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B.Tech. Computer Science and Engineering with Specialisation in Cyber Security and Forensics - IBM

program-details

As there is an enormous amount of data and to protect the data is one of the challenging tasks of various IT sectors. So, the Cyber Security and Forensics has become an hour of need of today’s society. This course will help the students to become the emerging Cyber Security Experts of the modern era.

Industry Immersion

MAJOR COURSES OFFERED

  • Python + Clean Coding
  • Data Visualization
  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Predictive Analysis
  • NoSQL
  • Devops
  • Data Sciences
  • Big Data Fundamentals
  • BlockChain Technology

eligibility criteria

Passed 10+2 examination with Physics/ Mathematics / Chemistry/ Computer Science/Electronics/ Information Technology/ Biology/ Informatics Practices/ Biotechnology/ Technical Vocational subject/ Agriculture/ Engineering Graphics/ Business Studies/ Entrepreneurship with atleast 50% marks
OR
Passed min. 3 years Diploma examination with at least 45% marks (40% marks in case of candidates belonging to reserved category) subject to vacancies in the First Year, in case the vacancies at lateral entry are exhausted.
(The Universities will offer suitable bridge courses such as Mathematics, Physics, Engineering drawing, etc., for the students coming from diverse backgrounds to prepare Level playing field and desired learning outcomes of the programme) 

Admission criteria

online and offline both.

Duration

4 Years

related program

Curriculum

1ST SEMESTER SUBJECTS

Applied Chemistry introduces fundamental chemical principles and their engineering applications, covering water chemistry, corrosion, materials, polymers, fuels, nanomaterials, spectroscopy, and green chemistry for sustainable technological development.
Course Outcome:
At the end of the course, the students will be able to achieve following outcomes:
CO1: Apply concepts of solution chemistry and water treatment for engineering applications and solve numerical problems related to concentration and hardness of water.
CO2: Describe the principles and applications of spectroscopic techniques (UV-Visible, IR, and NMR) for molecular characterization.
CO3: Explain the principles, classifications, and applications of chemical sensors used in environmental, biomedical, and industrial fields.
CO4: Classify polymers and explain their properties, synthesis, and applications in engineering and industrial sectors.
CO5: Analyze stereo chemical properties of organic molecules, determine molecular configurations, and interpret conformational stability.
CO6: Explain the mechanisms of organic reactions including substitution, addition, and elimination reactions, and apply them in basic organic synthesis.

Applied Chemistry Laboratory develops practical skills through experiments involving water analysis, corrosion, chemical reactions, material characterization, solution preparation, and analytical techniques, emphasizing safety, accuracy, and scientific interpretation.
Course Outcome:
At the end of the course, the students will be able to:
CO1: Demonstrate proficiency in laboratory safety practices, handling of chemical reagents, preparation of standard solutions, and the use of volumetric analysis apparatus.
CO2: Perform acid–base and redox titrations to determine the concentration or strength of unknown solutions and analyze experimental results accurately.
CO3: Determine physicochemical properties of samples, including pH, total hardness, total alkalinity, surface tension, viscosity, redox potential, and partition coefficient using appropriate analytical techniques.
CO4: Carry out organic chemistry experiments, including the preparation of iodoform, differentiation between aldehydes and ketones using qualitative tests, and separation of compounds by thin-layer chromatography.
CO5: Synthesize polymers or drugs and evaluate the properties of oils through saponification and acid value determination using standard laboratory methods.
CO6: Record experimental observations, perform calculations, interpret analytical data, and prepare laboratory reports while adhering to good laboratory practices and safety guidelines.

This course introduces fundamental concepts of electrical and electronic engineering, including circuits, electrical machines, semiconductor devices, digital systems, measurements, and practical applications in engineering and technology.
Course Outcome:
At the end of the course the students will be able to:
CO-1: To Understand the fundamental concepts of electricity, such as voltage, current, resistance, power, and energy.
CO-2: To understand AC and DC fundamentals and measure power factor in given circuit.
CO-3: Describe the characteristics and applications of diodes and transistors.
CO-4: To understand Electrical safety and explain the construction, working principle, performance and applications of transformers.
CO-5: Understand number systems, logic gates, and basic combinational circuits.
CO-6: Apply Boolean algebra and Karnaugh maps to simplify and design digital logic circuits.

This laboratory develops practical skills in electrical circuits, measurements, electronic components, semiconductor devices, digital circuits, and basic electrical systems through experiments, testing, analysis, and troubleshooting techniques.
Course Outcome:
At the end of the course, the students will be able to:
CO1: Understand the fundamental concepts of electricity, such as voltage, current, resistance, power, and energy
CO2: Develop the ability to analyze electrical circuits using techniques such as Ohm's law, Kirchhoff's laws, and network theorems.
CO3: Plot the I-V characteristics of various semiconductor devices.
CO4: Design electrical and electronic circuits by utilizing various components.
CO-5: Verify the truth tables of various logic gates

Programming Concepts introduces the fundamentals of computer programming, including problem-solving techniques, algorithms, flowcharts, data types, operators, control structures, functions, and arrays, using a structured programming language.
Course Outcome:
At the end of the course, the students will able to be:
CO1: Describe the procedural and object-oriented paradigm with concepts of streams, classes, functions, data and objects.
CO2: Understand dynamic memory management techniques using pointers, constructors, destructors, etc.
CO3: Describe the concept of function overloading, operator overloading, virtual functions and polymorphism.
CO4: Understanding inheritance in OOP for code reusability and extensible design.
CO5: Demonstrate the use of various OOPs concepts with the help of programs.

Programming Concepts Lab provides hands-on practice in writing, debugging, and executing programs based on the concepts covered in programming Concepts, including control structures, functions, and arrays.
Course Outcome:
At the end of the course, the students will able to be:
CO1: Describe the procedural and object-oriented paradigm with concepts of streams, classes, functions, data and objects.
CO2: Understand dynamic memory management techniques using pointers, constructors, destructors, etc.
CO3: Describe the concept of function overloading, operator overloading, virtual functions and polymorphism.
CO4: Understanding inheritance in OOPs for code reusability and extensible design.
CO5: Demonstrate the use of various OOPs concepts with the help of programs.

This course provides evelops advanced concepts in multivariable calculus, vector calculus, differential equations, Laplace transforms, and numerical methods, equipping students with mathematical techniques for solving engineering problems.
Course Outcome:
At the end of the course, the students will be able to:
CO1: Able to verify some of the theoretical concepts learnt in the theory courses.
CO2: trained to visualize and conceptualize the engineering problems
CO3: Relate matrices and linear transformations, compute Eigen values and Eigen vectors of linear transformations.
CO4: Solve engineering problems by making use of ordinary differential equations.
CO5: Inter-relationship amongst the line integral, double and triple integral formulations.

Workshop Practices provides hands-on exposure to basic manufacturing trades such as carpentry, fitting, welding, sheet metal work, and plumbing, along with workshop safety practices.
Course Outcome:
At the end of the course, the students will be able to:
CO1: Prepare moulds, cores and wooden joints for basic manufacturing applications.
CO2: Perform basic welding operations and fabricate simple welded joints.
CO3: Carry out fitting and machining operations using conventional workshop tools and machines.
CO4: Fabricate simple products using sheet metal and forging processes.
CO5: Demonstrate basic electrical wiring, soldering and electronic circuit assembly practices.

Environmental Studies develops awareness of ecosystems, biodiversity, natural resources, pollution, climate change, environmental management, and sustainable development, encouraging responsible practices and informed solutions to environmental challenges.
Course Outcome:
At the end of the course, the students will be able to:
CO1: Analyse the impact of Biodiversity conservation on species and the environment.
CO2: Apply knowledge of environmental policies and legislations to evaluate and propose solutions for local and global environmental issues.
CO3: Implement environmental management plans to address campus environmental issues such as Waste disposal, water management, and sanitation.
CO4: Students will gain knowledge of the structure and function of ecosystems, biodiversity, and the importance of natural resources.
CO5: Recognize the interdependence between humans and the environment.

Communicative English-I develops foundational language skills in grammar, vocabulary, listening, speaking, reading, and writing for effective communication.
Course Outcome:
At the end of the course, the students will be able to:
CO1: Use standard English aptly in listening, speaking, and communicative situations
CO2: Write error-free sentences and short texts in English Language
CO3: Comprehend reading passages effectively
CO4: Demonstrate use of apt and relevant vocabulary at lower intermediate to intermediate level
CO5: Develop effective oral presentation skills, including audience analysis and body language
CO6: Apply audio-visual aids to enhance communication and improve pronunciation

This course develops an entrepreneurial mindset through self-awareness, creativity, innovation, opportunity recognition, problem-solving, communication, teamwork, leadership, and professional ethics. Students are introduced to the startup ecosystem, design thinking, business models, prototyping, value propositions, and idea pitching to encourage solution-oriented thinking and entrepreneurial initiative.
Course Outcome:
CO1: Demonstrate self-awareness, confidence and growth mindset.
CO2: Apply creativity and innovation tools to generate ideas and solutions.
CO3: Identify opportunities through analysis of real-life and community problems.
CO4: Demonstrate effective communication, teamwork and leadership skills.
CO5: Explain entrepreneurship concepts, startup ecosystem and support systems.
CO6: Develop and present a solution-oriented entrepreneurial project.

Python Programming covers Python syntax and semantics, data structures, control flow, functions, object-oriented programming, file handling, and modules, with applications in data-driven programming.
Course Outcome:
At the end of the course, the students will able to be:
CO1: Explain Python syntax, programming constructs, and problem-solving methodologies.
CO2: Develop programs using control structures, functions, recursion, and functional programming concepts.
CO3: Apply Python data structures and string processing techniques to solve computational problems.
CO4: Design modular programs using packages, modules, and file processing techniques.
CO5: Implement object-oriented solutions using classes, inheritance, polymorphism, and abstraction.
CO6: Utilize Python libraries for data analysis, visualization, and basic application development.

Python Programming Lab provides hands-on practice in writing and executing Python programs covering data structures, control flow, functions, object-oriented programming, and file handling.
Course Outcome:
At the end of the course, the students will be able to:
CO1: Write simple Python programs using basic syntax, control structures, and loops.
CO2: Apply Python’s data structures such as lists, dictionaries, tuples, and sets for data organization.
CO3: Implement modular programs using user-defined functions and recursion.
CO4: Handle file operations and apply exception handling for robust programs.
CO5: Demonstrate object-oriented programming concepts such as class, inheritance, and polymorphism.
CO6: Develop mini-projects using Python integrating multiple programming concepts.

2ND SEMESTER SUBJECTS

Applied Physics provides fundamental knowledge of mechanics, waves, optics, electricity, magnetism, and modern physics, emphasizing practical applications and problem-solving skills essential for engineering and technological development.
Course Outcome:
At the end of the course, the student will be able to-
CO1: Acquire knowledge about the Maxwell equation and Electromagnetic spectrum
CO2: Understand laser system in industries, laboratories and in communication
CO3: Acquire knowledge about the Crystallography, superconductivity and Magnetic materials.
CO4: Appreciate the need for quantum mechanics, wave particle duality, uncertainty principle etc. and their applications.
CO5: Understand the properties and synthesis of nanomaterials.

Applied Physics Laboratory develops practical skills through experiments in mechanics, optics, electricity, magnetism, and semiconductor physics, enabling students to verify theoretical concepts, analyze experimental data, and understand physical phenomena.
Course Outcome:
At the end of the course, students will be:
CO1: Able to verify some of the theoretical concepts learnt in the theory courses.
CO2: Trained in carrying out precise measurements and handling sensitive equipment.
CO3: Introduced to the methods used for estimating and dealing with experimental uncertainties and systematic errors.
CO4: Learn to draw conclusions from data and develop skills in experimental design.
CO5: Write a technical report which communicates scientific information in a clear and concise manner.

This course provides advanced concepts in multivariable calculus, vector calculus, differential equations, Laplace transforms, and numerical methods, equipping students with mathematical techniques for solving engineering problems.
Course Outcome:
At the end of the course, the students will be able to:
CO1: Apply derivative tests in optimization problems appearing in social sciences, physical sciences, life sciences and a host of other disciplines.
CO2: Understand conceptual variations while advancing from one variable to several variables in calculus.
CO3: Find numerical solutions of system of linear equations and check the accuracy of the solutions.
CO4: Solve initial and boundary value problems in differential equations using numerical methods.
CO5: To find and analyze solution of Laplace equation using different numerical methods.

Engineering Drawing covers principles of orthographic projection, sectional views, isometric and pictorial drawings, and an introduction to computer-aided drafting (CAD).
Course Outcome:
At the end of the course, the students will be able to:
CO1: Identify and use engineering drawing instruments, symbols, and conventions.
CO2: Understand and apply projection methods for points, lines, planes, and solids.
CO3: Create accurate 2D drawings using scales and dimensioning techniques.
CO4: Generate isometric (3D) drawings from 2D orthographic views.
CO5: Use basic CAD tools to create and modify engineering drawings digitally.

Universal Human Values, covering self-awareness, love, compassion, truth, non-violence, righteousness, sacrifice, and inner transformation. Students will develop ethical decision-making, empathy, emotional intelligence, self-reflection, and value-based thinking for personal and professional life.
Course Outcome:
CO1: Define and identify core universal human values and relate them to their own lives.
CO2: Demonstrate self-awareness and initiate personal transformation (Human Revolution)
CO3: Appreciate the importance of Sewa (selfless service), compassion, and empathy.
CO4: Apply principles of truth, non-violence, and moral responsibility in real-life dilemmas.
CO5: Evaluate ethical decisions involving sacrifice and righteousness through case studies.
CO6: Reflect on the relevance of renunciation and simplicity in modern life for inner peace.

Communicative English II builds on foundational language skills with emphasis on advanced communication, presentation skills, group discussions, and technical writing.
Course Outcome:
CO1: Able to apply advanced English language skills for effective academic and professional communication.
CO2: Able to communicate ideas, information and opinions confidently through effective speaking and listening skills.
CO3: Able to comprehend, analyze and interpret various forms of written and spoken English.
CO4: Able to prepare effective professional documents such as emails, reports, presentations and resumes.
CO5: Able to demonstrate effective interpersonal, presentation and communication skills in academic and professional situations.

Entrepreneurship Mindset-II covers business planning, understanding the startup ecosystem, funding avenues, and effective pitching of business ideas.
Course Outcome:
CO1: Able to understand and apply entrepreneurial concepts, principles and practices in identifying business opportunities.
CO2: Able to develop an entrepreneurial mindset through creativity, innovation, critical thinking and effective decision-making.
CO3: Able to identify customer needs and evaluate business ideas based on market opportunities and feasibility.
CO4: Able to develop basic business models and strategies for starting and managing entrepreneurial ventures.
CO5: Able to demonstrate leadership, teamwork, risk-taking and problem-solving skills for successful entrepreneurial development.

Cloud Application Development introduces the design, development, and deployment of scalable applications on cloud platforms, covering cloud service models, application architecture, APIs, containerization, and cloud-native development practices.
Course Outcome:
At the end of the course, the students will be able to:
CO1: Understand cloud computing fundamentals, service models, and their role in application development.
CO2: Design and develop cloud-native applications using appropriate architectural patterns.
CO3: Build and consume RESTful APIs for cloud-based application integration.
CO4: Apply containerization concepts for packaging and deploying cloud applications.
CO5: Deploy, scale, and manage applications on a public cloud platform.
CO6: Understand monitoring, security, and cost-management practices for cloud applications.

Cloud Application Development Lab provides hands-on practice in building, containerizing, and deploying applications on cloud platforms, including API development, cloud storage integration, and application monitoring.
Course Outcome:
At the end of the course, the students will be able to:
CO1: Set up and configure a cloud development environment and account.
CO2: Develop and test RESTful APIs for a cloud-hosted application.
CO3: Containerize applications using Docker and deploy them to a cloud platform.
CO4: Integrate cloud storage and database services with an application.
CO5: Deploy a complete cloud application and monitor its performance and usage.

3RD SEMESTER SUBJECTS

Covers fundamentals of database design, the relational model, SQL, normalization, and transaction management.
Course Outcome:
CO1: Understand basic concepts of database systems and the relational data model.
CO2: Design ER diagrams and convert them into relational schemas.
CO3: Formulate queries using SQL and relational algebra.
CO4: Apply normalization techniques to design efficient, redundancy-free databases.
CO5: Understand transaction management, concurrency control, and recovery techniques.
CO6: Explore concepts of indexing and query optimization.

Hands-on lab for designing databases and implementing SQL queries using RDBMS tools.
Course Outcome:
CO1: Create and manipulate databases using DDL and DML commands.
CO2: Write and execute simple to complex SQL queries.
CO3: Implement joins, subqueries, and views.
CO4: Design and implement PL/SQL procedures, functions, and triggers.
CO5: Apply normalization and ER modeling to real-world case studies.

Introduces linear and non-linear data structures along with algorithm design and analysis techniques.
Course Outcome:
CO1: Understand asymptotic notations and analyze the time/space complexity of algorithms.
CO2: Implement linear data structures such as arrays, stacks, queues, and linked lists.
CO3: Implement non-linear data structures such as trees and graphs.
CO4: Apply searching and sorting algorithms to solve computational problems.
CO5: Understand hashing techniques and their applications.
CO6: Design efficient algorithms using divide-and-conquer, greedy, and dynamic programming approaches.

Lab-based implementation of data structures and algorithmic problem-solving using a programming language.
Course Outcome:
CO1: Implement stacks, queues, and linked lists programmatically.
CO2: Implement tree and graph traversal algorithms.
CO3: Implement and compare various sorting and searching techniques.
CO4: Apply data structures to solve real-world computational problems.
CO5: Analyze the time complexity of implemented algorithms.

Covers advanced mathematical techniques including transforms, numerical methods, and probability essential for engineering applications.
Course Outcome:
CO1: Apply Laplace and Fourier transforms to solve engineering problems.
CO2: Solve differential equations using series solutions and special functions.
CO3: Apply numerical methods for solving algebraic and differential equations.
CO4: Understand concepts of probability and statistical distributions.
CO5: Apply vector calculus concepts to engineering problems.

Advanced Python Programming builds on foundational Python skills to cover advanced language features, functional programming, object-oriented design patterns, concurrency, database connectivity, and API-based application development.
Course Outcome:
CO1: Apply advanced Python constructs such as decorators, generators, and context managers to write efficient code.
CO2: Implement functional programming techniques using lambda functions, map, filter, and reduce.
CO3: Design robust applications using advanced object-oriented programming concepts and design patterns.
CO4: Apply multithreading and multiprocessing to build concurrent Python applications.
CO5: Integrate Python applications with databases and external APIs.
CO6: Develop and deploy a Python-based application integrating multiple advanced concepts.

Advanced Python Programming Lab provides hands-on practice in advanced Python concepts including decorators, generators, multithreading, database connectivity, web scraping, and API development.
Course Outcome:
CO1: Implement advanced Python constructs such as decorators, generators, and context managers.
CO2: Apply multithreading and multiprocessing concepts to build concurrent Python programs.
CO3: Connect Python applications to databases and perform CRUD operations.
CO4: Develop and consume RESTful APIs using Python frameworks.
CO5: Implement web scraping scripts to extract and process data.
CO6: Build a mini-project integrating advanced Python libraries and concepts.

Builds entrepreneurial thinking, business planning, and innovation skills through practical exposure.
Course Outcome:
CO1: Understand the entrepreneurial mindset and identify business opportunities.
CO2: Develop a basic business model and plan for a venture idea.
CO3: Understand fundamentals of innovation, risk-taking, and value creation.
CO4: Apply financial and marketing basics to a proposed venture.
CO5: Present and pitch a business idea effectively.

Cyber Security Fundamentals and Ethics introduces core concepts of information security, threat landscapes, security principles, and the ethical and legal frameworks governing cyberspace.
Course Outcome:
CO1: Understand fundamental concepts of cyber security, threats, and vulnerabilities.
CO2: Explain the CIA triad and core principles of information security.
CO3: Understand common attack vectors and defense mechanisms.
CO4: Understand cyber laws, ethics, and regulatory compliance requirements.
CO5: Analyze real-world cyber security incidents and their ethical implications.
CO6: Apply basic security practices to protect systems and data.

Cyber Security Fundamentals and Ethics Lab provides hands-on exposure to basic security tools, safe system configuration, and simulated exercises illustrating ethical and legal aspects of cyber security.
Course Outcome:
CO1: Configure basic security settings on operating systems and networks.
CO2: Use fundamental security tools to identify common vulnerabilities.
CO3: Demonstrate safe practices for password management and data protection.
CO4: Analyze case studies to identify ethical and legal issues in cyber security.
CO5: Prepare a basic security awareness or incident report.

Incident Response and Threat Hunting covers the incident response lifecycle, threat intelligence, proactive threat hunting techniques, and strategies for detecting and containing security breaches.
Course Outcome:
CO1: Understand the phases of the incident response lifecycle.
CO2: Apply threat intelligence concepts to identify potential security threats.
CO3: Understand proactive threat hunting methodologies and techniques.
CO4: Analyze logs and system artifacts to detect indicators of compromise.
CO5: Apply containment, eradication, and recovery strategies for security incidents.
CO6: Prepare incident response reports and post-incident review documentation.

Incident Response and Threat Hunting Lab provides hands-on practice with log analysis, forensic tools, and simulated incident scenarios to build practical detection and response skills.
Course Outcome:
CO1: Set up and use log collection and analysis tools.
CO2: Identify indicators of compromise using threat hunting tools.
CO3: Perform basic digital forensic analysis on compromised systems.
CO4: Simulate and respond to a security incident in a controlled lab environment.
CO5: Document findings and prepare an incident response report.

4TH SEMESTER SUBJECTS

Covers algorithm design paradigms, complexity analysis, and advanced algorithmic techniques for problem-solving.
Course Outcome:
CO1: Analyze the time and space complexity of algorithms using asymptotic notations.
CO2: Design algorithms using divide-and-conquer, greedy, and dynamic programming strategies.
CO3: Apply graph algorithms for shortest path, spanning tree, and network flow problems.
CO4: Understand backtracking and branch-and-bound techniques.
CO5: Analyze NP-completeness and classify problems based on computational complexity.
CO6: Design and evaluate efficient algorithms for real-world computational problems.

Lab-based implementation and performance analysis of algorithm design techniques.
Course Outcome:
CO1: Implement divide-and-conquer algorithms and analyze their performance.
CO2: Implement greedy and dynamic programming based solutions.
CO3: Implement graph algorithms for traversal, shortest path, and spanning trees.
CO4: Implement backtracking algorithms for constraint satisfaction problems.
CO5: Compare and evaluate algorithm efficiency using empirical analysis.

Introduces networking concepts, protocols, and architectures across the OSI and TCP/IP layers.
Course Outcome:
CO1: Understand network architectures, topologies, and the OSI/TCP-IP reference models.
CO2: Analyze data link layer protocols including error detection and correction techniques.
CO3: Understand network layer concepts including routing algorithms and IP addressing.
CO4: Analyze transport layer protocols and congestion control mechanisms.
CO5: Understand application layer protocols and their real-world implementations.
CO6: Explore network security fundamentals and emerging networking technologies.

Hands-on lab for network configuration, simulation, and protocol analysis.
Course Outcome:
CO1: Configure basic networking devices and IP addressing schemes.
CO2: Simulate network topologies using networking tools/simulators.
CO3: Analyze network traffic and protocols using packet capture tools.
CO4: Implement socket programming for client-server communication.
CO5: Troubleshoot common networking issues in a lab environment.

Covers mathematical foundations including set theory, logic, graph theory, and combinatorics for computer science.
Course Outcome:
CO1: Apply propositional and predicate logic to solve reasoning problems.
CO2: Understand set theory, relations, and functions.
CO3: Apply combinatorics and counting principles to solve problems.
CO4: Understand graph theory concepts including trees, graphs, and their applications.
CO5: Apply algebraic structures such as groups and lattices to computer science problems.

Introduces operating system concepts including process management, memory management, and file systems.
Course Outcome:
CO1: Understand the structure, functions, and types of operating systems.
CO2: Apply process scheduling algorithms and understand process synchronization.
CO3: Understand deadlock detection, prevention, and avoidance techniques.
CO4: Apply memory management techniques including paging and segmentation.
CO5: Understand file system organization and disk scheduling algorithms.
CO6: Explore concepts of virtualization and modern operating systems.

Hands-on lab for implementing OS concepts using shell scripting and system calls.
Course Outcome:
CO1: Implement basic Linux/Unix commands and shell scripts.
CO2: Implement process creation and synchronization using system calls.
CO3: Implement CPU scheduling algorithms programmatically.
CO4: Implement memory management techniques such as paging.
CO5: Implement solutions for classical process synchronization problems.

Covers computer system architecture, instruction sets, memory hierarchy, and processor design.
Course Outcome:
CO1: Understand basic computer organization and functional units.
CO2: Analyze instruction set architectures and addressing modes.
CO3: Understand arithmetic and logic unit design and computer arithmetic.
CO4: Understand memory hierarchy including cache and virtual memory.
CO5: Understand pipelining and instruction-level parallelism.
CO6: Explore I/O organization and multiprocessor architectures.

Website Security introduces common web application vulnerabilities, secure coding practices, authentication and session management, and techniques for protecting websites against common attacks.
Course Outcome:
CO1: Understand the fundamentals of web application architecture and associated security risks.
CO2: Identify common web vulnerabilities such as SQL injection, XSS, and CSRF.
CO3: Apply secure coding practices to prevent common web application attacks.
CO4: Implement secure authentication and session management mechanisms.
CO5: Understand the OWASP Top 10 and related mitigation strategies.
CO6: Apply security testing techniques to assess website vulnerabilities.

Website Security Lab provides hands-on practice in identifying and mitigating web application vulnerabilities using security testing tools in a controlled lab environment.
Course Outcome:
CO1: Set up a web application testing environment.
CO2: Identify common vulnerabilities using web security scanning tools.
CO3: Exploit sample vulnerabilities such as SQL injection and XSS in a controlled environment.
CO4: Implement fixes and secure coding practices to remediate identified vulnerabilities.
CO5: Prepare a website security assessment report.

Big Data Security & Privacy covers security and privacy challenges in big data systems, including data governance, access control, encryption, anonymization, and compliance in distributed data environments.
Course Outcome:
CO1: Understand security and privacy challenges unique to big data environments.
CO2: Apply access control and authentication mechanisms in distributed data systems.
CO3: Understand encryption and data masking techniques for protecting sensitive data.
CO4: Apply data anonymization and privacy-preserving techniques.
CO5: Understand data governance frameworks and regulatory compliance requirements.
CO6: Analyze security and privacy issues in real-world big data platforms.

Big Data Security & Privacy Lab provides hands-on practice in securing big data platforms, implementing access controls, and applying privacy-preserving techniques on large datasets.
Course Outcome:
CO1: Configure access control and authentication on a big data platform.
CO2: Implement encryption for data at rest and in transit in a big data environment.
CO3: Apply data anonymization and masking techniques on sample datasets.
CO4: Monitor and audit access to sensitive data in a distributed system.
CO5: Prepare a security and privacy compliance report for a big data use case.

Builds entrepreneurial thinking and practical business skills through case studies and projects.
Course Outcome:
CO1: Understand advanced concepts of entrepreneurship and business growth.
CO2: Analyze case studies of successful startups and ventures.
CO3: Develop strategies for scaling and sustaining a business.
CO4: Apply leadership and team-building concepts to entrepreneurial ventures.
CO5: Present a refined business plan incorporating market feedback.

5TH SEMESTER SUBJECTS

Covers software development life cycle, requirement analysis, design, and project management principles.
Course Outcome:
CO1: Understand software process models and the software development life cycle.
CO2: Apply requirement elicitation and analysis techniques.
CO3: Apply software design principles including modularity and design patterns.
CO4: Understand software testing techniques and quality assurance practices.
CO5: Apply project management and estimation techniques for software projects.
CO6: Understand software maintenance and configuration management.

Introduces formal languages, automata theory, and computability concepts.
Course Outcome:
CO1: Understand finite automata and regular languages.
CO2: Design context-free grammars and analyze pushdown automata.
CO3: Understand Turing machines and their role in computability.
CO4: Classify problems based on decidability and undecidability.
CO5: Understand complexity classes including P and NP.

Covers object-oriented programming concepts and application development using Java.
Course Outcome:
CO1: Understand the history, features, and fundamental elements of Java programming.
CO2: Apply object-oriented concepts including classes, objects, and inheritance.
CO3: Implement interfaces, packages, and exception handling in Java.
CO4: Understand multithreading and concurrent programming in Java.
CO5: Implement GUI applications using AWT/Swing.
CO6: Handle file I/O and stream operations in Java.

Hands-on lab for developing Java applications using object-oriented concepts.
Course Outcome:
CO1: Implement basic Java programs using core language constructs.
CO2: Implement classes, objects, and inheritance-based programs.
CO3: Implement exception handling and multithreading programs.
CO4: Develop GUI-based applications using Java.
CO5: Implement file handling operations in Java.

Covers information security principles, cryptography basics, and cyber law frameworks.
Course Outcome:
CO1: Understand fundamentals of information security and threat models.
CO2: Apply cryptographic techniques for data confidentiality and integrity.
CO3: Understand network and application security mechanisms.
CO4: Understand cyber laws, IT Act provisions, and compliance requirements.
CO5: Analyze case studies of cybercrimes and security breaches.

Introduces ethical hacking methodologies, tools, and penetration testing techniques.
Course Outcome:
CO1: Understand the fundamentals and phases of ethical hacking.
CO2: Perform reconnaissance and scanning using penetration testing tools.
CO3: Identify and exploit common vulnerabilities in systems and networks.
CO4: Understand web application security testing techniques.
CO5: Prepare penetration testing reports following ethical and legal guidelines.

Hands-on lab for practicing ethical hacking and penetration testing techniques.
Course Outcome:
CO1: Perform network scanning and vulnerability assessment using standard tools.
CO2: Exploit system and application vulnerabilities in a controlled lab environment.
CO3: Perform web application penetration testing.
CO4: Use password cracking and social engineering awareness techniques.
CO5: Document findings in a professional penetration testing report.

Identity & Access Management (IAM) introduces the principles and technologies for managing digital identities, authentication, authorization, and access governance across enterprise systems and cloud environments.
Course Outcome:
CO1: Understand fundamental concepts of identity, authentication, and authorization.
CO2: Apply access control models such as RBAC, ABAC, and least privilege principles.
CO3: Understand single sign-on (SSO), multi-factor authentication (MFA), and federated identity concepts.
CO4: Design IAM policies for on-premises and cloud-based systems.
CO5: Understand identity governance, provisioning, and lifecycle management.
CO6: Analyze IAM-related security risks and compliance requirements.

Identity & Access Management (IAM) Lab provides hands-on practice in configuring authentication, authorization, and identity governance solutions using industry-standard IAM tools and platforms.
Course Outcome:
CO1: Configure user identities, roles, and access policies on an IAM platform.
CO2: Implement multi-factor authentication and single sign-on for sample applications.
CO3: Set up role-based and attribute-based access control for enterprise resources.
CO4: Configure identity federation between on-premises and cloud systems.
CO5: Audit and monitor access logs to identify and address IAM-related risks.

Evaluation of industrial/summer training undertaken by students to assess practical exposure gained.
Course Outcome:
CO1: Demonstrate understanding of the industrial/organizational environment.
CO2: Apply theoretical knowledge to practical, real-world tasks undertaken during training.
CO3: Present and document the training experience through a report and viva-voce.
CO4: Reflect on skills gained and their relevance to career development.

Develops logical reasoning, quantitative aptitude, and analytical problem-solving skills.
Course Outcome:
CO1: Apply logical reasoning techniques to solve analytical problems.
CO2: Solve quantitative aptitude problems involving numbers and arithmetic.
CO3: Apply data interpretation techniques to analyze given data sets.
CO4: Develop problem-solving strategies for competitive examinations.

Advanced module on entrepreneurship focusing on innovation, funding, and venture execution.
Course Outcome:
CO1: Understand advanced funding options and investment readiness for startups.
CO2: Apply innovation management techniques to venture development.
CO3: Understand legal and regulatory aspects of starting a business.
CO4: Develop a comprehensive venture execution plan.
CO5: Present a pitch incorporating financial and operational planning.

6TH SEMESTER SUBJECTS

Covers cryptographic algorithms, network security protocols, and mechanisms to secure data communication.
Course Outcome:
CO1: Understand fundamentals of network security and cryptographic principles.
CO2: Apply symmetric and asymmetric encryption algorithms for data security.
CO3: Understand hash functions, digital signatures, and message authentication.
CO4: Apply key management and public key infrastructure concepts.
CO5: Understand network security protocols such as SSL/TLS, IPSec, and firewalls.
CO6: Analyze security threats and countermeasures in networked systems.

Hands-on lab for implementing cryptographic algorithms and network security techniques.
Course Outcome:
CO1: Implement classical and modern encryption algorithms.
CO2: Implement hashing and digital signature techniques.
CO3: Configure firewalls and basic network security tools.
CO4: Analyze network traffic for security vulnerabilities.
CO5: Implement secure communication using SSL/TLS concepts.

Covers advanced data structures and their applications in efficient algorithm design.
Course Outcome:
CO1: Understand advanced tree structures such as AVL, B-trees, and Red-Black trees.
CO2: Implement advanced graph algorithms and their applications.
CO3: Understand heap structures and priority queue implementations.
CO4: Apply hashing techniques and collision resolution strategies.
CO5: Understand advanced string matching and pattern searching algorithms.
CO6: Analyze the performance trade-offs of advanced data structures.

Lab-based implementation of advanced data structures and their applications.
Course Outcome:
CO1: Implement balanced tree structures such as AVL and B-trees.
CO2: Implement heap-based priority queues.
CO3: Implement advanced graph algorithms programmatically.
CO4: Implement hashing techniques with collision handling.
CO5: Implement string matching algorithms.

Introduces the phases of compiler construction including lexical analysis, parsing, and code generation.
Course Outcome:
CO1: Understand the phases and structure of a compiler.
CO2: Design lexical analyzers using regular expressions and finite automata.
CO3: Design parsers using context-free grammars and parsing techniques.
CO4: Understand syntax-directed translation and intermediate code generation.
CO5: Understand code optimization and target code generation techniques.
CO6: Explore error detection and recovery mechanisms in compilers.

Introduces core AI concepts, search techniques, knowledge representation, and intelligent agent design.
Course Outcome:
CO1: Understand the fundamentals of AI and intelligent agents.
CO2: Apply uninformed and informed search techniques to solve problems.
CO3: Represent knowledge using logic-based and semantic approaches.
CO4: Understand the basics of machine learning and its role in AI systems.
CO5: Apply AI techniques to design simple intelligent systems.
CO6: Understand ethical and societal implications of AI.

Covers data warehouse architecture, OLAP concepts, and data mining techniques for knowledge discovery.
Course Outcome:
CO1: Understand data warehouse architecture and multidimensional data models.
CO2: Apply OLAP operations for data analysis.
CO3: Understand data preprocessing techniques for data mining.
CO4: Apply classification and clustering algorithms for pattern discovery.
CO5: Understand association rule mining techniques.
CO6: Explore applications of data mining in real-world domains.

Digital Forensics and Footprinting introduces the principles of digital evidence collection, forensic investigation methodologies, and reconnaissance techniques used to trace digital footprints across systems and networks.
Course Outcome:
CO1: Understand the fundamentals and legal aspects of digital forensics.
CO2: Apply evidence acquisition and preservation techniques for digital investigations.
CO3: Perform footprinting and reconnaissance to gather information about target systems.
CO4: Analyze file systems, memory, and network artifacts for forensic evidence.
CO5: Use forensic tools to recover and examine deleted or hidden data.
CO6: Prepare a digital forensic investigation report in line with legal and procedural standards.

Digital Forensics and Footprinting Lab provides hands-on practice with forensic imaging, evidence analysis, and reconnaissance tools to investigate simulated security incidents.
Course Outcome:
CO1: Acquire forensic images of storage media while preserving evidence integrity.
CO2: Use footprinting and OSINT tools to gather information about a target.
CO3: Analyze file systems and recover deleted files using forensic tools.
CO4: Examine memory dumps and network logs for indicators of compromise.
CO5: Document forensic findings in a structured investigation report.

Security Operations & Threat Intelligence covers the functioning of a Security Operations Center (SOC), security monitoring, log analysis, and the use of threat intelligence to identify and respond to emerging cyber threats.
Course Outcome:
CO1: Understand the roles, functions, and workflows of a Security Operations Center.
CO2: Apply security monitoring and log analysis techniques using SIEM tools.
CO3: Understand threat intelligence lifecycle and sources of threat data.
CO4: Correlate security events to detect and prioritize potential threats.
CO5: Apply threat intelligence to improve incident detection and response.
CO6: Understand metrics and reporting practices used in security operations.

Security Operations & Threat Intelligence Lab provides hands-on practice with SIEM tools, log analysis, and threat intelligence platforms to detect and investigate simulated security threats.
Course Outcome:
CO1: Configure and use a SIEM tool for security event monitoring.
CO2: Analyze logs to identify suspicious activity and potential threats.
CO3: Use threat intelligence feeds to enrich and prioritize security alerts.
CO4: Investigate simulated security incidents using SOC tools and workflows.
CO5: Prepare a security operations report summarizing detection and response activities.

Builds advanced logical reasoning, quantitative aptitude, and analytical problem-solving skills.
Course Outcome:
CO1: Apply advanced logical reasoning techniques to complex problems.
CO2: Solve advanced quantitative aptitude problems.
CO3: Apply data sufficiency and interpretation techniques.
CO4: Develop strategies for competitive and placement examinations.

Provides students hands-on experience in identifying, designing, and initiating a substantial project applying learned concepts.
Course Outcome:
CO1: Identify a real-world problem and formulate project objectives.
CO2: Conduct literature review and requirement analysis for the project.
CO3: Design the system architecture and methodology for the project.
CO4: Develop an initial working prototype of the proposed solution.
CO5: Present and document the project progress through reports and reviews.

Focuses on developing communication, interpersonal, and professional workplace skills.
Course Outcome:
CO1: Develop effective verbal and written communication skills.
CO2: Apply interpersonal and teamwork skills in professional settings.
CO3: Understand workplace etiquette and professional ethics.
CO4: Develop resume writing and interview preparation skills.

7TH SEMESTER SUBJECTS

Introduces image processing fundamentals and computer vision techniques for visual data analysis.
Course Outcome:
CO1: Understand fundamentals of digital image processing and representation.
CO2: Apply image filtering, enhancement, and edge detection techniques.
CO3: Understand feature extraction and object detection techniques.
CO4: Apply image segmentation and classification techniques.
CO5: Understand deep learning approaches for computer vision tasks.
CO6: Explore real-world applications of computer vision.

Covers Internet of Things architecture, protocols, and applications for connected devices.
Course Outcome:
CO1: Understand IoT architecture, components, and protocols.
CO2: Apply sensor and actuator interfacing concepts.
CO3: Understand communication protocols used in IoT systems.
CO4: Apply cloud integration concepts for IoT data management.
CO5: Understand IoT security challenges and solutions.
CO6: Explore real-world IoT application domains.

Hands-on lab for building IoT-based projects using microcontrollers, sensors, and connectivity modules.
Course Outcome:
CO1: Interface sensors and actuators with microcontroller boards.
CO2: Implement basic IoT communication protocols.
CO3: Develop IoT applications with cloud data integration.
CO4: Implement basic IoT security measures.
CO5: Build and demonstrate a working IoT-based mini-project.

Introduces principles of designing scalable, reliable, and maintainable software systems.
Course Outcome:
CO1: Understand fundamentals of system design and design trade-offs.
CO2: Apply scalability concepts including load balancing and caching.
CO3: Design database and storage solutions for large-scale systems.
CO4: Understand microservices architecture and distributed system design.
CO5: Design fault-tolerant and highly available systems.
CO6: Apply system design principles to real-world case studies.

Introduces blockchain concepts, architecture, and applications in decentralized systems.
Course Outcome:
CO1: Understand fundamentals of blockchain technology and distributed ledgers.
CO2: Understand consensus mechanisms used in blockchain networks.
CO3: Apply smart contract concepts for decentralized applications.
CO4: Understand cryptocurrency and blockchain-based financial systems.
CO5: Explore blockchain applications beyond cryptocurrency.

Hands-on lab for developing and deploying blockchain-based applications and smart contracts.
Course Outcome:
CO1: Set up a basic blockchain network environment.
CO2: Develop and deploy smart contracts.
CO3: Build a simple decentralized application (DApp).
CO4: Implement basic cryptocurrency transaction simulations.
CO5: Evaluate blockchain applications for real-world use cases.

Introduces research methods, ethics, and technical writing skills for academic and applied research.
Course Outcome:
CO1: Understand fundamentals of research design and methodology.
CO2: Apply literature review and research problem formulation techniques.
CO3: Understand data collection and analysis methods for research.
CO4: Apply research ethics and plagiarism-avoidance practices.
CO5: Develop skills for writing and presenting research papers.

Incident Response and Cyber Crisis Management covers advanced incident handling, crisis communication, business continuity, and coordinated response strategies for managing large-scale cyber security incidents.
Course Outcome:
CO1: Understand the incident response and crisis management lifecycle for large-scale cyber incidents.
CO2: Apply frameworks for coordinating cross-functional incident response teams.
CO3: Develop business continuity and disaster recovery plans for cyber crisis scenarios.
CO4: Understand crisis communication strategies for internal and external stakeholders.
CO5: Apply post-incident review and lessons-learned practices to improve organizational resilience.
CO6: Analyze case studies of major cyber crises and their management outcomes.

Incident Response and Cyber Crisis Management Lab provides hands-on practice in simulating and managing large-scale cyber security incidents through tabletop exercises and response coordination tools.
Course Outcome:
CO1: Participate in simulated tabletop exercises for cyber crisis scenarios.
CO2: Use incident response coordination and case management tools.
CO3: Develop a business continuity plan for a simulated organizational scenario.
CO4: Draft crisis communication materials for a simulated cyber incident.
CO5: Prepare a post-incident review report with recommendations for improvement.

Blockchain Solutions Development covers the design and implementation of decentralized applications, smart contracts, and blockchain-based solutions for real-world business use cases.
Course Outcome:
CO1: Understand blockchain platforms and their suitability for different application domains.
CO2: Design and develop smart contracts for decentralized applications.
CO3: Build front-end interfaces that interact with blockchain networks.
CO4: Apply security best practices in smart contract and blockchain application development.
CO5: Deploy and test blockchain-based solutions on a test network.
CO6: Evaluate blockchain solutions for real-world business use cases.

Blockchain Solutions Development Lab provides hands-on practice in building, testing, and deploying smart contracts and decentralized applications using industry-standard blockchain development tools.
Course Outcome:
CO1: Set up a blockchain development environment and toolchain.
CO2: Write and deploy smart contracts on a test blockchain network.
CO3: Develop a front-end application that interacts with deployed smart contracts.
CO4: Test smart contracts for functional correctness and common vulnerabilities.
CO5: Build and demonstrate a working decentralized application (DApp).

Continuation of the capstone project focusing on implementation, testing, and final deployment.
Course Outcome:
CO1: Implement the complete proposed system based on the earlier design.
CO2: Conduct testing and validation of the developed system.
CO3: Refine the solution based on evaluation and feedback.
CO4: Document the complete project methodology, results, and outcomes.
CO5: Present and defend the final project through a viva-voce/demonstration.

Focuses on advanced professional skills including leadership, career readiness, and workplace communication.
Course Outcome:
CO1: Develop advanced presentation and public speaking skills.
CO2: Apply leadership and team management concepts in professional settings.
CO3: Prepare for competitive job interviews and group discussions.
CO4: Understand corporate work culture and professional networking practices.

8TH SEMESTER SUBJECTS

Provides students with industry exposure through a structured training/internship period to apply academic knowledge in a professional environment.
Course Outcome:
CO1: Demonstrate understanding of industry practices, tools, and work culture.
CO2: Apply academic knowledge and skills to real-world industrial tasks.
CO3: Develop professional and technical skills relevant to the chosen domain.
CO4: Present the outcomes of industrial training through a report and viva-voce.

fees

Details

Amount

Programme Fees (per Semester)

₹85000

Examination Fees

₹3000

International Fees (per Year)

$4500

Fee Slab

Slab >=60% - 74.99% >=75% - 89.99% >=90% & Above
Fee ₹80000 ₹75000 ₹70000

Students can avail these slots depending on the marks they have scored. Each slot reflects a different academic range, helping students understand where they stand and what benefits they qualify for.

Programme Outcomes

To make students function in their profession with social awareness and responsibility. To make students engineering professionals, innovators or entrepreneurs engaged in technology development, technology deployment, or engineering system implementation in industry. To make students interact with their peers in other disciplines in industry and society and contribute to the economic growth of the country To make students provide students with contemporary knowledge in Cybersecurity. To make students understand how cybersecurity can be used as an effective tool in providing assurance concerning privacy and integrity of information. To make students provide skills to design security protocols for recognize security problems

Programme Specific Outcomes

A graduate of the Computer Science and Engineering Program will demonstrate: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences. Understand the principles and practices of cryptographic techniques. Understand a variety of generic security threats and vulnerabilities, and identify & analyse particular security problems for given application. Appreciate the application of security techniques and technologies in solving real-life security problems in practical systems. 

Salient Features

Apply appropriate security techniques to solve security problem Design security protocols and methods to solve the specific security problems. Familiar with current research issues and directions of security.

Infrastructure

Laboratory

Laboratory

What better way to learn working of anything than to get exposed to it first hand!. The specialized laboratories are equipped to conduct advanced practical and research work.