ADVANCED DATABASE SECURITY

 ADVANCED DATABASE SECURITY

(MTCSPE3001A)

Assignment Questions

UNIT I: Database Basics & SQL

Bloom Level 3 – Apply

1. Apply the concept of data abstraction by giving real-life examples of each level.

2. Write a SQL query to display names and salaries of employees earning more than ₹50,000.

3. Draw an ER diagram for a library management system.

4. Demonstrate the process of converting an ER model into a relational schema.

5. Formulate a SQL query to fetch customer details who have placed orders in the last 30 days.

Bloom Level 4 – Analyze

6. Analyze the differences between a schema and an instance with suitable examples.

7. Differentiate between logical and physical data independence with examples.

8. Compare ER model and Relational model in terms of data representation and usage.

9. Given a SQL query, identify and explain its components (SELECT, FROM, WHERE).

10. Analyze a poorly structured SQL query and suggest improvements.

Bloom Level 5 – Evaluate

11. Evaluate the effectiveness of SQL in querying large databases.

12. Critically assess the limitations of the ER model in representing complex relationships.

13. Justify the use of relational databases over file systems with examples.

14. Assess how data abstraction improves database performance and usability.

15. Evaluate SQL’s role in enforcing data integrity.

UNIT II: Introduction to Database Security

Bloom Level 3 – Apply

1. Apply access control concepts to a hospital database system.

2. Demonstrate how cryptographic techniques secure data in transit and at rest.

3. Illustrate the structure of a statistical database and its use in government data.

4. Apply SQL GRANT and REVOKE commands to manage access.

5. Create an access control list (ACL) for a university student portal.

Bloom Level 4 – Analyze

6. Analyze various types of security threats databases face.

7. Compare discretionary access control and mandatory access control with examples.

8. Analyze how cryptographic data protection differs from access control.

9. Examine how SQL handles security features like roles and permissions.

10. Compare the advantages and limitations of statistical databases.

Bloom Level 5 – Evaluate

11. Evaluate the role of databases in supporting organizational security policies.

12. Judge the effectiveness of cryptographic data protection in preventing data breaches.

13. Evaluate the importance of SQL security features in multi-user systems.

14. Critically examine the trade-offs between performance and security in database systems.

15. Justify the need for security mechanisms even in isolated database systems.

UNIT III: Security Methods and Techniques

Bloom Level 3 – Apply

1. Demonstrate how to use SQL views to limit data exposure.

2. Apply data masking to protect sensitive information in a database.

3. Write SQL triggers to track unauthorized modifications.

4. Illustrate row-level security using example SQL commands.

5. Use escaping techniques to prevent SQL injection in user input.

Bloom Level 4 – Analyze

6. Analyze the role of triggers in enhancing security.

7. Compare column-level and row-level access control with examples.

8. Examine the effectiveness of change tracking for detecting unauthorized access.

9. Distinguish between symmetric and asymmetric encryption in databases.

10. Analyze how views can support security while ensuring data usability.

Bloom Level 5 – Evaluate

11. Evaluate different access control models in the context of database security.

12. Assess the use of data masking in protecting personally identifiable information (PII).

13. Judge the impact of encryption on database performance and security.

14. Justify the need for query escaping in web applications.

15. Evaluate change tracking tools as part of a database audit mechanism.

UNIT IV: Data Integrity & Backup

Bloom Level 3 – Apply

1. Apply referential integrity rules to a banking database.

2. Demonstrate how to perform a full database backup using SQL tools.

3. Illustrate how domain integrity constraints ensure data validity.

4. Use SQL commands to enforce table-level constraints.

5. Show how to configure monitoring tools to track user activity.

Bloom Level 4 – Analyze

6. Analyze how different types of integrity constraints ensure data consistency.

7. Compare integrity constraints and triggers in terms of their roles.

8. Examine how backup strategies differ for small and large databases.

9. Analyze the importance of transaction logs in backup and recovery.

10. Distinguish between logical and physical database backups.

Bloom Level 5 – Evaluate

11. Evaluate the effectiveness of built-in database integrity features.

12. Judge the role of regular backups in disaster recovery planning.

13. Assess the reliability of database monitoring tools in detecting suspicious activity.

14. Critically evaluate whether constraints limit or enhance database performance.

15. Justify the use of foreign keys in maintaining relational integrity.

UNIT V: Security Analysis Tools

Bloom Level 3 – Apply

1. Apply penetration testing methods on a test database.

2. Demonstrate how a SQL injection attack works with a basic example.

3. Use a database security scanner to identify vulnerabilities.

4. Illustrate how to write a simple script to detect weak passwords in a database.

5. Apply input validation techniques to prevent SQL injection.

Bloom Level 4 – Analyze

6. Analyze the causes and consequences of SQL injection attacks.

7. Compare manual vs automated database security analysis.

8. Examine the working of a popular open-source database security scanner.

9. Distinguish between false positives and true threats in vulnerability reports.

10. Analyze how security misconfigurations contribute to database breaches.

Bloom Level 5 – Evaluate

11. Evaluate different tools used for database security analysis.

12. Judge the adequacy of SQL injection prevention techniques.

13. Critically assess the benefits and limitations of writing custom security tools.

14. Evaluate how regular audits can improve database security posture.

15. Justify the need for continuous monitoring even after initial hardening.

Social Network Analysis

 

1: Introduction & Tools

1. Define social network analysis and explain its importance in real-world systems.

2. Describe the basic components of a graph. How are these used in network modeling?

3. Explain the differences between directed and undirected networks with suitable examples.

4. Write a Python snippet using NetworkX to create and visualize a simple graph.

5. Describe the main features and uses of Google Colab for social network analysis tasks.

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 2: Network Measures

1. Define degree centrality and closeness centrality. How do they differ in interpretation?

2. What is betweenness centrality? Explain its significance in identifying bridge nodes.

3. Describe clustering coefficient. What does a high clustering coefficient imply?

4. Explain the concept of average path length in a network.

5. Write a Python code using NetworkX to compute degree centrality and plot it.

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3: Network Growth Models

1. Compare and contrast the Erdős–Rényi model and Barabási–Albert model.

2. Explain the concept of preferential attachment in network evolution.

3. How do random graphs help in understanding real-world network structures?

4. What are small-world networks? Explain with the help of the Watts–Strogatz model.

5. Describe the steps to generate a scale-free network using NetworkX.

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 4: Link Analysis

1. Describe the PageRank algorithm and its applications.

2. What is the HITS algorithm? How does it differ from PageRank?

3. Explain the concepts of hub and authority scores.

4. How does link analysis help in ranking web pages?

5. Illustrate with code how to compute PageRank of a graph in NetworkX.

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 5: Graph Visualization & Community Detection I

1. Why is graph visualization important in network analysis?

2. Discuss different layout algorithms available for visualizing graphs.

3. What are communities in a network? Give real-world examples.

4. Explain the Girvan–Newman algorithm for community detection.

5. Demonstrate a visualization of communities using NetworkX and matplotlib.

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 6: Community Detection II

1. What is modularity? How does it help in evaluating community structures?

2. Explain the Louvain method for community detection.

3. Compare the Girvan–Newman and Louvain algorithms in terms of accuracy and efficiency.

4. How can overlapping communities be identified in a network?

5. Write code to detect communities in a graph and calculate modularity using NetworkX.

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7: Link Prediction

1. What is link prediction and why is it important in social networks?

2. Describe common similarity-based methods for link prediction.

3. Explain how machine learning can be applied to the link prediction problem.

4. Describe and compare Jaccard Coefficient and Adamic-Adar Index.

5. Implement a simple link prediction model using NetworkX.

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 8: Cascade Behavior and Network Effects

1. Explain the concept of information cascade with an example.

2. How does the threshold model of behavior adoption work in networks?

3. What are network externalities? How do they affect user behavior?

4. Describe diffusion models used in analyzing cascade behaviors.

5. Simulate a simple cascade process using a Python script.

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9: Anomaly Detection

1. What constitutes an anomaly in a network?

2. Explain how network topology can help detect anomalous nodes or links.

3. Discuss different types of anomalies (e.g., structural, temporal).

4. Describe a method to detect fraud in e-commerce networks.

5. Write a Python function to identify nodes with unusual degree distributions.

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10: Intro to Deep Learning & Graph Representation I

1. What are the challenges in applying deep learning to graphs?

2. Define graph embeddings and explain their purpose.

3. Describe the concept of node2vec and how it captures network features.

4. How does graph structure differ from regular data in DL applications?

5. Illustrate how to convert a graph into a format usable by deep learning models.

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11: Graph Representation II

1. Explain Graph Convolutional Networks (GCNs) and their working principles.

2. How is information propagated in GCNs?

3. Describe one practical use case of Graph Neural Networks.

4. What are the limitations of shallow embedding methods like DeepWalk?

5. Implement a basic graph representation learning model using node2vec.

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12: Applications & Case Studies

1. Describe a real-world application where social network analysis improved outcomes.

2. How can network science help in analyzing fake news spread?

3. Discuss a case study involving anomaly detection in financial transaction networks.

4. Explain the role of SNA in recommendation systems.

5. Summarize key learnings from the course and their practical significance.

Strategic Management

 

1: Introduction to Strategic Management

1. Explain the significance of strategic management in achieving organizational goals.

2. Discuss the steps involved in the strategic management process with examples.

3. Analyze how the liberalization of the Indian economy in 1991 impacted corporate strategy.

4. Compare corporate strategy with business and functional strategies.

5. Illustrate with examples how strategic management leads to competitive advantage.

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2: Board of Directors and Top Management

1. Describe the structure and key functions of the Board of Directors in a corporate setting.

2. Explain the strategic role played by top management in shaping the vision of a company.

3. Discuss corporate governance and its influence on strategic decision-making.

4. Analyze the challenges faced by Boards in the Indian context while performing their duties.

5. What skills should top executives possess to ensure effective strategic planning?

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 3: Environmental and Internal Scanning

1. Explain the purpose and process of environmental scanning in strategic planning.

2. Differentiate between EFAS and IFAS with suitable examples.

3. How does industry analysis help in identifying strategic opportunities and threats?

4. Describe the value chain model and its application in internal analysis.

5. Using a hypothetical case, explain how to synthesize internal and external factors.

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4: Strategy Formulation

1. Explain the process of preparing a Strategic Factors Analysis Summary (SFAS).

2. Distinguish between corporate-level strategy and business-level strategy with examples.

3. Evaluate how strategic alternatives are assessed and selected in organizations.

4. Describe the role of functional strategies in the overall strategic framework.

5. How do internal and external factors influence strategic choice?

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5: Strategy Implementation

1. Explain how organization structure supports or hinders strategy implementation.

2. Discuss the impact of corporate culture on successful strategy execution.

3. Analyze diversification strategies using real-world company examples.

4. Explain how mergers and acquisitions contribute to strategic growth.

5. Identify and explain key challenges in implementing corporate strategies effectively.

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6: Evaluation and Control

1. Describe the steps involved in evaluating strategic performance.

2. How does the Balanced Scorecard help in monitoring and controlling strategy?

3. Discuss the role of feedback mechanisms in strategic control systems.

4. Analyze the benefits of using Strategic Information Systems for performance evaluation.

5. Provide a framework for measuring the success of a newly implemented strategy.

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7: Strategic Enablers – R&D, IT

1. Explain the strategic significance of R&D in innovation-driven industries.

2. How does IT support strategic decision-making and competitive positioning?

3. Analyze the integration of IT strategy with business strategy using an industry example.

4. Discuss the challenges of managing R&D as a strategic function.

5. Evaluate the role of digital transformation in reshaping strategic planning.

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8: KM, Technology, Strategic Risk

1. Explain the process of Knowledge Management and its strategic importance.

2. Discuss the types of strategic risks faced by global businesses today.

3. How can organizations build resilience against strategic risks?

4. Analyze the role of emerging technologies in transforming strategic capabilities.

5. Discuss how KM supports continuous improvement and innovation in strategy.

More Questions 

1: Introduction to Strategic Management

1. Define strategic management. How does it differ from operational management?

2. Explain the key elements of the strategic management process.

3. What is the significance of corporate strategy in an organization?

4. Discuss the role of vision and mission statements in strategy formulation.

5. How does strategic management provide a competitive edge in a liberalized economy?

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2: Board of Directors and Top Management

1. What are the primary roles and responsibilities of the Board of Directors?

2. How does top management influence strategic decision-making?

3. Explain the importance of corporate governance in strategic management.

4. Compare and contrast board functioning in Indian companies versus global practices.

5. What are the essential skills required by top executives for effective strategic leadership?

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 3: Environmental and Internal Scanning

1. What is environmental scanning and why is it important for strategy formulation?

2. Describe the components of the external environment in strategic analysis.

3. How is the EFAS (External Factors Analysis Summary) prepared?

4. Explain the concept of value chain analysis and its strategic significance.

5. Discuss how internal factors are analyzed using IFAS (Internal Factors Analysis Summary).

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 4: Strategy Formulation

1. What is SFAS (Strategic Factors Analysis Summary) and how is it derived?

2. Differentiate between business-level and corporate-level strategies.

3. Explain the process of choosing an appropriate strategic alternative.

4. Describe the role of functional strategy in supporting business strategy.

5. What factors should be considered while making strategic choices?

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5: Strategy Implementation

1. How does organizational structure affect strategy implementation?

2. What is the relationship between corporate culture and strategy execution?

3. Discuss the strategic rationale behind mergers and acquisitions.

4. Explain how diversification can be used as a strategic tool.

5. Identify key barriers to successful strategy implementation.

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 6: Evaluation and Control

1. What are the key steps in strategic evaluation?

2. Explain the role of feedback in strategic control systems.

3. Describe the concept of Balanced Scorecard and its application in strategy control.

4. How can Strategic Information Systems support evaluation and control?

5. Discuss how companies can measure the effectiveness of their strategies.

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 7: R&D and IT as Strategic Enablers

1. How does R&D contribute to sustaining competitive advantage?

2. Discuss the strategic role of Information Technology in modern organizations.

3. Explain the interlinkages between innovation, R&D, and strategy.

4. What challenges do firms face while integrating IT with business strategy?

5. How can R&D and IT be aligned with long-term corporate objectives?

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8: Knowledge Management, Technology & Strategic Risk

1. Define Knowledge Management and its relevance in strategic management.

2. Discuss how technology acts as a driver of strategic change.

3. What are the different types of strategic risk organizations face today?

4. Explain how companies can proactively manage strategic risks.

5. How does KM enhance organizational learning and decision-making?

DATA PRIVACY Syllabus

 DATA PRIVACY MTCSPE1001D

Course objectives:

1. To create architectural, algorithmic and technological foundations for the maintenance of the privacy of individuals, the confidentiality of organizations, and the protection of sensitive information, despite the requirement that information be released publicly or semi-publicly.

Course outcomes: After successful completion of this course, students will be able to:

1. Understand the concepts of privacy in today’s environment.

2. Obtain the understanding of how automation is changing the concepts and expectations concerning privacy and the increasingly interconnected issue of security.

3. Obtain the knowledge of the role of private regulatory and self-help efforts.

4. Have an understanding of how emerging issues are affecting society and business, with a concentration on how information security must shape corporate practices.

Course Contents: 

UNIT I

Introduction- Fundamental Concepts, Definitions, Statistics, Data Privacy Attacks, Data linking and profiling, access control models, role-based access control, privacy policies, their specifications, languages and implementation, privacy policy languages, privacy in different domains- medical, financial, etc. 

UNIT II

Data explosion- Statistics and Lack of barriers in Collection and Distribution of Person- specific information. Mathematical model for characterizing and comparing real-world data sharing practices and policies and for computing privacy and risk measurements, Demographics and Uniqueness.

UNIT III

Protection Models- Null-map, k-map, Wrong map Survey of techniques- Protection models (null-map, k-map, wrong map), Disclosure control, Inferring entity identities, Strength and weaknesses of techniques, entry specific databases. Computation systems for protecting delimited data- MinGen, Datafly, Mu-Argus, k-Similar, Protecting textual documents: Scrub. 

UNIT IV

Technology, Policy, Privacy and Freedom- Medical privacy legislation, policies and best practices 

UNIT V

Examination of privacy matters specific to the World Wide Web, Protections provided by the Freedom of Information Act or the requirement for search warrants.

References:

1. B. Raghunathan, The Complete Book of Data Anonymization: From Planning to Implementation, Auerbach Pub, 2013.

2. L. Sweeney, Computational Disclosure Control: A Primer on Data Privacy Protection, MIT Computer Science, 2002.

DCCN: Course objectives and Course Outcomes

 This course introduces students to the fundamental concepts of data communication and computer networks. It covers the basic components of network systems, transmission media, multiplexing, switching technologies, error detection and correction techniques, medium access control protocols, and network topologies. The course also explores Internet protocols, transport layer mechanisms, and application layer functions, providing students with a comprehensive understanding of how data is transmitted and processed across networks.

Course Objectives:

1. To introduce students to the basic components and concepts of data communication and networking.
2. To provide a comprehensive understanding of transmission media, multiplexing and switching.
3. To explain error detection and correction techniques, and medium access control.
4. To explain the functions and protocols associated with Internet layer, Transport and Application layers.
5. To understand the various network topologies and network devices.

Course Outcomes:

After successful completion of this course the student will be able:

1. To understand the fundamentals of data communication and computer networks.
2. To understand transmission media, multiplexing and switching.
3. To gain the ability to implement and analyze error detection and correction techniques and understand medium access control methods.
4. To be capable of describing Internet and Transport layer protocols.
5. To identify and explain the various components and topologies of data communication systems

DCCN:BOOKs

 book

Data-Communications-and-Networking-By-Behrouz-A.Forouzan

Computer Network (Andrew S Tanenbaum)

Type of connection

 Two types of connections

a. Point-to-point

b. Multipoint

In point-to-point connection the two devices are connected by a dedicated link. The entire capacity of

the link is reserved for transmission between those two devices.

A multipoint (also known as multidrop) connection is one in which more than two specific devices share

a single link. The capacity of the channel is shared either spatially or temporally.

Computer Network (Difination)

 Network: Definition:

• A network is set of devices (nodes) connected by communication links (media)
• A node can be a computer, printer or other device capable of sending and/or receiving data
• Link connecting the devices are often called communication channels
• Most network use distributed processing.

Distributed Processing Networks use distributed processing in which a task divided among multiple computers. Separate computers handle a subset instead of a single machine responsible for all aspects of a process.

Performance Performance can be measured in terms of transit time, response time, number of users, type of transmission medium, and capabilities of the connected hardware and the efficiency of the software.

Transit time The time required for a message to travel from one device to another.

Response time The time spent between an inquiry and a response

Reliability It is measured by the frequency of failure and time required to recover from a failure.

Security Network security is protecting data from unauthorized access.

Direction of data flow

 Two devices can communicate in simplex, half-duplex or full-duplex mode.

Simplex:

In simplex mode, the communication is unidirectional. Only one of the devices on a link can transmit;

the other can only receive.

Ex. Keyboard and monitor

Half-duplex

In half-duplex mode, each station can both transmit and receive but not at the same time. When one

device is sending, the other can only receive.

Ex. Walkie-talkies and CB (citizen band radios)

Full-duplex

In full-duplex mode, both stations can transmit and receive simultaneously.

Ex. Telephone network

When two people are communicating by a telephone line, both can listen and talk at the same time.

Lan, Man and Wan (Distance Comparison)

 

Internetwork

 Connection of two or more networks by the use of internetworking devices which include routers

and gateways

 Internet is a generic term used to mean an interconnection of networks

 The Internet is the name of a specific worldwide network.

protocol

 A protocol is essentially a set of rules that governs how data is communicated between systems. These protocols have three fundamental elements:

1. Syntax: This covers the data formats and signal levels - essentially the structure and form that the data must follow.
2. Semantics: This involves control information and error handling - the meaning behind the data and how to respond when something goes wrong.
3. Timing: This addresses speed matching and sequencing - ensuring systems can communicate at compatible rates and in the correct order.

Data Privacy Question Bank

syllabus 

Question Bank 

DATA PRIVACY MTCSPE1001D 

UNIT I Questions

1. Define data linking and profiling in the context of privacy. Discuss how these techniques can compromise individual privacy with relevant examples.
2. Compare and contrast different access control models with special emphasis on role-based access control. How do they contribute to ensuring data privacy?
3. Explain the concept of privacy policies. What are the key components that should be included in a well-designed privacy policy language?
4. Discuss the unique privacy challenges in the medical domain. How do these challenges differ from those in the financial sector?
5. Analyze how fundamental privacy concepts have evolved with the advancement of technology. Provide examples of how traditional definitions of privacy may be inadequate in today's digital environment.
6. Evaluate the effectiveness of role-based access control in protecting sensitive information. What improvements can be made to strengthen its implementation?
7. Discuss the ethical considerations that should be incorporated into privacy policies. How do these ethical frameworks influence policy development?
8. Critically analyze the relationship between data privacy attacks and defensive measures. How has this relationship evolved over time?
9. Compare different privacy policy specification languages. What are their relative strengths and limitations in practical implementations?
10. Explain how the concept of privacy differs across cultures and legal systems. How should international organizations address these differences in their privacy frameworks?

UNIT II Questions

1. Explain the concept of "data explosion" and analyze its implications for individual privacy in the digital age. Provide relevant statistics to support your answer.
2. What are the primary barriers (or lack thereof) in the collection and distribution of person-specific information? Discuss both technical and non-technical factors.
3. Describe a mathematical model for characterizing real-world data sharing practices. How can such models be used to compute privacy risks?
4. Explain the relationship between demographics and uniqueness in the context of data privacy. How does this relationship impact re-identification risks?
5. Compare different approaches to measuring privacy risks in datasets. What metrics are commonly used and what are their limitations?
6. Analyze how advances in big data technologies have accelerated the data explosion phenomenon. What specific privacy challenges emerge from these technological developments?
7. Discuss how the concept of "informed consent" has been affected by modern data collection practices. Is traditional consent still meaningful in today's data ecosystem?
8. Evaluate the effectiveness of current mathematical models in quantifying privacy risks. What improvements could be made to make these models more accurate?
9. Describe how uniqueness patterns in data can be exploited for re-identification. What demographic factors contribute most significantly to uniqueness?
10. Compare the data sharing practices across different industries. How do their approaches to privacy protection differ and what factors influence these differences?

UNIT III Questions

1. Compare and contrast the null-map, k-map, and wrong map protection models. What are the strengths and weaknesses of each approach?
2. Explain the working principles of the Datafly system. How does it achieve privacy protection for delimited data?
3. Analyze the k-Similar approach to privacy protection. In what scenarios is it most effective, and what are its limitations?
4. Describe the methods used for inferring entity identities from supposedly anonymized data. How can organizations defend against such inference attacks?
5. Explain how the Scrub system works to protect textual documents. What types of identifiers can it detect and sanitize?
6. Evaluate the trade-off between data utility and privacy in different protection models. How can this balance be optimized for different use cases?
7. Compare MinGen and Datafly systems in terms of their approaches, effectiveness, and computational efficiency. In what scenarios would you prefer one over the other?
8. Analyze the technical challenges in implementing disclosure control mechanisms in large-scale databases. How can these challenges be addressed?
9. Discuss the evolution of protection models from simple suppression techniques to more sophisticated approaches. What factors have driven this evolution?
10.  Evaluate the effectiveness of current techniques for protecting textual data compared to structured data. What unique challenges does textual data present for privacy protection?

UNIT IV Questions

1. Analyze the relationship between technology, policy, and freedom in the context of data privacy. How do these elements interact in shaping privacy outcomes?
2. Discuss the key provisions of major medical privacy legislation. What protections do they offer to patients regarding their health information?
3. Evaluate the effectiveness of current medical privacy best practices. What gaps exist and how might they be addressed?
4. Compare privacy policies and practices in healthcare organizations before and after the implementation of medical privacy legislation. What changes have occurred?
5. Discuss the challenges in balancing medical research needs with patient privacy. How can healthcare institutions maintain this balance effectively?
6. Analyze the impact of emerging technologies like AI and IoT on medical privacy policies. How should regulations evolve to address these technological developments?
7.  Evaluate the effectiveness of self-regulatory approaches to privacy protection in the healthcare sector. Under what conditions are they most successful?
8. Compare medical privacy legislation across different countries or jurisdictions. What common principles exist, and what significant differences can be observed?
9. Discuss the role of patient consent in the context of medical data sharing. How has the concept of consent evolved with digitization of health records?
10.  Analyze the particular privacy challenges associated with genetic and genomic data. What special protections are needed for this type of information?

UNIT V Question

1. Analyze the unique privacy challenges posed by the World Wide Web. How have these challenges evolved over time?
2. Evaluate the protections provided by the Freedom of Information Act in the context of privacy. What are its strengths and limitations?
3. Discuss the legal requirements for search warrants in the digital age. How do these requirements apply to digital evidence and online activities?
4. Compare privacy protection approaches across different web-based services. What common strategies are employed and how effective are they?
5. Analyze the role of user awareness and self-protection in maintaining privacy on the World Wide Web. What tools and techniques are available to individual users?
6.  Evaluate the effectiveness of current browser privacy features and extensions. How do they protect users, and what limitations do they have?
7. Discuss the tensions between freedom of information principles and privacy protection. How can these competing interests be balanced in policy and law?
8. Analyze the evolution of search warrant requirements for digital content. How have courts interpreted the Fourth Amendment in the context of digital evidence?
9. Compare different jurisdictional approaches to web privacy. How do regulatory frameworks like GDPR and CCPA differ in their protection models?
10. Evaluate the role of data localization policies in protecting privacy. What are the implications of cross-border data transfers for individual privacy?

 

Notes on Protocols in Computer Networks

 

Definition of a Protocol

In computer networks, communication occurs between entities (devices, applications, or systems) that exchange information. For successful communication, entities must follow a protocol—a set of rules governing data exchange. A protocol defines:

• What is communicated (data format).

• How it is communicated (transmission method).

• When it is communicated (synchronization and speed).

Key Elements of a Protocol

1. Syntax

   • Refers to the structure or format of the data.

   • Example: A protocol may define:

     • First 8 bits = Sender’s address.

     • Next 8 bits = Receiver’s address.

     • Remaining bits = Actual message.

2. Semantics

   • Refers to the meaning of each part of the data.

   • Example:

     • Does an address field indicate the destination or a routing path?

     • What does a specific bit pattern represent (e.g., error code, control signal)?

3. Timing

   • Ensures synchronization and speed matching between sender and receiver.

   • Includes:

     • When data should be sent (e.g., flow control).

     • How fast data can be transmitted (e.g., matching sender/receiver speeds).

   • Example: If a sender transmits at 100 Mbps but the receiver processes at 1 Mbps, data loss occurs due to overload.

Importance of Protocols

• Enable standardized communication between different systems.

• Ensure reliable, efficient, and error-free data transfer.

• Facilitate interoperability between devices from different manufacturers.

Examples of Protocols

• HTTP (Hypertext Transfer Protocol) – Web communication.

• TCP/IP (Transmission Control Protocol/Internet Protocol) – Internet data transfer.

• Ethernet – LAN communication.

Conclusion

Protocols are essential for structured and efficient network communication, ensuring that devices interpret data correctly and synchronize transmissions effectively.

Client-Server Architecture

 Definition: Client-Server Architecture is a network architecture where multiple clients (users) request and receive services from a centralized server. The server hosts, manages, and delivers resources or services to clients over a network.

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Key Components:

• Client:

  • A device or software application that requests services or resources from the server.

  • Examples: Web browsers, mobile apps, desktop apps.

• Server:

  • A powerful system or software that provides services or resources to clients.

  • Examples: Web servers, database servers, file servers.

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Diagram:

          +-----------+         Request         +-----------+
          |           | ---------------------> |           |
          |  Client   |                        |   Server  |
          | (Browser) | <--------------------- | (Web/App) |
          +-----------+        Response        +-----------+
                |                                     |
          +-----------+                        +-----------+
          |  Client   |                        | Database  |
          | (Mobile)  |                        |  Server   |
          +-----------+                        +-----------+

You can imagine:

• Clients send requests to the server (like asking for a webpage).

• Server processes the request and sends a response back (like returning the webpage).

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Advantages:

• Centralized control.

• Easier maintenance and security.

• Scalability (add more clients easily).

Disadvantages:

• Server bottlenecks if overloaded.

• Single point of failure (if server goes down).

Data representation

Data Representation

Information can be in any form such as text, numbers, images, audio, and video.

1. Text

• Text is represented as a bit pattern.

• The number of bits in a pattern depends on the number of symbols in that language.

• Code is the set of bit patterns designed to represent text symbols.

ASCII (American Standard Code for Information Interchange)

• Developed by ANSI (American National Standards Institute).

• Uses 7 bits for each symbol.

Extended ASCII

• To make the size 1 byte (8 bits), an extra 0 is added to the left of the ASCII bit patterns.

• This does not change the value of the pattern.

Unicode

• Used to represent symbols or text in any language.

• Uses 32 bits to represent characters.

ISO (International Organization for Standardization)

• Designed a 32-bit pattern.

• Can represent up to 4,294,967,296 symbols.

2. Numbers

• Represented using bit patterns.

• Instead of ASCII, numbers are directly converted to binary.

3. Images

• Represented by bit patterns.

• An image is divided into a matrix of pixels (smallest element of an image).

• Each pixel is assigned a bit pattern.

• The size and value of the pattern depend on the image.

4. Audio

• Audio refers to the recording or broadcasting of sound or music.

• It is continuous, not discrete like text, numbers, or images.

5. Video

• Video refers to the recording or broadcasting of pictures or movies.

• It can be:

  • A continuous entity (like live streaming).

  • A combination of images (frames in a video).