The document discusses a final year project on addressing issues with implementing a Trust Management Model. It provides background on the model and identifies research problems. It reviews literature on trust management concepts in IoT and proposes expected outcomes such as addressing how the model resolves issues. The methodology discusses breaking problems into sub-problems and addressing each. Results achieved were identifying themes in literature. Future work could involve blockchain-based models and decentralizing social networks.
Business Talk: Harnessing Generative AI with Data Analytics MaturityIJCI JOURNAL
Generative AI applications offer transformative potential for business operations, yet their adoption introduces substantial challenges. This paper utilizes the CBDAS data maturity model to pinpoint pivotal success factors for seamless generative AI integration in businesses. Through a comprehensive analysis of these factors, we underscore the essentials of generative AI deployment: cohesive architecture, robust data governance, and a data-centric corporate ethos. The study also highlights the hurdles and facilitators influencing its implementation. Key findings suggest that fostering a data-friendly culture, combined with structured governance, optimizes generative AI adoption. The paper culminates in presenting the practical implications of these insights, urging further exploration into the real-world efficacy of the proposed recommendations.
4020 Crews 1
4020 Crews 4
The Least Privilege Principle in Contemporary HR
Nancy Pier
Human Resource Management
The Least Privilege Principle in Contemporary HR
There is a recent trend in contemporary business where enterprises seem to have achieved a collaboration with information technology aimed at improving business efficiency and consequently result in sustainable success. This development has however come with the liability of protecting key identifiable information of each party in a business organization (Dhillon et al., 2017). As it is, governments have put it as a legal obligation for organizations to protect the information of their people as they work towards protecting sensitive information related to business. In the United States alone in 2018, there were 65 successful litigations by employees towards the employer for exposing their information to malicious parties leading to closure of 80% of these businesses due to hefty legal fees (Cockcroft, 2020). Previous studies have attributed secure employee and business information to 45% success in business based on more motivated employees, confidentiality of business information of the firms and favorable reputation by clients (Porter et al., 2019).
The current situation points to the necessity in the application of the least privilege principle based on the numerous success stories upon its application. There is evidence that the implementation of this principle in the homeland department of security led to 78% reduction of loss of crucial information for the department, 71 % reduction of witness and whistle blower information leakage and efficient classification of information an aspect that aids investigative efficiency in the departments (Hammad et al., 2019). Experts aver that cloud computing, is not enough to protect important information and point to role based access, the foundation of the least privilege principle, as the next reliable pillar for workplace and business safety. This subject is particularly vital in human resource management practice as the department is the custodian of employee information and is tasked with capacitating employees.
Interestingly, under the period of the boom in internet technologies and their application in business processes, there has been cases of insider trading where businesses have lost huge investment money and their operating reputations. A study on the effects of employee data insecurity, in Texas, indicated that last year, 2019, 28% of employees reached by the survey reported at least one case of bullying as unauthorized parties accessed their key identifiable information (Sennewald & Baillie, 2020). The study further indicated that this.
Business Talk: Harnessing Generative AI with Data Analytics MaturityIJCI JOURNAL
Generative AI applications offer transformative potential for business operations, yet their adoption introduces substantial challenges. This paper utilizes the CBDAS data maturity model to pinpoint pivotal success factors for seamless generative AI integration in businesses. Through a comprehensive analysis of these factors, we underscore the essentials of generative AI deployment: cohesive architecture, robust data governance, and a data-centric corporate ethos. The study also highlights the hurdles and facilitators influencing its implementation. Key findings suggest that fostering a data-friendly culture, combined with structured governance, optimizes generative AI adoption. The paper culminates in presenting the practical implications of these insights, urging further exploration into the real-world efficacy of the proposed recommendations.
4020 Crews 1
4020 Crews 4
The Least Privilege Principle in Contemporary HR
Nancy Pier
Human Resource Management
The Least Privilege Principle in Contemporary HR
There is a recent trend in contemporary business where enterprises seem to have achieved a collaboration with information technology aimed at improving business efficiency and consequently result in sustainable success. This development has however come with the liability of protecting key identifiable information of each party in a business organization (Dhillon et al., 2017). As it is, governments have put it as a legal obligation for organizations to protect the information of their people as they work towards protecting sensitive information related to business. In the United States alone in 2018, there were 65 successful litigations by employees towards the employer for exposing their information to malicious parties leading to closure of 80% of these businesses due to hefty legal fees (Cockcroft, 2020). Previous studies have attributed secure employee and business information to 45% success in business based on more motivated employees, confidentiality of business information of the firms and favorable reputation by clients (Porter et al., 2019).
The current situation points to the necessity in the application of the least privilege principle based on the numerous success stories upon its application. There is evidence that the implementation of this principle in the homeland department of security led to 78% reduction of loss of crucial information for the department, 71 % reduction of witness and whistle blower information leakage and efficient classification of information an aspect that aids investigative efficiency in the departments (Hammad et al., 2019). Experts aver that cloud computing, is not enough to protect important information and point to role based access, the foundation of the least privilege principle, as the next reliable pillar for workplace and business safety. This subject is particularly vital in human resource management practice as the department is the custodian of employee information and is tasked with capacitating employees.
Interestingly, under the period of the boom in internet technologies and their application in business processes, there has been cases of insider trading where businesses have lost huge investment money and their operating reputations. A study on the effects of employee data insecurity, in Texas, indicated that last year, 2019, 28% of employees reached by the survey reported at least one case of bullying as unauthorized parties accessed their key identifiable information (Sennewald & Baillie, 2020). The study further indicated that this.
TaskYou are required to prepare for this Assessment Item by1..docxbradburgess22840
Task
You are required to prepare for this Assessment Item by:
1. READING the Subject outline,
2. COMPLETING Topic 2 Project Planning
3. BUILDING your PLAN up from the ProjectTitle and Abstract in Assessment Task 1
WHAT TO DO:
1. Follow the Study Schedule and work with the Topics in Interact as they provide a "scaffold" for your learning in this subject.
2. Develop a detailed Capstone Project Proposal and Plan using project management software (as listed in the Study Schedule) and the skills you have acquired from IT Project Management to develop a project plan with a Work Breakdown Structure (WBS), milestones and Gantt chart. These tools may help.
1. MicrosoftProject Pro (http://office.microsoft.com/en-au/project/);
2. Open source tools like GanttProject (http://www.ganttproject.biz/);
3. OpenProj(http://sourceforge.net/projects/openproj/)
4. OpenProject (https://www.openproject.org/about).
5. ProjectLibre (http://www.projectlibre.org/)
3. Begin using the 'project blog' as a tool beyond the weekly progress reportsfor your chosen emerging technology topic:
1. The blog helps you to "think by writing" and also store your notes, project files and links in a cloud-based service.
2. Consider sharing the site with your peers as a way to tell a story and harness each other’s knowledge.
4. The blog is ideally updated each week with 3 or 4 entries for documenting your project notes and as the foundation for editing and writing the Capstone Project Report. An ideal blog entry will have around 50-150 words (150-600 words a week).
Presentation
Project Plan Sample Format
(subject to change or modified to include systems development projects)
1. Title: Emerging Technology and Innovation Topic
1. Project Blog ( Web address provided)
2. Weekly Progress Reports Plan (In class, Discussion Board or Project Blog entries)
2. Rationale
1. Problem domain
2. Purpose and justification
3. Supervisor Approval
4. Research Questions
5. Conceptual or Theoretical Framework
6. Methodology
1. Analysis of sources of information (EndNote, APA Referencing Style)
2. Research method(s)
3. Data collection or systems design methods
4. Ethical Issues
5. Compliance Requirements (Workplace, Industry or Government regulations)
7. Project Plan
1. Deliverables (Annotated Bibliography, Journal Paper, Report, Seminar)
2. Work breakdown structure (WBS)
3. Risk Analysis
4. Duration
5. Gantt chart
8. References
9. Appendix (if required)
Final project
Formulating Strategic Management Decisions
This final project is based on the following Harvard Business case study:
Khachatryan, D. (2014). Amarcord Incorporated: Combating money laundering using data analytics. Harvard Business Case Study. Retrieved from https://hbsp.harvard.edu/tu/789925b5
Assume your client accepted your urgent business proposal to design a data-driven approach to effectively accomplish the goal of fraud detection in financial institutions. Data analytics for fraud detection in financial institutions is the strat.
TaskYou are required to prepare for this Assessment Item by1..docxdeanmtaylor1545
Task
You are required to prepare for this Assessment Item by:
1. READING the Subject outline,
2. COMPLETING Topic 2 Project Planning
3. BUILDING your PLAN up from the ProjectTitle and Abstract in Assessment Task 1
WHAT TO DO:
1. Follow the Study Schedule and work with the Topics in Interact as they provide a "scaffold" for your learning in this subject.
2. Develop a detailed Capstone Project Proposal and Plan using project management software (as listed in the Study Schedule) and the skills you have acquired from IT Project Management to develop a project plan with a Work Breakdown Structure (WBS), milestones and Gantt chart. These tools may help.
1. MicrosoftProject Pro (http://office.microsoft.com/en-au/project/);
2. Open source tools like GanttProject (http://www.ganttproject.biz/);
3. OpenProj(http://sourceforge.net/projects/openproj/)
4. OpenProject (https://www.openproject.org/about).
5. ProjectLibre (http://www.projectlibre.org/)
3. Begin using the 'project blog' as a tool beyond the weekly progress reportsfor your chosen emerging technology topic:
1. The blog helps you to "think by writing" and also store your notes, project files and links in a cloud-based service.
2. Consider sharing the site with your peers as a way to tell a story and harness each other’s knowledge.
4. The blog is ideally updated each week with 3 or 4 entries for documenting your project notes and as the foundation for editing and writing the Capstone Project Report. An ideal blog entry will have around 50-150 words (150-600 words a week).
Presentation
Project Plan Sample Format
(subject to change or modified to include systems development projects)
1. Title: Emerging Technology and Innovation Topic
1. Project Blog ( Web address provided)
2. Weekly Progress Reports Plan (In class, Discussion Board or Project Blog entries)
2. Rationale
1. Problem domain
2. Purpose and justification
3. Supervisor Approval
4. Research Questions
5. Conceptual or Theoretical Framework
6. Methodology
1. Analysis of sources of information (EndNote, APA Referencing Style)
2. Research method(s)
3. Data collection or systems design methods
4. Ethical Issues
5. Compliance Requirements (Workplace, Industry or Government regulations)
7. Project Plan
1. Deliverables (Annotated Bibliography, Journal Paper, Report, Seminar)
2. Work breakdown structure (WBS)
3. Risk Analysis
4. Duration
5. Gantt chart
8. References
9. Appendix (if required)
Final project
Formulating Strategic Management Decisions
This final project is based on the following Harvard Business case study:
Khachatryan, D. (2014). Amarcord Incorporated: Combating money laundering using data analytics. Harvard Business Case Study. Retrieved from https://hbsp.harvard.edu/tu/789925b5
Assume your client accepted your urgent business proposal to design a data-driven approach to effectively accomplish the goal of fraud detection in financial institutions. Data analytics for fraud detection in financial institutions is the strat.
4Emerging Trends in Business IntelligenceITS 531.docxblondellchancy
4
Emerging Trends in Business Intelligence
ITS 531-20 Business Intelligence
Emerging Trends in Business Intelligence
By
Vivek Reddy Chinthakuntla
Soumya Kalakonda
To Professor Dr. Kelly Bruning
University of the Cumberlands
Table of Contents
Abstract.......................................................................................................................................4
Business Intelligence with Data Analytics................................................................................................6
Partial Application of BI with Data Analytics...........................................................................................7
Future of BI and Data Analytics.................................................................................................................8
Positive and negative impacts of BI ..........................................................................................................9
Recommendations ....................................................................................................................................9
Cloud Computing with BI.......................................................................................................................10
Practical Implications..............................................................................................................................10
Future of Cloud Computing with BI........................................................................................................14
Advantages and Disadvantages................................................................................................................15
Recommendations....................................................................................................................................15
Introduction to Business Drive Data Intelligence.....................................................................................16
Data Governance of Self-Service BI ........................................................................................................19
Future of BI depends on Data Governance..............................................................................................19
Conclusion................................................................................................................................................20
References................................................................................................................................................ 22
Abstract:
This paper is based on the proposition used, and the outcomes attained, using data management to expedite the changes in the operation from a conventional old-fashioned practice to an automatic Business Intelligence data analytics system, presenting timely, reliable system production data by using Business Intelligence tools and technologies. This paper explains the importance and productivity of ...
Running head PROJECT PLAN INCEPTION1PROJECT PLAN INCEPTION .docxjeanettehully
Running head: PROJECT PLAN INCEPTION 1
PROJECT PLAN INCEPTION 2
Information Technology and Business
Babatunde Ogunade
CIS499: Information System Capston
Professor Reddy Urimindi
October 13, 2019
Information Technology and Business
Project Introduction
The very core operation of this company involves the collection and analysis of data through a currently limited technological infrastructure. The basis of this business may focus on leadership structure, the type of industry, business culture, core vision and mission including objectives. The company has a Chief Executive Officer (CEO) as the highest rank, four Information Technology experts and other employees. Marketing can, therefore, categorize this company as a service industry company with a core vision of a 60 percent growth in the next eighteen months and mission of redesigning its information technology to fulfill its organizational needs.
Product features, new market product, differentiation techniques, and value addition defines the type of business which the company is operating. The assessment of its product features which involves data indicate that the opportunities focus on marketing. In the continued operations of the company, the management is not foreseeing any shift from its original product but is rather fixing a differentiation technique within six months. An addition in product value should be achieved by employing an exclusively new technology based on a hybrid model, hosted solution or on-site solution.
The idea of integrating technologies from other partners to realize cost-effective outcomes and best operations outlines the outsourcing policies as far as new technology is concerned. Consequently, future intentions to acquire services such as Software-as-a-Service (SaaS) and cloud computing technologies may involve the adoption of knowledge and skills from outside the country, therefore, describing offshoring activities. As asserted by Aithal, (2017), the success of fulfilling the effective company operation, these activities are important.
One of the skilled personnel in the company is the Chief Information Officer (CIO) whose basic role is to keep a charge on the computer systems and information technology (IT) necessary in ensuring a company’s goals and objectives. Additionally, the CEO has devolved the responsibility of security protocols to the CIO in the process of more digitized frameworks. Other personnel includes the company CEO tasked with communicating to partners, creating the company mission and vision, and generally heading the implementation of both long term and short term objectives. The other information technician is mandated in both the installation and configuration of computer hardware and software.
Based on the current collection and analysis method, data on the customer, marketing, lifecycle, website engagement, and funnel analytics. In broad-spectrum, funnel analytics provide customer information through registration, ...
MIST.601 Management Information SystemsResearch Project Proposal.docxannandleola
MIST.601 Management Information Systems
Research Project Proposal
Name
Ryan Schwalbe
Title
Robot Lawyers – The Future of Artificial Intelligence in Law
Synopsis
(Briefly describe your research proposal with the following criteria.)
Purpose
The purpose of this project is to discuss how artificial intelligence (AI), also referred to as machine based learning, is currently being used in the legal industry. Furthermore, the project intends to discuss the benefits of this technology in addition to the challenges clients and attorneys face both working with and against it.
Problems & Issues
One of the various issues the industry is facing with AI technology is the general adoption and implementation into traditional document review models. Many clients and senior attorneys are still hesitant to rely on computers for document review calls without the validation by human lawyers. The technology also requires a technical understanding of computer science and statistical methodologies used in machine based workflows, which many lawyers do not have experience in. AI methods can also reduce the number of human attorneys necessary to facilitate electronic document reviews. As the technology continues to evolve this could potentially create a drought for attorneys that would have otherwise been needed for the review work.
Organizational Impacts
It’s already been proven that large scale document reviews leveraging AI software can significantly reduce the legal spend when compared to traditional search term and linear based human review models. Courts are now more accepting of this approach due mostly to the controversy surrounding e-discovery related costs proportional to the financial damage merits of many law suits. The technology has also been proven to increase the accuracy and consistency of document reviews which reduce the associated risks of missing key documents and producing sensitive privilege materials inadvertently.
Suggestions
Companies, law firms and governing bodies alike need to continue evaluating the needs and uses of this learning technology for practical legal applications. Currently, there are many private vendor companies with expertise in this area but the lack of standardizations in the industry has created a diverse range of AI software and practices which has in turn has caused confusion through complexity. Industry standard practices should be developed so that training can be standardized, implemented and adopted across the legal community more rapidly.
Future Implications & Directions
As the AI technology in legal review continues to develop the need for human review and even second level validation will continue to decrease. Courts will become more accepting of the process and corporate clients will be less tolerant of expensive, bloated document review costs. Attorneys will need to be armed with both the legal and technical knowledge necessary in order to stay relevant in next generation law firms.
Other ...
How to Improve Efficiency of Banking System with Big Data (A Case Study of Ni...Hafiz Sanni
In banking industry today which their data has now turn to what we call Big data, some banks has now started making advantages of these big data to reach the main objectives of marketing. The banking industry can use the data to increase their efficiency by identifying the key customer, improving the customer feedback system, detect when they are about to lose a customer, to enhance the active and passive security system and efficiently evaluating of the system. This paper focus on different analysis and algorithms the banking industry can use to achieve all the advantages of these big data especially Nigeria banking industry. Analysis such as Link analysis, survival analysis, neural analysis, text analytics, clustering analysis, decision tree, sentiment analysis, social network analysis and datammer for predicting the security threat.
TaskYou are required to prepare for this Assessment Item by1..docxbradburgess22840
Task
You are required to prepare for this Assessment Item by:
1. READING the Subject outline,
2. COMPLETING Topic 2 Project Planning
3. BUILDING your PLAN up from the ProjectTitle and Abstract in Assessment Task 1
WHAT TO DO:
1. Follow the Study Schedule and work with the Topics in Interact as they provide a "scaffold" for your learning in this subject.
2. Develop a detailed Capstone Project Proposal and Plan using project management software (as listed in the Study Schedule) and the skills you have acquired from IT Project Management to develop a project plan with a Work Breakdown Structure (WBS), milestones and Gantt chart. These tools may help.
1. MicrosoftProject Pro (http://office.microsoft.com/en-au/project/);
2. Open source tools like GanttProject (http://www.ganttproject.biz/);
3. OpenProj(http://sourceforge.net/projects/openproj/)
4. OpenProject (https://www.openproject.org/about).
5. ProjectLibre (http://www.projectlibre.org/)
3. Begin using the 'project blog' as a tool beyond the weekly progress reportsfor your chosen emerging technology topic:
1. The blog helps you to "think by writing" and also store your notes, project files and links in a cloud-based service.
2. Consider sharing the site with your peers as a way to tell a story and harness each other’s knowledge.
4. The blog is ideally updated each week with 3 or 4 entries for documenting your project notes and as the foundation for editing and writing the Capstone Project Report. An ideal blog entry will have around 50-150 words (150-600 words a week).
Presentation
Project Plan Sample Format
(subject to change or modified to include systems development projects)
1. Title: Emerging Technology and Innovation Topic
1. Project Blog ( Web address provided)
2. Weekly Progress Reports Plan (In class, Discussion Board or Project Blog entries)
2. Rationale
1. Problem domain
2. Purpose and justification
3. Supervisor Approval
4. Research Questions
5. Conceptual or Theoretical Framework
6. Methodology
1. Analysis of sources of information (EndNote, APA Referencing Style)
2. Research method(s)
3. Data collection or systems design methods
4. Ethical Issues
5. Compliance Requirements (Workplace, Industry or Government regulations)
7. Project Plan
1. Deliverables (Annotated Bibliography, Journal Paper, Report, Seminar)
2. Work breakdown structure (WBS)
3. Risk Analysis
4. Duration
5. Gantt chart
8. References
9. Appendix (if required)
Final project
Formulating Strategic Management Decisions
This final project is based on the following Harvard Business case study:
Khachatryan, D. (2014). Amarcord Incorporated: Combating money laundering using data analytics. Harvard Business Case Study. Retrieved from https://hbsp.harvard.edu/tu/789925b5
Assume your client accepted your urgent business proposal to design a data-driven approach to effectively accomplish the goal of fraud detection in financial institutions. Data analytics for fraud detection in financial institutions is the strat.
TaskYou are required to prepare for this Assessment Item by1..docxdeanmtaylor1545
Task
You are required to prepare for this Assessment Item by:
1. READING the Subject outline,
2. COMPLETING Topic 2 Project Planning
3. BUILDING your PLAN up from the ProjectTitle and Abstract in Assessment Task 1
WHAT TO DO:
1. Follow the Study Schedule and work with the Topics in Interact as they provide a "scaffold" for your learning in this subject.
2. Develop a detailed Capstone Project Proposal and Plan using project management software (as listed in the Study Schedule) and the skills you have acquired from IT Project Management to develop a project plan with a Work Breakdown Structure (WBS), milestones and Gantt chart. These tools may help.
1. MicrosoftProject Pro (http://office.microsoft.com/en-au/project/);
2. Open source tools like GanttProject (http://www.ganttproject.biz/);
3. OpenProj(http://sourceforge.net/projects/openproj/)
4. OpenProject (https://www.openproject.org/about).
5. ProjectLibre (http://www.projectlibre.org/)
3. Begin using the 'project blog' as a tool beyond the weekly progress reportsfor your chosen emerging technology topic:
1. The blog helps you to "think by writing" and also store your notes, project files and links in a cloud-based service.
2. Consider sharing the site with your peers as a way to tell a story and harness each other’s knowledge.
4. The blog is ideally updated each week with 3 or 4 entries for documenting your project notes and as the foundation for editing and writing the Capstone Project Report. An ideal blog entry will have around 50-150 words (150-600 words a week).
Presentation
Project Plan Sample Format
(subject to change or modified to include systems development projects)
1. Title: Emerging Technology and Innovation Topic
1. Project Blog ( Web address provided)
2. Weekly Progress Reports Plan (In class, Discussion Board or Project Blog entries)
2. Rationale
1. Problem domain
2. Purpose and justification
3. Supervisor Approval
4. Research Questions
5. Conceptual or Theoretical Framework
6. Methodology
1. Analysis of sources of information (EndNote, APA Referencing Style)
2. Research method(s)
3. Data collection or systems design methods
4. Ethical Issues
5. Compliance Requirements (Workplace, Industry or Government regulations)
7. Project Plan
1. Deliverables (Annotated Bibliography, Journal Paper, Report, Seminar)
2. Work breakdown structure (WBS)
3. Risk Analysis
4. Duration
5. Gantt chart
8. References
9. Appendix (if required)
Final project
Formulating Strategic Management Decisions
This final project is based on the following Harvard Business case study:
Khachatryan, D. (2014). Amarcord Incorporated: Combating money laundering using data analytics. Harvard Business Case Study. Retrieved from https://hbsp.harvard.edu/tu/789925b5
Assume your client accepted your urgent business proposal to design a data-driven approach to effectively accomplish the goal of fraud detection in financial institutions. Data analytics for fraud detection in financial institutions is the strat.
4Emerging Trends in Business IntelligenceITS 531.docxblondellchancy
4
Emerging Trends in Business Intelligence
ITS 531-20 Business Intelligence
Emerging Trends in Business Intelligence
By
Vivek Reddy Chinthakuntla
Soumya Kalakonda
To Professor Dr. Kelly Bruning
University of the Cumberlands
Table of Contents
Abstract.......................................................................................................................................4
Business Intelligence with Data Analytics................................................................................................6
Partial Application of BI with Data Analytics...........................................................................................7
Future of BI and Data Analytics.................................................................................................................8
Positive and negative impacts of BI ..........................................................................................................9
Recommendations ....................................................................................................................................9
Cloud Computing with BI.......................................................................................................................10
Practical Implications..............................................................................................................................10
Future of Cloud Computing with BI........................................................................................................14
Advantages and Disadvantages................................................................................................................15
Recommendations....................................................................................................................................15
Introduction to Business Drive Data Intelligence.....................................................................................16
Data Governance of Self-Service BI ........................................................................................................19
Future of BI depends on Data Governance..............................................................................................19
Conclusion................................................................................................................................................20
References................................................................................................................................................ 22
Abstract:
This paper is based on the proposition used, and the outcomes attained, using data management to expedite the changes in the operation from a conventional old-fashioned practice to an automatic Business Intelligence data analytics system, presenting timely, reliable system production data by using Business Intelligence tools and technologies. This paper explains the importance and productivity of ...
Running head PROJECT PLAN INCEPTION1PROJECT PLAN INCEPTION .docxjeanettehully
Running head: PROJECT PLAN INCEPTION 1
PROJECT PLAN INCEPTION 2
Information Technology and Business
Babatunde Ogunade
CIS499: Information System Capston
Professor Reddy Urimindi
October 13, 2019
Information Technology and Business
Project Introduction
The very core operation of this company involves the collection and analysis of data through a currently limited technological infrastructure. The basis of this business may focus on leadership structure, the type of industry, business culture, core vision and mission including objectives. The company has a Chief Executive Officer (CEO) as the highest rank, four Information Technology experts and other employees. Marketing can, therefore, categorize this company as a service industry company with a core vision of a 60 percent growth in the next eighteen months and mission of redesigning its information technology to fulfill its organizational needs.
Product features, new market product, differentiation techniques, and value addition defines the type of business which the company is operating. The assessment of its product features which involves data indicate that the opportunities focus on marketing. In the continued operations of the company, the management is not foreseeing any shift from its original product but is rather fixing a differentiation technique within six months. An addition in product value should be achieved by employing an exclusively new technology based on a hybrid model, hosted solution or on-site solution.
The idea of integrating technologies from other partners to realize cost-effective outcomes and best operations outlines the outsourcing policies as far as new technology is concerned. Consequently, future intentions to acquire services such as Software-as-a-Service (SaaS) and cloud computing technologies may involve the adoption of knowledge and skills from outside the country, therefore, describing offshoring activities. As asserted by Aithal, (2017), the success of fulfilling the effective company operation, these activities are important.
One of the skilled personnel in the company is the Chief Information Officer (CIO) whose basic role is to keep a charge on the computer systems and information technology (IT) necessary in ensuring a company’s goals and objectives. Additionally, the CEO has devolved the responsibility of security protocols to the CIO in the process of more digitized frameworks. Other personnel includes the company CEO tasked with communicating to partners, creating the company mission and vision, and generally heading the implementation of both long term and short term objectives. The other information technician is mandated in both the installation and configuration of computer hardware and software.
Based on the current collection and analysis method, data on the customer, marketing, lifecycle, website engagement, and funnel analytics. In broad-spectrum, funnel analytics provide customer information through registration, ...
MIST.601 Management Information SystemsResearch Project Proposal.docxannandleola
MIST.601 Management Information Systems
Research Project Proposal
Name
Ryan Schwalbe
Title
Robot Lawyers – The Future of Artificial Intelligence in Law
Synopsis
(Briefly describe your research proposal with the following criteria.)
Purpose
The purpose of this project is to discuss how artificial intelligence (AI), also referred to as machine based learning, is currently being used in the legal industry. Furthermore, the project intends to discuss the benefits of this technology in addition to the challenges clients and attorneys face both working with and against it.
Problems & Issues
One of the various issues the industry is facing with AI technology is the general adoption and implementation into traditional document review models. Many clients and senior attorneys are still hesitant to rely on computers for document review calls without the validation by human lawyers. The technology also requires a technical understanding of computer science and statistical methodologies used in machine based workflows, which many lawyers do not have experience in. AI methods can also reduce the number of human attorneys necessary to facilitate electronic document reviews. As the technology continues to evolve this could potentially create a drought for attorneys that would have otherwise been needed for the review work.
Organizational Impacts
It’s already been proven that large scale document reviews leveraging AI software can significantly reduce the legal spend when compared to traditional search term and linear based human review models. Courts are now more accepting of this approach due mostly to the controversy surrounding e-discovery related costs proportional to the financial damage merits of many law suits. The technology has also been proven to increase the accuracy and consistency of document reviews which reduce the associated risks of missing key documents and producing sensitive privilege materials inadvertently.
Suggestions
Companies, law firms and governing bodies alike need to continue evaluating the needs and uses of this learning technology for practical legal applications. Currently, there are many private vendor companies with expertise in this area but the lack of standardizations in the industry has created a diverse range of AI software and practices which has in turn has caused confusion through complexity. Industry standard practices should be developed so that training can be standardized, implemented and adopted across the legal community more rapidly.
Future Implications & Directions
As the AI technology in legal review continues to develop the need for human review and even second level validation will continue to decrease. Courts will become more accepting of the process and corporate clients will be less tolerant of expensive, bloated document review costs. Attorneys will need to be armed with both the legal and technical knowledge necessary in order to stay relevant in next generation law firms.
Other ...
How to Improve Efficiency of Banking System with Big Data (A Case Study of Ni...Hafiz Sanni
In banking industry today which their data has now turn to what we call Big data, some banks has now started making advantages of these big data to reach the main objectives of marketing. The banking industry can use the data to increase their efficiency by identifying the key customer, improving the customer feedback system, detect when they are about to lose a customer, to enhance the active and passive security system and efficiently evaluating of the system. This paper focus on different analysis and algorithms the banking industry can use to achieve all the advantages of these big data especially Nigeria banking industry. Analysis such as Link analysis, survival analysis, neural analysis, text analytics, clustering analysis, decision tree, sentiment analysis, social network analysis and datammer for predicting the security threat.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Model Attribute Check Company Auto PropertyCeline George
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ELEC6840A Final Year Project A.docx
1. ELEC6840A Final Year Project A
Answers:
Introduction
Project Aims
The aim of the project is to address the issues implementing the Trust Management Model.
In order to address the issue, the appropriate existing pieces of literature will be reviewed
along with discussing a proper methodology.
Background
The Trust Management Model is basically considered as a viable solution by which the IoT
issues are addressed. By optimizing the protection, as well as process of the support
decision making, the concerned model identifies the untrusted behaviour, installation of the
untrusted objects and redirecting the functionality for trusted zones (Malik et al. 2019).
According to the Trust Management model a system is proposed through which the trust
management system can be implemented for cloud computing. As a result, secured data
access is assured by the cloud service provider. Herein the method of trust evaluation gets
proposed to weight the trust factors for calculating the multiple attributes.
Research Problems And The Context
In terms of research problem the issue of abstract notion of the non-measurable variables
will be taken into account. Considering this fact the concept of Trust Management Model
will be concerned as a viable solution for resolving the IOT issues. As such the issues will be
focused on identifying the areas of support for the decision making process, optimisation of
protection, and identification of untrusted behaviour. Herein the components of the Trust
Management Model will be discussed.
Expected Outcomes
In terms of expected outcomes, it can be stated that the research will address the way
through which the issues are addressed by the Trust Management Model.
2. Benefits And Significance
In terms of benefits, it can be stated that the study is significant because it will review
appropriate pieces of the existing literature. As the data will be gathered from the already
published research, therefore authentic data will be presented by the concerned research.
Issues in current Trust Management Model: In current Trust Management Model it is seen
that the concerned model fails to optimise the protection along with supporting the decision
making process. As a result, the trust management system got failed to be implemented for
the cloud computing. The issues in trust evaluation method weighted the trust factors to be
calculated considering the several attributes.
How to resolve the issues: In order to resolve the said issue, the cloud security standard will
be established. As such, the SOC 2 standard will be demonstrating the policies, controls and
procedures of the firm in order to meet the trust management principles such as
Availability, Security, Processing Integrity, Privacy and Confidentiality.
Research Methodology
What is the Problem?
The issues of abstract notions of non-measurable variables has been considered in terms of
the problem. In light of this, the Trust Management Model idea will be considered as a
feasible approach for tackling IoT concerns (Kochovski et al. 2019). As a result, the concerns
will be focused on identifying the areas of support decision-making process, protection
optimization, and recognising untrustworthy behaviour. The Trust Management Model's
components will be explained in this section.
How do you break it down to smaller (sub-) problems?
In order to break down the main problems into the sub problems, establishment of the sub
problems will be done for distinguishing their characters. Herein it is worth to mention that
in order to identify the key problems, the sub problems will be considered as a researchable
as well as the complete unit (Rehiman and Veni 2017). As such the sub problem will be
clearly linked with the data interpretation.
How Do You Address Each Sub-Problem?
In order to identify the each sub problem, all the sub problems will be identified as a
complete resealable unit. Herein, the sub problems will be strongly linked with the data
interpretation. It is worth mentioning here that the sub problems need to be added up to
the total of the issue. Herein the sub problems will be established based on the aim of the
research.
3. How do you put everything together to solve your big problem?
In order to solve the big problem of the research, the main problem will be differentiated
from the opinion fact. As such specifying the underlying issues, the alternative solutions are
expected to be generated on that note. Apart from that by selecting as well as evaluating the
alternative, the target standard will be relatively linked.
Literature Review
Theme 1: Understanding the concept of Trust management in IoT:
In relation to the IoT, the concept of trust management has appeared as a vital solution for
trust issues. Some previous research has stated that the concerned model helps to optimize
the protection along with supporting the decision making process. As such by identifying
the untrusted behaviour, it can isolate the untrusted objects along with redirecting the
functionality associated with the trusted zones. Based on this concern theme, it can be
stated that the hierchical trust management model focuses on inverted tree structure
focusing on which the root causes are analysed. On the other hand, as believed by Li,
Varadharajan and Nepal (2019) as the root considered as the starting point of a trust,
therefore the top down arts enhance the leaf node of the user.
Theme 2: Trust Management Model as a Public infrastructure:
Trust Management Model has been identified as a collection of rules through which the
application is informed regarding deciding the legitimacy of the digital certificate. The
research by Isirova and Potii (2018) revealed that fundamentally the trust management
model provides the positive environment whether to trust on a particular organization or
needs to depend on the certificate issued by the hierarchical department of the
organization. Herein, in order to address the issues most of the organizations opt for the
peer to peer architecture due to its well defined structure of the organization as well as
discovering the complex validation.
Theme 3: Effective distribution of the trust management model for IoT:
The Internet of Things (IoT) is a worldwide architecture for the digital age that connects
physical or digital things with current interoperability technological tools under
development to deliver improved services. It is indeed interesting to note that the explosion
in the number of cell phones and internet connections has created a new industry with
nearly limitless possibilities. Every day, 5.5 million things are connected throughout the
globe in 2016. By 2020, the population might be in the billions (Maddar, Kammoun and
Youssef 2018). According to Gartner, 26 billion items will be deployed by 2020. On the
other hand, in order to address the issue, In comparison to the above theme, it can be stated
that in order to address the issue, the categorization process is rather different. The
clustering approach can be represented on a computer as an inversion tree, but the web-of-
4. trust is more directly tied to how people evaluate trustworthiness in their personal
interactions. Customers can define how much trust they have in a certificate by choosing the
number of independent signatories that must be present for it to be considered valid (Tran,
Lu and Weber 2018). This technique works well for small groups with well-established
relationships, but it does not scale well for big groups or where security consistency is
critical, such as the amount of verification required before issuing a certificate.
Results/Outcomes And Analysis/Discussion
Introducing and discussing the results/outcomes that have achieved:
In terms of achieving the outcomes, it can be stated that the concerned study has identified
several themes identifying the existing pieces of literature. Herein as identified from the
selected themes, in the context of the Internet of Things, the notion of trust management
has emerged as a viable solution to trust challenges. According to prior study, the concerned
model aids in the optimization of protection as well as the decision-making process. As a
result, it may segregate untrusted objects while diverting functionality associated with
trusted zones by recognising untrustworthy behaviour (Mehraj and Banday 2020).
According to this common concept, the hierchical trust management model relies on an
inverted tree structure in which the root causes are identified. On the other hand, because
the root is thought to be the starting point of a trust, top down arts are used to enrich the
sub users. The abstract idea of non-measurable variables has been considered in terms of
the research challenge. Given this, the Trust Management Model idea will be seen as a
feasible approach for overcoming IoT concerns. As a result, the concern has been focused on
identifying the areas of support decision-making process, protection optimization, and
untrustworthy behaviour identification (Awan et al. 2019). The Trust Management Model's
components will be explored in this article. In terms of predicted outcomes, the study has
been looked into how the Trust Management Model deals with challenges.
Suggestions For Future Solutions:
In terms of future solutions, it can be stated that in the forthcoming days, the Block chain
based trust management model is required to be used (Qureshi et al. 2020). As such the
trust related issues can be attacked by producing the malicious users through utilizing the
techniques of classification. Decentralization of the online social network is another area to
be concerned for the future solutions.
What is to be done in the rest weeks?
Activities during research
1st Week
11. Final submission of the research report
ü
(Source: Self-Creation)
Conclusion And Future Outlook
What problems have you addressed?
It can be concluded that The Trust Management Model is widely recognised as a viable
approach to dealing with IoT issues. By optimizing the protection and support decision-
making processes, the concerned model recognises untrustworthy behaviour, isolates
untrustworthy objects, and diverts functionality to trusted zones. A way for establishing a
trust management system for cloud computing is described by the Trust Management
Model. As a result, the cloud service provider ensures that data is accessible in a secure
manner. In this research, a trust evaluation approach is presented for computing a variety
12. of attributes by weighing the trust components.
What results have you achieved and what is the significance of the results?
The result that has been achieved from the study is that In terms of accomplishing the
desired goals, it can be claimed that the research project has found various topics through
analysing existing literature. As a result of the chosen topics, the following is presented. The
concept of trust management has evolved as a feasible solution to trust concerns in the
context of the Internet of Things. The concerned model, according to previous research,
contributes in the optimization of protection as well as the decision-making process. As a
consequence, by recognising untrustworthy behaviour, it may be able to isolate untrusted
objects while redirecting functionality associated with trusted zones.
What problems would need to be addressed in future?
In terms of problems to be addressed in future, it can be claimed that the block chain-based
trust management model will be necessary in the near future. As a result, trust-related
issues may be targeted by creating fraudulent users and employing categorization
algorithms. Another area to consider for future solutions is decentralization of online social
networks.
References
Awan, K.A., Din, I.U., Almogren, A., Guizani, M., Altameem, A. and Jadoon, S.U., 2019.
Robusttrust–a pro-privacy robust distributed trust management mechanism for the
internet of things. IEEE Access, 7, pp.62095-62106.
Kochovski, P., Gec, S., Stankovski, V., Bajec, M. and Drobintsev, P.D., 2019. Trust management
in a blockchain based fog computing platform with trustless smart oracles. Future
Generation Computer Systems, 101, pp.747-759.
Maddar, H., Kammoun, W. and Youssef, H., 2018. Effective distributed trust management
model for Internet of Things. Procedia Computer Science, 126, pp.321-334.
Qureshi, K.N., Iftikhar, A., Bhatti, S.N., Piccialli, F., Giampaolo, F. and Jeon, G., 2020. Trust
management and evaluation for edge intelligence in the Internet of Things. Engineering
Applications of Artificial Intelligence, 94, p.103756.
Rehiman, K.R. and Veni, S., 2017, February. A trust management model for sensor enabled
mobile devices in IoT. In 2017 International Conference on I-SMAC (IoT in Social, Mobile,
Analytics and Cloud)(I-SMAC) (pp. 807-810). IEEE.
Isirova, K. and Potii, O., 2018, May. Decentralized public key infrastructure development
13. principles. In 2018 IEEE 9th International Conference on Dependable Systems, Services and
Technologies (DESSERT) (pp. 305-310). IEEE.
Tran, A.B., Lu, Q. and Weber, I., 2018, September. Lorikeet: A Model-Driven Engineering
Tool for Blockchain-Based Business Process Execution and Asset Management. In BPM
(Dissertation/Demos/Industry) (pp. 56-60).
Li, N., Varadharajan, V. and Nepal, S., 2019, July. Context-aware trust management system
for iot applications with multiple domains. In 2019 IEEE 39th International Conference on
Distributed Computing Systems (ICDCS) (pp. 1138-1148).
Malik, S., Dedeoglu, V., Kanhere, S.S. and Jurdak, R., 2019, July. Trustchain: Trust
management in blockchain and iot supported supply chains. In 2019 IEEE International
Conference on Blockchain (Blockchain) (pp. 184-193). IEEE.
Mehraj, S. and Banday, M.T., 2020, January. Establishing a zero trust strategy in the cloud
computing environment. In 2020 International Conference on Computer Communication
and Informatics (ICCCI) (pp. 1-6). IEEE.