Computer Science and Engineering (Cyber Security)

Year of establishment: 2024
B.Tech. in Computer Science and Engineering (Cyber Security) (4 years)

The Department of Computer Science and Engineering (Cyber Security) has been established in the year 2024. B.Tech in CSE (Cybersecurity) is designed to address the industry’s increasing demand for skilled security professionals in the public and private sector, both in the Data Security and in the Network/Cloud Security domains.
The program covers core computer science subjects as well as cybersecurity specific courses. The emphasis of the program is to nurture students with the knowledge and skills required to secure computers, detect and analyse attacks and threats, respond to attacks, develop security policies, procedures, and standards.
The four-year undergraduate curriculum includes a sound preparation in Basic Sciences, Mathematical Foundations, Cybersecurity, Cryptography and Network Security, Secure Programming and Ethical hacking.
The designed imparts 21st century skills having the following component: Liberal education aspects for all round development, courses that trigger new age skills, project based learning, special topics (hands-on sessions on multiple topics with mentoring from expert), option for MOOC, UG Research Project/Product Development/Internships. The curriculum focuses on Liberal Art Courses, Foundation Courses, Professional Courses, and Electives that help them build expertise in some specialized areas. Curriculum developed, also emphasis on design oriented thinking, Communication, Collaboration and Creativity right from 1st year.
Stanford University, University of Michigan, Harvard University, Columbia University, University of Washington have standalone program in MS-PhD for data science.
After working as a Cybersecurity Architect for 15 years, most Cybersecurity professionals move up to Senior-level Cybersecurity roles as Senior Manager of IT & Security Compliance, Director of IT Security, Senior Manager, and Senior Director, A Chief Information Security Officer (CISO).

OVERVIEW

PROGRAM EDUCATIONAL OBJECTIVES FOR B.TECH CSE (Cyber Security)

A graduate of Computer Science and Engineering (Cyber Security) will be able to:

PEO1: Be recognized as effective professionals for their applied skills, problem solving capabilities and professional skills in the field of cyber security.
PEO2: Develop themselves as effective communicators that help them for employment in the areas of cyber security and related fields.
PEO3: Incorporate ethical, legal and social implications as outcomes of their profession. PEO4: Actively engage themselves in activities which allow for the continuous development of their computing and cyber security skills.

PROGRAM SPECIFIC OUTCOMES (PSOs) A graduate of Computer Science and Engineering (Cyber Security) acquires ability to:

PSO1: Develop secure software with vulnerability assessment, and security requirements, designed with the least privileges for the protection of digital applications.
PSO2: Evaluate the function of cyber security by identifying the tools and systems to minimize the risk to an organization’s cyberspace.
PSO3: Apply machine learning models, methods, and techniques for data analysis, data handling, and data visualization for effective decision-making.

LABORATORIES

Data Structure and Algorithms
Analog and Digital Electronics
Computer Organization
IT Workshop (Python/Matlab/R)
Data Communication and Networks Lab
Design and Analysis of Algorithm Lab
System Security Lab
Operating System Lab
Object Oriented Programming Lab
Network Security Lab
Network Security Lab
Database Management System lab
Project Lab

Vision

Ignite and nurture young learners to provide a sustainable, humane, and research-centric educational platform in the domain of cybersecurity for building a robust, resilient, and attack-free digital universe

Mission

M1: Provide committed and competent faculty and educational infrastructure to impart the theoretical and practical foundation of cyber security in the emanating youth.
M2: Establish MoUs and Centre of Excellences (CoEs) with Information Technology Sector to provide industry-ready cybersecurity graduates with research instinct imbibed for the sustainable development of young learners.
M3: Build collaborative and teamwork-centric project-oriented learning environment, to address global challenges whilst preserving human and ethical values.
M4: Encourage young minds to educate society to restore nationwide human safety and security in digital world.

HOD Details

Contact No:

Contact Email:

Message from HOD

List of Faculty

Sudipta Samanta	Assistant Professor
Amit Mondal	Assistant Professor
DR. SOHAM BANDYOPADHYAY	Assistant Professor
Dr, Subir Panja	Associate Professor

List of Technical Staff

Achievements

Laboratories

Area of Research

Faculty Activity

Publications

Journal

Date	Title	Authors	Journal	DOI	Link
01-02-2026	Fuzzy-logic-based IoMT framework for COVID19 patient monitoring	Subir Panja, Arup Kumar Chattopadhyay, Amitava Nag, Jyoti Prakash Singh	Computers & Industrial Engineering	DOI	View
08-12-2025	Decoding brain tumors: an attention-guided hybrid learning framework for multi-class classification of MRI images	Soham Bandyopadhyay, Arnab Banerjee, Bhumik Roy, Ankur Lodh	International Journal of Information Technology	DOI	View
01-04-2025	AI-enabled computational intelligence approach to neurodevelopmental disorders detection using rs-fMRI data	S Bandyopadhyay, M Sarma, D Samanta	Computers and Electrical Engineering	DOI	View
05-03-2025	Novel framework of significant risk factor identification and cardiovascular disease prediction	Soham Bandyopadhyay a , Ananya Samanta b , Monalisa Sarma c , Debasis Samanta d	Expert Systems with Applications	DOI	View
16-04-2024	Tri‑fuzzy interval arithmetic with deep learning and hybrid statistical approach for analysis and prognosis of cardiovascular disease	Soham Bandyopadhyay, Monalisa Sarma, Debasis Samanta	International Journal of Information Technology	DOI	View
14-04-2024	SOHAM BANDYOPADHYAY Statistical Analysis of Renal Risk Factors and Prediction of Chronic Kidney Disease	Soham Bandyopadhyay, Monalisa Sarma, Debasis Samanta	SN Computer Science	DOI	View
24-02-2024	Decoding autism: Uncovering patterns in brain connectivity through sparsity analysis with rs-fmri data	S Bandyopadhyay, S Peddi, M Sarma, D Samanta	Journal of neuroscience methods	DOI	View
08-06-2018	Improving the Performance of Fuzzy Minimum Spanning Tree based Routing Process through PNode Fuzzy Multicasting Approach in MANET	Soham Bandyopadhyay, Sunil Karforma	I. J. Computer Network and Information Security	DOI	View
08-03-2016	Derivation and Comparative Study on Centroid Ranking Value of TrIFN and Apply on Fuzzy Geometric Programming	Soham Bandyopadhyay	I.J. Information Technology and Computer Science	DOI	View

Conference

Date	Title	Authors	Conference	DOI	Link
29-07-2025	Predicting ADHD: Combining Data-Driven ROI Extraction and Composite Graph Spectral Analysis	Soham Bandyopadhyay, M Unnikrishnan, Monalisa Sarma, Debasis Samanta	International Conference on Computer Vision and Image Processing	DOI	View
21-04-2025	Autism Spectrum Disorder Prediction Using Sparse Connectivity Patterns in RS-fMRI Data	Soham Bandyopadhyay, Santhoshkumar Peddi, Monalisa Sarma, Debasis Samanta	2024 IEEE 21st India Council International Conference (INDICON)	DOI	View
04-11-2024	Prediction of neurodevelopmental disorder by combining data-driven ROI extraction and frequency specific brain functional connectivity approach	Soham Bandyopadhyay, Monalisa Sarma, Debasis Samanta	2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)	DOI	View
19-02-2024	Cardiac Risk Factors Identification with Hybrid Statistical Approach and Prediction of Cardiovascular Disease with Machine Learning	Soham Bandyopadhyay; Monalisa Sarma; Debasis Samanta	2023 OITS International Conference on Information Technology (OCIT)	DOI	View
11-12-2023	Statistical analyses for key risk factor identification and prediction of chronic kidney disease	Ananya Samanta, Soham Bandyopadhyay, Debasis Samanta	2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)	DOI	View

Thesis Supervised

Patent

Name	Year	Description
Sudipta Samanta	2017	Extract, transform and load (ETL) system and method Patent number: 9633095 Abstract: An ETL system for extracting transactional data from a plurality of source machines is provided. The ETL system includes a data query module configured to provide an interface to enable a data analyst to define an input query to extract transactional data, which is present on a plurality of source machines. The source machines form a multi-tenant system and each source machine is identified by a unique tenant identifier. The system also includes a query parsing module coupled to the data query module and configured to deconstruct the input query to create a tree structure. The tree structure comprises a plurality of distinct queries. The system further includes a data extraction module coupled to the query parsing module and configured to extract transactional data based on the distinct queries and copy the transactional data to a destination system wherein the transactional data comprises a plurality of data types.

Highlights

Department

Computer Science and Engineering (Cyber Security)

Year of establishment: 2024
B.Tech. in Computer Science and Engineering (Cyber Security) (4 years)