HPRCA Hamirpur Scientific Assistant (Digital Forensics) Exam Syllabus

 1. Syllabus as per essential qualification
A. FORENSIC SCIENCE & DIGITAL FORENSICS
i. GENERAL FORENSIC SCIENCE, LEGAL FRAMEWORK AND QUALITY ASSURANCE: Definition, history and development of forensic science, principles and scope of forensic science, concept and classification of crime, criminal profiling, constitution and hierarchy of courts, crime scene management including protection, documentation, search, collection and preservation of evidence, types and classification of evidence (physical, biological and digital), chain of custody and integrity of evidence, standard operating procedures for collection of physical and digital evidence from scene of crime, report writing, expert testimony and courtroom presentation, Frye and Daubert standards for admissibility of scientific evidence, provisions of Bharatiya Sakshya Adhiniyam 2023, Bharatiya Nagarik Suraksha Sanhita 2023, Bharatiya Nyaya Sanhita 2023, Information Technology Act 2000 and amendments, legal procedures for search and seizure, admissibility of electronic evidence and ethical issues in forensic science, scope of ISO/IEC 17025:2017, general understanding of requirements of ISO/IEC 17025:2017.
ii. DIGITAL FORENSICS FUNDAMENTALS AND COMPUTER FORENSICS: Scope and importance of digital forensics, characteristics and sources of digital evidence, forensic process including identification, acquisition, preservation, examination, analysis and reporting, storage media structure and disk architecture, file systems including FAT, NTFS and EXT, data acquisition techniques (live and dead), forensic imaging formats (RAW, DD, AFF, E01), write blockers, hashing techniques for integrity verification, file signature analysis, file carving, registry and log analysis, timeline analysis, metadata analysis, recovery of deleted and hidden data, artifacts from slack and unallocated space, anti-forensics techniques and countermeasures.
iii. MEMORY, NETWORK AND WEB FORENSICS: Volatile data acquisition and RAM analysis, examination of processes, DLLs and network connections, packet capture and traffic analysis, TCP/IP fundamentals, network logs and intrusion detection systems, email forensics including header analysis, web forensics including browser artifacts, cookies and internet history.

 iv. MOBILE FORENSICS: Mobile device architecture, mobile operating systems including Android and iOS, SIM/USIM and memory card forensics, mobile data acquisition methods including manual, logical, file system and physical extraction, analysis of call logs, messages, emails, application data and location artifacts, mobile malware and overview of mobile forensic tools.
v. MULTIMEDIA AND VIDEO FORENSICS: Image and video formats, metadata analysis including EXIF, image enhancement techniques, error level analysis, clone detection, tampering detection, steganography and steganalysis basics, deepfake detection, audio forensics including speech analysis, DVR and NVR systems, CCTV camera types, video acquisition, enhancement and authentication.
vi. CYBER CRIME AND INVESTIGATION TECHNIQUES: Types of cyber crimes including hacking, phishing, spoofing, identity theft, cyber stalking and financial fraud, social engineering, dark web and anonymous browsing, digital investigation techniques including IP tracing, call detail record analysis, cell site analysis, tower dump, IPDR analysis, email tracing, domain analysis, open source intelligence and social media forensics.
vii. OPERATING SYSTEMS AND FILE SYSTEM ARTIFACTS: Fundamentals of operating systems including Windows and Linux, file system structures, user accounts and permissions, forensic artifacts including registry, event logs, prefetch files, browser artifacts and system logs.
viii. FORENSIC TOOLS AND TECHNOLOGIES: Working principles and applications of forensic tools including EnCase, FTK, Autopsy, Cellebrite, XRY, Oxygen, Wireshark and Volatility, use of write blockers, imaging and cloning devices, validation of tools and results.
ix. EMERGING TECHNOLOGIES IN DIGITAL FORENSICS: Cloud forensics, IoT forensics, drone forensics, crypto currency and block chain analysis, artificial intelligence and machine learning applications, big data analytics and deepfake technologies.
x. ALLIED FORENSIC DISCIPLINES RELATED TO DIGITAL EVIDENCE: Forensic physics involving examination and analysis of digital devices and storage media including assessment of physical damage, electrical failures, fire and explosion effects on electronic components, recovery possibilities from damaged devices, forensic voice and speaker identification involving audio signal analysis, spectrographic examination, speaker comparison, authentication of recorded conversations, detection of tampering and enhancement of audio recordings; forensic psychology focusing on cyber behavior analysis, offender profiling in cyber crimes, understanding motives,  patterns of online behavior, financial and cyber fraud forensics including analysis of digital financial transactions, online banking frauds, cryptocurrency transactions, integration of digital evidence with financial investigation.

B. INFORMATION SECUITY
i. CRYPTOGRAPHY AND INFORMATION SECURITY: Cryptographic system, classification of cryptographic systems, substitution-permutation network, Feistel structure, block ciphers: DES, Double DES, AES, modes of operation (ECB, CBC, CFB, OFB, CTR), stream ciphers: LFSR, RC4, cryptanalysis techniques (linear and differential cryptanalysis, brute force attacks), public key cryptography, RSA, discrete logarithm problem, Diffie-Hellman, DSA, elliptic curve cryptography (ECC), key management, public key infrastructure (PKI), digital certificates.
ii. DATA INTEGRITY, HASH FUNCTIONS: MD5, SHA family (SHA-1, SHA-2, SHA-3), collision resistance, message authentication codes (MAC), HMAC, authenticated encryption.
iii. SECURITY PROTOCOLS AND APPLICATIONS: Email security (PGP, S/MIME), SSL/TLS, HTTPS, secure shell (SSH), web security mechanisms, session management, access control models (DAC, MAC, RBAC), authentication mechanisms: token-based, biometric, multi-factor authentication, remote authentication protocols.
iv. CYBER THREATS AND DEFENSE: Malware types (virus, worm, trojan, ransomware, spyware), firewalls, intrusion detection and prevention systems (IDS/IPS), honeypots and honeynets, denial of service (DoS) and distributed DoS (DDoS), zero-day attacks, vulnerability assessment and penetration testing basics.
v. CYBER CRIME AND LEGAL FRAMEWORK Cyber space, types of cyber crimes, hacking, unauthorized access, spoofing, phishing, cyber terrorism, cyber stalking, social engineering attacks. Cyber attacks: DoS, DDoS, ransomware, financial frauds, identity theft, malware attacks.
C. COMPUER APPLICATIONS/COMPUER SCIENCE/ INFORMATION TECHNOLOGY
i. MATHEMATICS FOR COMPUTING: Discrete mathematics including sets, relations, functions, equivalence relations, partial ordering, propositional and predicate logic, truth tables, normal forms, combinatorics (permutations, combinations, pigeonhole principle), recurrence relations and their solutions,  graph theory (graphs, trees, connectivity, shortest paths), linear algebra (matrices, determinants, rank, eigenvalues and eigenvectors), probability theory (random variables, distributions, expectation, variance), and basic calculus (limits, continuity, differentiation, integration and their applications).
ii. PROGRAMMING AND DATA STRUCTURES: Fundamentals of programming using C/C++/Java including variables, data types, operators, control structures, functions, pointers and memory management, recursion, arrays and strings, structures and unions, object-oriented programming concepts such as classes, objects, inheritance, polymorphism, abstraction and encapsulation, exception handling; implementation and applications of data structures including stacks, queues, linked lists, trees, binary search trees, AVL trees, heaps, hashing techniques, graphs and graph traversal algorithms (BFS, DFS), algorithm design paradigms such as divide and conquer, greedy method, dynamic programming, backtracking, and analysis of algorithms including time and space complexity with asymptotic notations (Big-O, Theta, Omega).
iii. DATABASE MANAGEMENT SYSTEMS: Database system concepts, data models (ER model, relational model), schema design, integrity constraints, relational algebra and relational calculus, normalization techniques (1NF, 2NF, 3NF, BCNF), structured query language (SQL) including DDL, DML, DCL and TCL commands, transaction management, ACID properties, concurrency control mechanisms (locking, time stamping), deadlock handling, indexing techniques (B-tree, hashing), file organization, query processing and optimization, distributed databases, NoSQL databases and big data storage basics.
iv. OPERATING SYSTEMS: Basic concepts of operating systems, process management (process states, scheduling algorithms such as FCFS, SJF, Round Robin, priority scheduling), threads and multithreading, inter-process communication, synchronization mechanisms (semaphores, monitors, mutex), deadlock conditions, prevention and avoidance, memory management techniques (paging, segmentation, virtual memory, page replacement algorithms), file systems and directory structures, I/O management, disk scheduling algorithms, basics of Linux/Unix operating systems and shell commands.
v. COMPUTER NETWORKS: Fundamentals of data communication, network topologies, transmission media, OSI and TCP/IP reference models, detailed study of layers including physical layer (signals, encoding), data link layer (error detection and correction, flow control, protocols), network layer (IP addressing, sub netting, routing algorithms), transport layer (TCP/UDP,  congestion control), application layer protocols (HTTP, HTTPS, FTP, SMTP, DNS), network devices (routers, switches), wireless and mobile networks, network security basics including firewalls, VPNs and intrusion detection.
vi. COMPUTER ORGANIZATION AND ARCHITECTURE: Number systems and conversions, digital logic fundamentals, combinational and sequential circuits, CPU organization, instruction formats, addressing modes, control unit design, pipelining concepts, instruction-level parallelism, memory hierarchy including cache memory, RAM, ROM, virtual memory, input-output organization, interrupt handling, performance evaluation of computer systems.
vii. THEORY OF COMPUTATION: Formal languages and automata theory including finite automata (DFA, NFA), regular expressions, context-free grammars, pushdown automata, Turing machines, decidability and undecidability problems, computability theory, introduction to computational complexity including classes P, NP, NP-complete and NP-hard problems.
viii. SOFTWARE ENGINEERING: Software development life cycle models (waterfall, spiral, agile), requirement engineering, system design principles, UML diagrams, coding standards, software testing techniques (unit testing, integration testing, system testing, regression testing), software quality assurance, software metrics, project management, configuration management, version control systems (Git), DevOps practices.
ix. WEB TECHNOLOGIES: Fundamentals of web development including HTML, CSS, JavaScript, DOM manipulation, client-server architecture, HTTP protocol, cookies and session management, web services (SOAP, REST APIs), basics of frontend and backend frameworks, web security basics including cross-site scripting (XSS), SQL injection and authentication mechanisms.
x. CYBER SECURITY FUNDAMENTALS: Basic principles of information security including confidentiality, integrity and availability, introduction to cryptography (symmetric and asymmetric encryption), hashing, digital signatures, authentication and authorization techniques, common cyber threats such as malware, phishing and social engineering, network security tools such as firewalls and intrusion detection systems, basics of ethical hacking and security policies.
xi. DIGITAL LOGIC AND MICROPROCESSORS: Boolean algebra, logic gates, minimization techniques (K-map), combinational circuits (adders, multiplexers), sequential circuits (flip-flops, counters, registers), microprocessor architecture, instruction cycle, addressing modes, assembly language basics, interfacing concepts. 
xii. ARTIFICIAL INTELLIGENCE AND DATA SCIENCE BASICS: Introduction to artificial intelligence, problem-solving techniques, search algorithms (BFS, DFS, A*), knowledge representation, basics of machine learning including supervised and unsupervised learning, classification and clustering methods, data preprocessing, feature selection, introduction to neural networks, basics of data analytics and statistical methods. xiii. CLOUD COMPUTING AND EMERGING TECHNOLOGIES: Cloud computing concepts, service models (IaaS, PaaS, SaaS), deployment models (public, private, hybrid), virtualization techniques, distributed computing, big data fundamentals, Hadoop ecosystem basics, Internet of Things (IoT), block chain fundamentals, basics of cyber security in cloud environments.

D. ELECTRONICS/ELECTRONICS COMMUNICATIONS i. ENGINEERING MATHEMATICS: Linear algebra including matrices, determinants, eigenvalues, eigenvectors, rank, system of linear equations, vector spaces; calculus including limits, continuity, differentiation, partial differentiation, multiple integrals, vector calculus; differential equations including first and higher order, Laplace transforms and applications; Fourier series and Fourier transforms; probability and statistics including random variables, distributions, mean, variance, correlation and regression.
ii. NETWORK THEORY: Basic circuit elements (resistor, inductor, capacitor), Kirchhoff’s laws (KCL, KVL), network theorems (Thevenin, Norton, Superposition, Maximum Power Transfer), DC and AC circuit analysis, transient response of RL, RC and RLC circuits, steady state analysis, resonance, two-port networks, network functions, Laplace transform applied to circuits.
iii. ELECTRONIC DEVICES: Semiconductor physics, intrinsic and extrinsic semiconductors, PN junction diode characteristics and applications, Zener diode, BJT and its configurations, biasing techniques, MOSFET characteristics, small signal models, rectifiers, amplifiers, power electronic devices, optoelectronic devices such as LED, photodiode and solar cell.
iv. ANALOG CIRCUITS: Amplifiers including single-stage and multistage amplifiers, frequency response, bandwidth, feedback amplifiers, oscillators (RC phase shift, Wien bridge, LC, crystal), operational amplifiers (op-amp) and applications such as integrator, differentiator, comparators, active filters, waveform generators.
v. DIGITAL ELECTRONICS: Boolean algebra, logic gates, minimization techniques (K-map, Quine-McCluskey), combinational circuits such as adders,subtractors, multiplexers, demultiplexers, encoders, decoders; sequential circuits including flip-flops, counters, shift registers, finite state machines, memory devices.
vi. SIGNALS AND SYSTEMS: Continuous-time and discrete-time signals, system properties (linearity, time invariance, causality), convolution, Fourier series and Fourier transform, Laplace transform, Z-transform, sampling theorem, frequency response of systems.
vii. CONTROL SYSTEMS: Open-loop and closed-loop control systems, transfer functions, block diagram reduction, signal flow graphs, time domain analysis, stability analysis using Routh-Hurwitz criterion, frequency domain analysis using Bode plot and Nyquist plot, root locus techniques, controllers such as PID.
viii. COMMUNICATION SYSTEMS: Analog communication including amplitude modulation (AM), frequency modulation (FM), phase modulation (PM), demodulation techniques, noise analysis; digital communication including PCM, ASK, FSK, PSK, QAM, information theory basics, channel capacity, error detection and correction techniques, multiplexing methods.
ix. ELECTROMAGNETIC THEORY: Vector calculus, electrostatics, magnetostatics, Maxwell’s equations, electromagnetic wave propagation, transmission lines, waveguides, antennas fundamentals.
x. MICROPROCESSORS AND MICROCONTROLLERS: Architecture of microprocessors (8085/8086), instruction sets, addressing modes, assembly language programming, interfacing techniques, microcontrollers (8051), embedded system basics.
xi. VLSI DESIGN: Basics of MOS technology, CMOS circuits, fabrication process, layout design rules, scaling techniques, VLSI design flow, introduction to hardware description languages (Verilog/VHDL).
xii. MEASUREMENT AND INSTRUMENTATION: Measurement systems, types of errors, accuracy and precision, transducers and sensors, bridges, digital measuring instruments, CRO (oscilloscope), signal generators.
xiii. COMPUTER ORGANIZATION AND EMBEDDED SYSTEMS: Basic computer architecture, memory hierarchy, input-output systems, embedded systems design, real-time systems concepts.
xiv. ENGINEERING PHYSICS (ELECTRONICS-ORIENTED): Semiconductor materials, optical fibers, lasers, wave propagation fundamentals. 

2. General Awareness
(a) General knowledge: General Knowledge including General knowledge of HP
(b) Current Affairs .
(c) Everyday Science .
(d) Logical Reasoning .
(e) Social Science (10th standard).
(f) General English (10th standard)
(g) General Hindi (10th standard)

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