1. Management
Information
Systems:
Solving Business
Problems with
Information Technology
Part One:
Business Operations
Chapter Four:
Security, Privacy, and
Anonymity
Prof. Gerald V. Post
Prof. David L. Anderson

2. The Growth of Electronic Commerce
Business-to-Business
Includes up and down stream transactions that can enhance channel coordination and customer relationships
Business-to-Consumer
Encompasses all interaction between the customer and the organization
Open Marketspace
Connects business, partner, and consumer

3. Web-Based Commerce Model
Manufacturer/
Supplier
Customers
Direct
Marketspace
Business-to-Business
Business-to-Consumer
Intermediary

4. Operating Effectively in the Business-to-Consumer Boundary
Leverage Firm’s Logistical System
Price and Manage Online Transactions
Optimize Communication to Key Consumer Markets
Achieve Excellence through Service

5. Develop Business Partnerships
Establish Business-to-Business Relationships to Sell Competitively to Customers
Strengthen the Value Chain
Provide Value through Communication
Optimize Business-to-Business Service

6. Virtual Interconnectivity
Sell in a Virtual World
Stay Real or Become Virtual
Communicate with a Community
Provide Value-Add Services in the Marketspace

7. Opportunities and Threats of End-Run Strategies
Odd Person Out
Establish Place in Value Chain
Compare Information in a Virtual World
Optimize the Service Offering Across Partner Organizations

8. Managerial Issues for Security
Technical
Societal
Economic
Legal
Behavioral
Organizational/Managerial

9. Managerial Issues for Security
Technical
How will Security be Implemented?
What protocols will be the standards of future electronic commerce?
What are the future technologies used to “wire” people and households?

10. Managerial Issues for Security
Societal
How will the privacy of individuals be protected?
How will consumer data be used?
Will consumer data be misused?
How do user perceptions of issues reflect reality?

11. Managerial Issues for Security
Economic
How will electronic and physical markets differ?
Will economic theories succeed as instantaneous access to information emerges?
What will be the price of information?

12. Managerial Issues for Security
Legal
Should governments continue to subsidize the internet?
How will real world laws apply to the legality of virtual sites?
Who is liable for information accuracy?

13. Managerial Issues for Security
Behavioral
How satisfied will users be with virtual experiences compared to those in the real world?
How will a sense of community and social needs be represented through E-Commerce?
What are the characteristics of early adopters of E-Commerce?

14. Managerial Issues for Security
Organizational/Managerial
What are the differences between managing an E-commerce business and a more traditional one?
How will the organization of the firm change as E-commerce becomes more prevalent?
What products lend themselves to success with E-Commerce?

15. Managerial Issues for Security
Technical
Societal
Economic
Legal
Behavioral
Organizational/Managerial

16. Strategic Security Leverage Paradigm
Change
the
Game
Change
the
Game
Competitive
Position
Competitive
Position
Nature of Conflict;
Terms of
Competition
Strategic
Leverage
Objectives
Strategies
Tactics

17. Systems Development Lifecycle
Obsolete Solution
Problem to be Solved
Planning
New, Related Problem or Requirement
Analysis
Support
New implementation Alternative or Requirement
Implementation
Error (bug)
Problem
Understanding
and
Solution
Requirements
Implemented
Solution
Design
Implementation
Acceptable
Solution
Statement

18. Systems Planning Elements
People
Users, Management, Information Specialists
Data
How it is captured, used, and stored
Activities
Automated and Manual
Business and Information Applications
Networks
Where data is stored and processed
How data is exchanged between different locations
Technology
hardware and software used

19. Electronic Commerce Building Block
Systems
Owners
Systems
Users
Systems
Designers
Systems
Builders

20. Differentiation versus Cost Leadership
Differentiated
Player
Sustainable
Premium
Technology
Curve
Cost
Leader
Minimum or
Market-Required
Quality
Quality

21. Is Cost Leadership Sustainable?
Differentiated
Player
Sustainable
Premium
New
Technology
Curve
Old
Technology
Curve
Cost
Leader
Minimum or
Market-Required
Quality
Quality

22. Industry/Company Relationships
Structure &
Competitive
Position
Freedom of
Maneuver
Long-term
Objectives,
Strategic
Direction
Detailed
Strategies
and Tactics

23. Break-Even Point Total Revenue Revenue and Costs Profit Profit
Total Costs
Fixed
Costs
Fixed Costs
Sales
Break-Even Volume

24. Decision Trees
Probability
Decision
Point

25. Efforts to Categorize the Unknown
Complexity
Uncertainty
Instability

26. Variables
Cost
Time
Risk

27. Barriers to Information Security Sources
Economies of Scale
Economies of Scope
Product Differentiation
Capital Requirements
Cost Disadvantages
Independent of Size
Distribution Channel Access
Government Policy

28. Four Generic Approaches
Lose
Win
Win/Win
Win/Lose or
Cooperative Equilibrium
Win
Lose
Win/Lose or
Cooperative
Equilibrium
Lose/Lose

29. Lose/Lose Structure Defines the Industry War
Total Industry Profits are Very Low, Zero, or Negative
Industry Revenues are Declining, or, at best, steady
Product Technology is at or past its peak

30. Win/Win Total Industry Revenues and Profits are Growing Rapidly
Numerous Players of All Sizes
Products and Services are not Standardized

31. Win/Lose
Total Industry Revenues and/or Profits are Constant or are Growing very Slowly
Significant Economies of Scale in Production, Distribution, and/or Promotion
Number of Firms Participating in the Industry is Limited and Stable
Individual Participants have, or can obtain, Information Regarding the Relative Positions of the Players

32. Structure Defines the Terms of Competition
Wasting Resources
generic advertising rather than focusing on specific market segments
Precipitating Unwanted Warfare
Causing a full-scale price war when only brand repositioning was necessary
Failing to Anticipate and Adapt to Changes
Following historical patterns
Underspending on Advertising

33. Structure Defines Maneuver
Standard or Dominant Product Emerges
Distribution Channels Limit Firm’s Ability to Determine which Channels to Select
Target and Market Niches Become More Difficult to Defend
Substitutes Limit Price Increases which Requires Increase in Advertising Expenditure

34. Two Levels of Planning Systems Planning Systems Project Planning
Gives Managers, Users, and Information Systems Personnel Projects
Establishes what should be done
Sets a budget for the total cost of these projects
Systems Project Planning
Setting a plan for the development of each specific systems project

35. Systems Professional Skills
Systems Planning
Form project team after proposed systems project is cleared for development
Systems Analysis
Business Systems Analysts knowledgeable in business
General Systems Design
Business Systems Analysts
Systems Evaluation and Selection
Detailed Systems Design
Wide Range of Systems and Technical Designers
Systems Implementation
Systems analysts, programmers, and special technicians

36. Effective Leadership Style
Autocratic Style
Crisis-Style Management
Used to Correct Major Problem, such as Schedule Slippage
Democratic Style
Team-oriented Leadership
Gives each team member the freedom to achieve goals which he/she helped set
Laissez-Faire Style
Highly-motivated, Highly-Skilled Team Members
People who work best alone

37. Project Management Skills
Planning
States what should be done
Estimates how long it will take
Estimates what it will cost
Leading
Adapts to dynamics of enterprise and deals with setbacks
Guides and induces people to perform at maximum abilities
Controlling
Monitors Progress Reports and Documented Deliverables
Compares Plans with Actuals
Organizing
Staffs a Systems Project Team
Brings together users, managers, and team members

38. CASE/Frameworks Computer-Aided Systems and Software Engineering
Increase Productivity of Systems Professionals
Improve the Quality of Systems Produced
Improve Software Maintenance Issue

39. CASE/Frameworks Includes: workstations central repository
numerous modeling tools
project management
Systems Development Life Cycle Support
Prototyping Applications
Software Design Features

40. Central Repository for Models
Models Derived from Modeling Tools
Project Management Elements
Documented Deliverables
Screen Prototypes and Report Designs
Software Code from Automatic Code Generator
Module and Object Libraries of Reusable Code
Reverse Engineering, Reengineering, and Restructuring Features

41. Software Maintenance Reverse Engineering
Extract original design from spaghetti-like, undocumented code to make maintenance change request
Abstract meaningful design specifications that can be used by maintenance programmers to perform maintenance tasks
Reengineering
Examination and changing of a system to reconstitute it in form and functionality
Reimplementation
Restructuring
Restructures code into standard control constructs
sequence, selection, repetition

42. Data Design
Define all the entities to be dealt with and the relationships between them
Transform the conceptual design into logical design wherein all the views are combined and all the resulting data elements are defined and the data structure is syntactically and semantically determined
Normalize this logical design for mathematically minimized redundancy and maximized integrity
Transform this logical design to a physical design where the underlying RDBMS, hardware, and use patterns are taken into account
Develop the SQL DDL code specific to each RDBMS vendor’s product is generated

43. Business Rules For Data
Basic selection of what data elements are of interest, what are their characteristics (data type and acceptable range - also called syntactic structure)
How they are related to, or dependent on, each other in a business sense (key, foreign key and referential constraint rule - also called the semantic structure)
Data Integrity Rules

44. Advantages of Data Analysis
“slice and dice” dynamic query support
standard high-level access language (SQL)
minimum data redundancy
self-protecting data integrity
no insert, delete and update anomalies

45. Relational Model
The Relational Model for data design is the foundation of the relational database and the industry that produces the “engines” that run them.
It puts data design (and data modeling) on a formal, mathematical footing.

46. Relationship Types
a). One-to-one (1:1): means that an occurrence if one OT uniquely determines an occurrence of other OT - and vice-versa
b). One-to-many (1:n): means that an occurrence of one OT determines an occurrence of the other OT - but not vice-versa
c). Many-to-many (n:m):means that an occurrence of one OT can be related to many occurrences of other OT - and vice-versa

47. Data Rationalization
Identification of data synonyms and homonyms across multiple and disparate data sources and the creation of a map that points back to their original sources.

48. Data Access Gateway
sits between end users (usually in PC networks) and a legacy database
accepts data read requests (expressed as SQL statements)
converts the requests to legacy access method instructions
provides the resulting data to the users
data flow is one-way read-only.

49. Structured Data Analysis
the functions or activities which are to be handled by the system
the external entities which interact with the system
the logical data stores, and
the data flows among all the the above
Data flow diagrams (DFD) are used to diagrammatically describe the elements.

50. Entity Relationship Diagrams (ERDs)
A method of documenting and visualizing a conceptual data model.

51. Normalization The process based on the business rules for data
a set of data elements (attributes) are arranged in a mathematically minimum set of tables (relations), within which all the attributes are dependent on a primary key attribute (the key).

52. Normalization Model
The SA/Normalization method is based on the use of decomposition rules, which enable one to decompose tables/relations.
Database design starts with flat tables/relations, each of which is created out of a data stores in the DFDs and then decomposed into the normal form relations. No conceptual schema of the enterprise is created to express the semantics of its information structure.
The SA/IA method is based on the use of grouping rules which map simple relationships in the binary-relationship data model onto normal form relationships.
The relational model and the normalization method have been criticized for being too detailed to use at the initial design stage, and for lacking a semantic structure for making unambiguous choices in modeling the enterprise.
The IA method incorporates a semantic model of the enterprise which captures its essential semantic features from which the normal form relations are derived.

53. Conversion into Normalized Record Types
For every data flow which either enters or emanates from a data store (in the leaf level DFDs), the integral data elements are identified
For every data store, a list of the data elements which are entering and emanating are drawn up
The dependencies among all the data elements are analyzed, and the normalization rules are applied in steps so that at every step a given relation is split into more “simple” relations
Every relation has a key which consists of one or more data elements
Every non-key data element functionally depends on that entire key and not on part of it
No non-key data element depends on any other non-key data element in the relation (there are no transitive dependencies)

54. Conversion into Normalized Record Types
Enter exams dates & rooms
List of Exams details D1
Exams File
Details of Exams
Details of Exams
for lecturer
for students
Notify Lectures
Notify Students

55. De-Normalization The process of selectively
combining two or more normalized tables into one, or
decomposing one normalized table into two or more

56. Part Description for Model for General Motors
“Part #123 that is supplied by GM was assembled on bus 456 on May 28, 1996” is decomposed into the following elementary sentences:
a). A part... is supplied by a manufacturer...
b). A part... was assembled on a bus...
c). The assembly [part*bus] was performed on a date...

57. Part Distribution Model for General Motors
Part (p#)
Manufacturer (name)
Supplier of
Supplied of

58. Relationship Types
a). One-to-one (1:1): means that an occurrence if one OT uniquely determines an occurrence of other OT - and vice-versa
b). One-to-many (1:n): means that an occurrence of one OT determines an occurrence of the other OT - but not vice-versa
c). Many-to-many (n:m):means that an occurrence of one OT can be related to many occurrences of other OT - and vice-versa

59. GM Parts Assembly Distribution Model
Bus
(License #)
Manu-facturer (name)
Part (p#)
Supplier
Date (Calc. date)
Date of Assembly

60. Data Warehouse
An intermediate, read-only store (usually based in a purchased RDBMS product) and the programs that manage it.
Contains recent and summarized data extracted from across some or all of the legacy data systems
Presents a subject-based view

61. Functional Dependency
Mathematical term for the key relationship (using rational terminology) between data elements. A data element (attribute) that is functionally dependent on another data element (the key) will always exist in a relation (table) such that a unique value for the key will always “determine” or “locate” or “define a unique value of” the dependent.

62. Metadata
Data about data that is generally extracted from an existing system or created for a new system and stored in a design repository for developers to use in maintaining or extending the system during its lifecycle
Metadata refers to the table, attribute, and key definitions contained in the catalog of a relational database. It can also mean the business rules for data designed for a new design, or the business rules for data thought to be enforced in a legacy system (semantic data structure, sometimes called meta-data, or meta2 data).
The actual syntactic and semantic data structure (not just what the documentation might say), including a complete synonym and homonym map, plus the business rules for data that are actually being enforced in the legacy system.

63. Business Administration
Graduate School of
Business Administration
Loyola University