance in different sectors, there have been increased data breaches in various organizations carried out by hackers who need customers' personally identifiable information. The healthcare sector keeps this kind of data for their customers, which needs to be protected, which can be done by developing health sector cybersecurity. A.I. helps in the improvement and insurance of network safety in healthcare. Network safety in medical services includes securing clinical data, advancements in the medical sector, and new clinical cycles by presenting projects, information, and gadgets to unapproved access. Innovation has improved, which has affected numerous public areas. For example, in medical care, online protection has assumed a fundamental part in its improvement. Not only has it assisted the association with securing its patients' wellbeing and security, but it has likewise guaranteed that it is viable and quality medical care for each patient. The theme behind this paper is to provide information on how the health sector can shield itself from information penetration as per the Identity theft resource center in 2019. The methods that can uncover data and worker mindfulness will assist the health sector with protection from being assaulted by different sources. Research Paradigm The study on the cause of data breaches in the health sector and its implications used a quantitative research paradigm. Quantitative research has various goals, which are to establish ontology, phenomenology, logic, and epistemology. The study applied all those to enable the interviewee to provide multiple important information in the study, such as mobile healthcare applications, the number of people with smartphones, and other quantitative information required 3 as presented in the questionnaire. Logical, ontological, and further research will enable us to solve the problem effectively. Quantitative analysis is of great importance. The study is centered around evaluating the variables and upgrading online protection in medical care information (Bryman & Bell, 2015). The boundaries utilized in estimation are the solitary factors that change. Each occurrence expresses an assorted quantitative example question that needs to be resolved by using an alternate border. The responses to the quantitative review questions characterize the exploration purposes and evaluate the different subjects of investigation. Research Design To effectively resolve a research problem, reliable and sufficient data is required, both qualitative and quantitative data, to determine the root cause of data breaching in the health sector (Alawneh, 2008). I developed a questionnaire with both open- and close-ended inquiries and the entirety of this was controlled through a survey tool. The majority of the interviewee's reactions will be recorded when attempting to clarify their understanding of a penetrate and how information lost can be characterized into purposeful dangers and coincidental dangers, as this account was spelled out for additional examination utilizing otter A.I. Besides, every meeting of the members will be endured about an hour and a half, depending upon the assignments being performed. Data collection and Sampling Procedures Every interviewee considered in the data collection process will have to have worked or is currently working in the health sector. They will read and mark an assent structure clarifying the reason for the exploration and were given the alternative to skipping an inquiry if they feel awkward responding to a question. Members enlisting will be through promotions from web- 4 based media and from known contacts whose training and identified work experience with the examination that was being led. Their reactions will be inclined to in two segments, which are quantitative and subjective. While investigating the personal information from the poll, we directed a topical examination to more readily dissect the members' reactions to the open-ended inquiries (Namey et al.,2012). For the most part, the analyst will be centered around discovering a specific pattern or a comparable thought to help layout the examination. It will forester some codes to recognize equivalent subjects and standards. Then, at that point, they began to assemble an underlying rundown or perspective on these codes to distinguish the examples wherein the members discussed insider dangers and information breaks. The selection of words and searching for electives will determine various perspectives/experiences on information penetration. Statistical Tests Summary Descriptive and inferential data is used to analyze data from the healthcare sector; this is qualitative research. This kind of data is kept for customers and needs to be protected, which can be done by developing health sector cybersecurity. T-test will be employed to analyze individual responses on data breaching in which the TCAP test will derive the composite scores. This will establish statistical evidence of a relationship between machine learning and data protection in healthcare. Thus, this will be undertaken under a 5% significance level, and the data be presented in tables and a statistical test matrix. Besides, correlations will be utilized to establish the connection between healthcare data security and machine learning and the percentage of health records breached and affected by the data breach. Lastly, Chi-square will be employed to determine the dangers brought about by technological advancement in healthcare and the proportion of high-volume data set for a vast number of clients that have been leaked through 5 technology. Hence, a combination of these statistical tools of testing will help to establish the underlying issue of a data breach in the healthcare sector as the technology advance. References 6 Alawneh M, Abbadi IM (2008). Preventing information leakage between collaborating organizations. In: Proceedings of the 10th International Conference on Electronic Commerce, ICEC. Bryman, A., & Bell, E. (2015). Business Research Methods (4th ed., p. 160). Oxford, England: Identity theft resource center (2019). https://www.idtheftcenter.org/ data-breaches/ Namey E. Guest G., MacQueen K. M. (2012). Introduction to Applied Thematic Analysis. Applied Thematic Analysis. SAGE Publications. Oxford University Press. Cyber Security in Healthcare Research topic: Enhancing Cyber Security in Healthcare -With the Help of Machine Learning Research question: How can machine learning help to improve and protect cybersecurity in learning? Cybersecurity in health care involves protecting medical information, technologies, and new medical processes by introducing programs, data, and devices from unauthorized access. Over the years, technology has improved, which has significantly impacted many national sectors. For instance, in healthcare, cybersecurity has played an essential role in its improvement; not only has it helped the organization protect its patient safety and security, but it has also ensured that it is effective and quality health care to every patient. Health care organizations are more vulnerable and are significantly targeted by cyber-attack because they have expensive information and high intelligence value. Health care organizations have essential information such as patients' protected health care information, personal identification information, for example, intellectual properties, social security number, and financial information like credit card and bank accounts' numbers; this are data that are highly targeted by the cyber attacker (Tschider el at 2017). Hacking health care records causes high risks to patients' privacy, safety, and care delivery. For these reasons, health care organizations need to develop machine learning that will improve and provide cybersecurity. Machines' learning means giving computers the ability to access security threats in your organization and focus on valuable and strategic tasks. Medical organizations can enhance cybersecurity in health care with the help of machine learning in the following ways. First, machine learning has algorithms that detect hackers faster through agency networks and stops attacks; this protects health care organizations from cyber-attack and hacking of important information. Secondly, machine learning help health analyst to detect seizures, analyze networks protection of endpoints and protect vulnerable information from being assessed. Machine learning systems filter data and go through human analyst and gives alert in case of attacks. Additionally, machine learning detects repetitive tasks; this ensures that the staff focuses on more crucial work and focuses on high-value decision-making activities. Machine learning can protect many health organizations from cyber-attacking actions. Reference Tschider, C. A. (2017). Enhancing cybersecurity for the digital health marketplace. Annals Health L., 26, 1. Abstract 1 Abstract Bibliographic Citation Tschider, C. A. (2017). Enhancing cybersecurity for the digital health marketplace. Annals Health L., 26, 1. Author Qualifications Professor Charlotte Tschider lectures at the Loyola University Chicago School of Law as an assistant professor. Her principal research interests are in artificial intelligence, cybersecurity law, and information privacy, with a particular emphasis on the global healthcare industry. For nearly two decades, Tschider worked for Carlson Wagonlit Travel, Target Corporation, and most lately, Medtronic Corporation in different upper consultative and management capacities in IT, privacy, cybersecurity, and legal compliance. She is a Certified CISSP from ISC2 and an IAPP Certified Information Privacy Professional (CIPP) for both the United States and Canada. Research Concern The worldwide digital health market has risen at a breakneck pace in the last five years, thanks to advances in IoT, increased smartphone penetration, and Big Data investment. Major players in eHealth have lately made significant investments in technologies that improve patient Abstract 2 connectivity and convenience while also increasing the risk of cybersecurity threats exploiting system vulnerabilities. While eHealth technologies assist both healthcare providers and patients, they also introduce new dangers, which could result in both health data loss and patient physical safety being jeopardized. Because of the presence of high-volume data sets for multiple clients, often linked over the open Network or home networks with unknown settings, the combination of technology connectivity with increasingly common third-party involvement via the cloud, Software as a Service (SaaS), and big data multiplies the probability of harm. This article will explore the potential vulnerabilities connected with various health information systems in order to develop a comprehensive solution to the prevalent cybersecurity threats now afflicting the healthcare industry in the United States. Research Purpose This paper aims to demystify the science of cybersecurity and proposes a common-sense approach to improve clarity for organizations developing medical device products for the digital health industry. The author describes the existing context for regulatory activity and the conditions precipitating increased risk. She also describes in detail duplicative and frequently incomplete coverage within the existing regulatory framework regulated by the FDA and the OCR. Finally, the author proposes an adapted FDA regulatory framework to simplify and clarify the regulation of the digital health marketplace. Precedent Literature Organizations have been encouraged to produce connected digital health services as a result of technological advancements and rising demand to develop low-cost care solutions. With 64% of persons in the United States owning a smartphone, the possibilities for delivering health Abstract 3 care and improving general health have sparked tremendous growth in the digital healthcare sector. By 2015, 165,000 mobile health applications had been developed, with 22% of them focused on women's health and pregnancy, medication reminders and information, and diseasespecific treatment (DELOITTE, 2015). For malevolent actors, the digital health industry offers nearly limitless chances for sensitive data disclosure and financial benefit. Health data is now the most valuable data type for an illegal trade sale, fetching $10 per record; medical data is involved in 45 percent of identity theft incidents, and health data is affected in 44% of data breaches (Kristen, 2014). Health data is used by hackers and other hostile actors to submit bogus medical claims to insurance companies, file tax returns, and acquire other perks, such as free medicines. In 2014, one billion personal data records were breached in a single year, setting a new record; in 2015, Anthem, Inc. revealed a massive data breach affecting eighty million health insurance subscribers, the greatest compromise involving health information to date (Mills & Harclerode, 2017). Research Methodology The review looked at research articles that had been published in scientific journals in the areas of healthcare systems, potential vulnerabilities of healthcare systems, and possible solutions from 1993 to 2019. A search of ten electronic databases was conducted using a set of keywords, including cybersecurity and healthcare systems. Instrumentation Based on the three research topics, the publications were grouped into three primary categories. 17 papers were evaluated. The studies were largely cross-sectional in nature and Abstract 4 focused on the vulnerabilities of healthcare systems to cyber threats as well as potential solutions. Findings According to the study, the current legal framework governing the digital health sector is insufficient to mitigate and manage cybersecurity risk. Even though a framework could strengthen cybersecurity in the digital health business, there is presently no clear and comprehensive regulatory duty. Furthermore, the study found that the FTC, ONC, OCR, and FDA, have overlapping administrative duties, resulting in a lack of clear cybersecurity direction and accountability for digital health providers, leaving institutions with very few choices other than creating regulations irregularly and autonomously. Furthermore, because it is a pull, demand-side compliance paradigm, the HIPAA model cannot adequately regulate digital health cybersecurity. Conclusion The digital health marketplace demands a clear, balanced approach to consumer protection and data privacy in the face of an upsurge in digital health service and product investment increasingly acknowledged cybersecurity risks and a disjointed regulatory framework. While both legal and technology experts have advocated for enhanced cybersecurity action and investigation, neither has taken a multi-disciplinary strategy, combining technology and law to establish a regulatory framework for digital health. The framework needed to protect patients while also providing a clear vision for firms manufacturing digital health services and products will be created by exploiting present digital US FD processes with increased Abstract monitoring. The Federal Food, Drug, and Cosmetic Act are well-positioned to oversee cybersecurity in the digital health business in the United States. 5 Abstract 6 References Kristen Fischer, (Sept. 28, 2014). The7 Biggest Health Data Breaches in the US (So Far), HEALTHLINE. Retrieved from: http://www.healthline.com/health-news/seven-biggesthealth-data-breaches092814; DELOITTE (2015). Accelerating the Adoption of Connected Health. Retrieved from: http://www.del oitte.com. Mills, J. L., & Harclerode, K. (2017). Privacy, Mass Intrusion, and the Modern Data Breach. Fla. L. Rev., 69, 771. PROJECT DRAFT ON CHALLENGES OF INTERNET AS A TOOL FOR TEENAGERS The research project looks at the internet as a holistic tool that is used throughout the world for communication and socialization processes. A teenager is someone who is between 13 and 19 years old. The ages vary depending on each country. STATEMENT OF THE PROBLEM A correlation studies to assess the knowledge and self-expressed at how the internet has been a menace to the younger generation. Introduction The internet is a networking system that connects everybody from all corners of the earth. Through the internet, people can share information that is disturbing from anywhere in the world. Some of the major disadvantages of the internet include; health issues like loss of eyesight due to daily look on the laptop and phone screen. Equally, issues like hacking and theft always emerge when one is always on the internet. Additionally, weight gain can be experienced since one doesn't walk or exercise. LITERATURE REVIEW Background of the information The internet started with the introduction of the computer in the 1960s that was used to connect people with close and similar interests. Before the coming of the internet, people used traditional methods like groups to pass information to loved ones. Letter writing was also a common form of sending emails to those who were overseas and sometimes could take very many months before the information is delivered. The internet, therefore, makes it more accessible to speak to people thousands of miles away. It is also a platform where we get to share our thoughts about certain issues like the Covid 19 pandemic. CONCLUSION Teenagers need to be able to identify acceptable and unacceptable online content independently. This material might include: pornography or sexually explicit content in music videos, movies or online games, real or simulated violence, hate sites, among other dangerous sites. With digitalization, teenagers should be allowed to use the internet only under the watch of parents or guardians. Caretakers can also employ a scheme where the signal detects dirty content and turns it off immediately. REFERENCES https://raisingchildren.net.au/teens/entertainment-technology/cyberbullying-onlinesafety/internet-safety-teens https://www.usg.edu/galileo/skills/unit07/internet07_02.phtm https://www.canterbury.ac.nz/library/# PROJECT DRAFT ON CHALLENGES OF INTERNET AS A TOOL FOR TEENAGERS: ANNOTATED BIBLIOGRAPHY Kokka, I., Mourikis, I., Nicolaides, N. C., Darviri, C., Chrousos, G. P., KanakaGantenbein, C., & Bacopoulou, F. (2021). Exploring the Effects of Problematic Internet Use on Adolescent Sleep: A Systematic Review. International Journal of Environmental Research and Public Health, 18(2), 760. Kokka et al. (2021) ascertain the vast problematic internet use on teenage sleep and general mental and health development. Sleep as a cognitive teenage development factor is crucial to ensure good mental and physical development. Over the years, sleep disorders have been on the rise, and the immediate cause resonantly remaining to be the easy access and overuse of the internet. Kokka et al. l (2021) extensively investigate the sleep behavior among the 10-19 age group using the PRISMA guidelines of publications in the last decade. Insomnia symptoms were found to be provoked by uncontrolled internet use, thus affecting teenage sleep quantity and quality. This study is thus crucial in understanding the teenage behaviors influenced by overconsumption of the internet. Understandably, teenage leisure, academic reasoning, and relationships are embedded in the content on the internet. Responsible internet use is hence necessary to be taught to these teenagers to eradicate such negativities. Bonetti, F., & Tonelli, S. (2021, April). Challenges in Designing Games with a Purpose for Abusive Language Annotation. In Proceedings of the First Workshop on Bridging HumanComputer Interaction and Natural Language Processing (pp. 60-65). The online gaming industry targets the teen often targets. Online gaming is an everyday leisure activity among teenagers. Good graphics are solicitors for a massive audience among the teen group. Bonnetti and Tonelli, however, in the paper discuss the effect and several challenges of the development of the three-dimensional games aimed at raising cyberbullying awareness and massive use of abusive languages. The writing is essential, as its focus on the teen as significant consumers of the gaming industry. The designs and graphics are, however, denature the teenager's development by structuring their linguistics dictions. Abusive and hostile actions in these games negatively shape physical and emotional behavior. Guinta, M. R., & John, R. M. (2018). Social media and adolescent health. Pediatric Nursing, 44(4), 196-201. Guinta and John, in the pediatric Nursing journal, explore the exponential growth of social media among teens and its implication in their health. They describe the positive impacts but intensely identify the detrimental use of the internet to teenagers and young adults. The internet complexities not only trauma the teenager but also contribute to their hostile and uncontrolled physical behavior. They identify cyberbullying as a significant cause of mental instability among teenagers. The journal hence cements itself in the research by bringing the atrocities that teenagers face. Moral decadence, improper communication, low self-esteem, and the furthest suicidal mentality among teenagers are drawn from the internet as they deem them ethical. Chung, T. W., Sum, S. M., & Chan, M. W. (2019). Adolescent internet addiction in Hong Kong: prevalence, psychosocial correlates, and prevention. Journal of Adolescent Health, 64(6), S34-S43. Chung et al. reviewed the prevalence of the internet among Hong Kong teenagers. Reviewing several publications of up to 2018, their study found a prevalence of 3% -26.8% among these teenagers and adolescents. Internet addiction exposing teenagers to suicidal thinking, poor academic performance, depression, low self-esteem, to poor parental-child relationships. The study brings out a clear distinction between the two types of teenagers. The group that isolates themselves from the internet and the other group very deep into the internet. The study is hence helpful for it brings out the negativities of this addiction. Improper physiological developments, poor academic performance, depression, disorganized family relationships, and poor teen development are major results of internet addiction, as per the study. These negativities lead to restrictive parenting that eventually affects teen development. Carreiro, S., Chai, P. R., Carey, J., Lai, J., Smelson, D., & Boyer, E. W. (2018). mHealth for the detection and intervention in adolescent and young adult substance use disorder. Current addiction reports, 5(2), 110-119. Carreiro et al. assess the influence of social media on Substance abuse and mental health among teenagers. Their review highlighted the implication of the internet in the detection and treatment of substance abuse. Their study further acknowledges the detriments of the internet on the mental health of the teen with a focus on substance abuse. The teen learns various ways to abuse substances through videos and other graphics on the internet. Their study is crucial to address the recovery measures and other proper treatment of substance abuse without any discriminations. Their study is hence essential to structure treatment programs and efforts to elevate the teenagers from the negative internet implications. Gül, H., F?rat, S., Sertçelik, M., Gül, A., Gürel, Y., & K?l?ç, B. G. (2019). Cyberbullying among a clinical adolescent sample in Turkey: effects of problematic smartphone use, psychiatric symptoms, and emotion regulation difficulties. Psychiatry and Clinical Psychopharmacology, 29(4), 547-557. Gul et al. acknowledge the prevalence of cyberbullying due to increased use of the internet over time. Their student identity availability of internet access tools to strategically increasing internet interaction among teenagers. They define cyberbullying and cyber victimization as a significant concern among teen development in the millennium age. They hence examine the psychiatric signs, emotional symptoms, and difficulties among teenagers. Their research is indicating a prevalence of about 62.6% and 53.3%, cyber victimization, and bullying, respectively, among teenagers and young adults. Their research is hence essential as it identifies the strategic tools used to access the internet that is Smartphones. Ballarotto, G., Volpi, B., Marzilli, E., & Tambelli, R. (2018). Adolescent Internet abuse: A study on the role of attachment to parents and peers in a large community sample. BioMed research international, 2018. Ballarotto et al. confirm the teenagers and adolescents as the primary users of new technologies. They also highlight the use of virtual technologies as an obstacle to their development. In the article, they identify internet addiction as a factor for a poor relationship among teenagers and their parents. The internet limits their relationship profiles and abuses their peer relationships. Thteenager's'sThteenager's's parental attachment is weakened due to inadequate interaction time. Their psychological profile is also rooted on the internet, making it difficult for their parents to understand their mental state. This piece is essential for it enables an understanding of the hierarchal regression of peer and parental attachment among teenagers. The teenagers addicted to the internet prefer airing their problems on the internet to solicit sympathy than to talk them out. Pluhar, E., Kavanaugh, J. R., Levinson, J. A., & Rich, M. (2019). Problematic interactive media use in teens: comorbidities, assessment, and treatment. Psychology research and behavior management, 12, 447. Pluhar et al. describe the internet and virtual gaming as Problematic Interactive Media Use. They define teenage internet use as satisfying entertainment and other emotional needs. The study highlight PIMU effects as academic failure, social withdrawal, family conflicts, and behavioral, physical, and mental problems. With no scope of standardization, these problems are only limited to therapeutic mitigation. The article highlighting the addictive disorders, internet dialectical behavior therapies offer remedies to the distorted teenage health and mental stability. The writing is hence further critical in managing internet use among teens by providing diagnostic efforts to these challenges. Kim, M. H., Min, S., Ahn, J. S., An, C., & Lee, J. (2019). Association between high adolescent smartphone use and intellectual impairment, conflicts with family members or friends, and suicide attempts. PloS one, 14(7), e0219831. Kim et al. evaluated the relationship between internet use and possible suicidal attempts among teenagers. Assessing the 2017 Korea Youth Risk Behavior Web-based survey, the use of smartphones to access the internet with accompanying conflicts such as family feuds. More serious suicidal attempts and related conflicts were high among adolescent and Korean Youth due to smartphone use. Smartphone has eased the access to the internet. The study is thus essential to advance understanding of increased internet use. Accessing the internet at the finger point hence endangering the lives of these teens due to addiction risks. Razi, A., Kim, S., Choudhury, M. D., & Wisniewski, P. (2019, November). Ethical considerations for adolescent online risk detection AI systems. In Good Systems: Ethical AI for CSCW (The 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing). The writing explores the ethical domains that are infringed during teen interaction with the internet. Razi et al (2019) assess the online risks, ranging from abusive languages, sexual content, inappropriate gaming graphics to the adolescents. They hence seek to develop a future artificial intelligence tool to customize and monitor the online risks to the teens. This includes developing an intelligent tool to customize teen search scope and accurately adhere to the parental control policies. These tools inhibit teenage online bullying and accurate train mechanisms that raise ethical challenges. The article is hence essential to the research as it offers solutions to mitigate the effects of the internet on teenage development. Developing an AI tool that monitors and customizes teenage activities on the internet, substantively increases their online safety as bullying and access to inappropriate content are reduced. Hence reducing moral decadence. Research Methodology 1 2 Chapter III: Research Methodology Introduction As the technology advance in different sectors, there have been increased data breaches in various organizations carried out by hackers who need customers' personally identifiable information. The healthcare sector keeps this kind of data for their customers, which needs to be protected, which can be done by developing health sector cybersecurity. A.I. helps in the improvement and insurance of network safety in healthcare. Network safety in medical services includes securing clinical data, advancements in the medical sector, and new clinical cycles by presenting projects, information, and gadgets to unapproved access. Innovation has improved, which has affected numerous public areas. For example, in medical care, online protection has assumed a fundamental part in its improvement. Not only has it assisted the association with securing its patients' wellbeing and security, but it has likewise guaranteed that it is viable and quality medical care for each patient. The theme behind this paper is to provide information on how the health sector can shield itself from information penetration as per the Identity theft resource center in 2019. The methods that can uncover data and worker mindfulness will assist the health sector with protection from being assaulted by different sources. Research Paradigm The study on the cause of data breaches in the health sector and its implications used a quantitative research paradigm. Quantitative research has various goals, which are to establish ontology, phenomenology, logic, and epistemology. The study applied all those to enable the interviewee to provide multiple important information in the study, such as mobile healthcare applications, the number of people with smartphones, and other quantitative information required 3 as presented in the questionnaire. Logical, ontological, and further research will enable us to solve the problem effectively. Quantitative analysis is of great importance. The study is centered around evaluating the variables and upgrading online protection in medical care information (Bryman & Bell, 2015). The boundaries utilized in estimation are the solitary factors that change. Each occurrence expresses an assorted quantitative example question that needs to be resolved by using an alternate border. The responses to the quantitative review questions characterize the exploration purposes and evaluate the different subjects of investigation. Research Design To effectively resolve a research problem, reliable and sufficient data is required, both qualitative and quantitative data, to determine the root cause of data breaching in the health sector (Alawneh, 2008). I developed a questionnaire with both open- and close-ended inquiries and the entirety of this was controlled through a survey tool. The majority of the interviewee's reactions will be recorded when attempting to clarify their understanding of a penetrate and how information lost can be characterized into purposeful dangers and coincidental dangers, as this account was spelled out for additional examination utilizing otter A.I. Besides, every meeting of the members will be endured about an hour and a half, depending upon the assignments being performed. Data collection and Sampling Procedures Every interviewee considered in the data collection process will have to have worked or is currently working in the health sector. They will read and mark an assent structure clarifying the reason for the exploration and were given the alternative to skipping an inquiry if they feel awkward responding to a question. Members enlisting will be through promotions from web- 4 based media and from known contacts whose training and identified work experience with the examination that was being led. Their reactions will be inclined to in two segments, which are quantitative and subjective. While investigating the personal information from the poll, we directed a topical examination to more readily dissect the members' reactions to the open-ended inquiries (Namey et al.,2012). For the most part, the analyst will be centered around discovering a specific pattern or a comparable thought to help layout the examination. It will forester some codes to recognize equivalent subjects and standards. Then, at that point, they began to assemble an underlying rundown or perspective on these codes to distinguish the examples wherein the members discussed insider dangers and information breaks. The selection of words and searching for electives will determine various perspectives/experiences on information penetration. Statistical Tests Summary Descriptive and inferential data is used to analyze data from the healthcare sector; this is qualitative research. This kind of data is kept for customers and needs to be protected, which can be done by developing health sector cybersecurity. T-test will be employed to analyze individual responses on data breaching in which the TCAP test will derive the composite scores. This will establish statistical evidence of a relationship between machine learning and data protection in healthcare. Thus, this will be undertaken under a 5% significance level, and the data be presented in tables and a statistical test matrix. Besides, correlations will be utilized to establish the connection between healthcare data security and machine learning and the percentage of health records breached and affected by the data breach. Lastly, Chi-square will be employed to determine the dangers brought about by technological advancement in healthcare and the proportion of high-volume data set for a vast number of clients that have been leaked through 5 technology. Hence, a combination of these statistical tools of testing will help to establish the underlying issue of a data breach in the healthcare sector as the technology advance. References 6 Alawneh M, Abbadi IM (2008). Preventing information leakage between collaborating organizations. In: Proceedings of the 10th International Conference on Electronic Commerce, ICEC. Bryman, A., & Bell, E. (2015). Business Research Methods (4th ed., p. 160). Oxford, England: Identity theft resource center (2019). https://www.idtheftcenter.org/ data-breaches/ Namey E. Guest G., MacQueen K. M. (2012). Introduction to Applied Thematic Analysis. Applied Thematic Analysis. SAGE Publications. Oxford University Press.