Index
- Absorbed data, 213
- Abstract, 59, 127, 241
- Accountability, 9, 10 (Fig 1.2)
- Accuracy, 285, 286, 287
- Acquisition, 254
- Activity engagement, 93
- Ad Hoc, 111
- ADFA-LD, 307
- ADFA-WD, 307
- Adversarial, 296, 300, 302, 303, 312
- Adversary, 205
- Age-related cognitive decline and dementia, 94
- Aggregate functions, 84, 85
- AI, 295, 296, 297, 304, 310
- American society of testing materials, 111
- Analysis, 256
- Android, 297, 312
- ANN, 297
- ANN applications, 65
- Anonymous, 208
- Answer set programming in digital investigations, 61
- Anti-CSRF Tokens, 352
- API, 357
- Application layer, 206, 211, Fig. 9.1
- Application of artificial neural networking in predicting diseases, 66 Table-1
- Application of homomorphic encryption, 85
- AR face dataset, 235
- Architecture, 206 Arithmetic operations, 82, 84, 85
- Artificial intelligence, 93
- Artificial neural network works as patterns in predicting Information, 61, Fig 3.1
- Assessment, 164
- Asymmetric algorithms, 47
- Asymmetric key Cryptography, 46
- Attack, 295, 296, 297, 299, 300, 301, 303, 305, 306, 307, 308, 312
- Authentication cookies, 353
- Authenticity, 9, 10 (Fig 1.2)
- Authorization, 9, 10 (Fig 1.2)
- Authorization based trust, 218
- Autism spectrum disorders, 93
- Autopsy, 120, 122
- Availability, 9, 10 (Fig 1.2)
- BB84 quantum key distribution protocol, 45, 50, 51, 53, 55
- Behavioral mapping, 93
- Benchmarking, 165–173
- Beta-secretase, 100
- BGV, 80, 83, 84, Table 4.1
- Big data, 310
- Big data forensics, 154, 243
- Biometrics, 224
- Bionic devices, 97
- Bitcoin, 208, 214, 219
- Blockchain, 205, 208, 210, 214–219, 317, 318, 319, 323
- BMI, 99
- Boolean-based SQL injection, 338
- Bootstrapping, 78, 79, 80, 82, 83 Table 4.1
- Byzantine, 210, 217, 219
- CAINE, 121, 123
- Captcha, 278
- Causes of vulnerability, 340, 346, 350, 354, 357
- Cellebrite UFED, 121, 122
- Chain of custody, 128, 137, 139, 159
- Ciphertext, 74–87
- Ciphertext packing, 80, 82, 83
- CIPMA system, 188, 197
- CKSS, 77, 80, 87, Fig. 4.2
- Classical and quantum search of an item, 49
- Clients with disabilities and robotics, 94
- Cloud, 296, 297, 312
- Cloud computing, 73, 74, 87
- Cloud computing forensics, 243
- Cloud forensics, 116, 157, 159
- Clustering, 275, 298, 309
- CNN, 301
- COFEE, 122
- Cognitive decline, 94
- Command injection, 336, 353, 354, 355
- Command injection attack, 354, 355
- Communication, 205, 207
- Comparison operators, 83, 85
- Composite sketch, 235, Fig. 10.12
- Composite sketch with age variations, 235
- Computations on encrypted data, 73, 75, 76, 83, 86, 89
- Computer analysis and response team, 110
- Computer forensics, 117, 142
- Conclusion, 55, 68, 86–87, 267, 155, 160–161
- Confidentiality, 8
- Consensus, 210, 215–217, 219
- Consortium, 210, 221
- Content security policy (CSP), 348
- Convolutional neural network, 276–277
- CPIndex, 167, 168
- CPS designing, 164, 169
- CPS engineering, 166
- CPSSEC, 163, 164, 165, 166, 172, 173, 175, 181, 200
- Crime, 223, 224, 229, 238, 248, 326, 327, 330
- Cross site request forgery (CSRF), 336, 349
- Cross site scripting (XSS), 336, 344
- Cross-site scripting, 249
- Cryptocurrency, 326, 327, 330
- Cryptographic, 205, 208, 219
- Cryptographic digital signatures, 45
- Cryptographic techniques, 73, 74
- Cryptography, 298
- CSP header, 348
- CSRF attack, 353, 349
- CSRF vulnerabilities, 349, 350, 351
- CTU-13, 306
- Custom header, 352
- Cyber, 300
- Cyber physical systems (CPS), 163, 164
- Cyber security, 326, 327, 330
- Cyber stalking, 251
- Cyberattack, 296, 299, 300, 301, 302, 304, 310, 312, 313
- Cyber-attacks, 127
- Cyber-crime, 127
- Cybersecurity, 200, 272, 295, 296, 298, 299, 300, 301, 302, 303, 304, 305, 307, 309, 310, 311, 313
- Cyber-security assessment corpus, 173
- Darkweb, 317
- Data analysis, 283
- Data carving, 257
- Data diddling, 251
- Data forensics, 147
- Data sanitization, 341, 347
- Data science processing with artificial intelligence models, 64
- Data security, 73, 74, 75, 76
- Data validation, 347
- Database forensics, 118
- Dataset, 281–282
- DDoS, 296, 305
- De facto Cyber & Physical Security (DCPS), 176, 182
- Decentralized, 208, 221
- Decision tree, 298, 309, 310
- Deep learning and modelling, 67
- Deep learning enabled cyber–forensic investigation analysis, 62, Fig 3.2
- Deep learning, 276
- Defense computer forensic laboratory, 110
- Delegated Proof of Stake (DPoS), 209–210
- Dementia, 94
- Denial of service, 135–137, 250
- Design security, 163, 165, 174
- Diagonal basis, 50, 51
- Digital forensic analysis knowledge, 61
- Digital forensics, 107, 127–129, 142, 147, 150, 154–155, 157
- Digital forensics history, 108
- Digital forensics process, 244
- Digital forensics tools, 119
- Dimensionality reduction, 310
- Directory traversal, 357
- Disguised faces in wild, 235
- Disk forensics, 141–143, 147
- DL, 297, 298, 299, 301
- Domain specific methods, 223, 224, 230, 231
- DOM-based Cross Site Scripting (DOM-XSS), 344, 346
- DoS, 301, 305
- Double-chain, 216
- Drug discovery and robotics, 100
- E91 protocol, 51, 52, 55
- ECML-PKDD 2007, 305
- Elliptic curve cryptography (ECC), 48
- Email forensic, 131, 133
- Email spamming, 251
- Embedded systems, 169
- Emotional desires, 95
- Encase, 119, 121
- Entanglement, 51
- Enterprise phase, 112
- E-PRIP (Extended PRIP), 235
- Error-based SQL Injection, 337
- Ethical concerns and robotics, 95
- Evidence collection and analysis, 118, Fig. 6.5
- Evolutionary cycle of digital forensics, 111
- EWF (Energy), 210
- Exceptional case security assessment corpus, 173
- Exploitation techniques, 344, 349, 354, 355, 358
- Face recognition, 223, 224, 225, 226, 227, 228, 229
- Facebook, 295, 310, 311
- Factoring of a large number, 47
- Federated, 210
- FG-Net, 235
- File inclusion, 336, 355
- Firewall, 301
- Forensic education program accreditation commission, 111
- Forensic face recognition, 223, 224, 229, 230, 231, 232, 233, 234, 235
- Forensic science laboratory, 230
- Forensics, 223, 224
- Forensics process principles, 108
- Forensics toolkit, 110, 121
- FTP forensics, 133–134
- Future directions, 55
- Future robotics, 96
- Future space exploration, 98
- Fuzzy, 165
- Hacking, 249
- Hash-based signature techniques, 55
- Hashing algorithms, 47
- HEAAN, 85
- Heart catheterization, 100
- Heisenberg’s uncertainty principle, 49
- HElib, 73, 79, 80, 81, 82, 83, 84, 85 Table 4.1, Table 4.2
- Hidato puzzle (Hidoku) Matrix list (Kjellerstrand, 2015), 63, Fig-3.3
- HMM, 298
- Holistic, 164, 165, 166, 168, 169, 171, 175, 178, 179, 186, 192, 200
- Holistic comparison, 231
- Holistic, Medical-Specific & Boundary Cases (HMSB), 178
- Homomorphic encryption, 73–87, Fig. 4.1, Fig. 4.2
- Homomorphic encryption libraries, 79, 82, 83, Table 4.1
- HTML tag, 351
- HTTP header, 348, 351, 352, 354
- HTTP referer, 351
- HTTP request, 349, 351, 353, 356
- HTTP request with GET method, 349
- HTTP request with POST method, 350
- Human-robot interaction, 91
- IDC, 297
- Identification, 244, 253
- Identity theft, 251
- Improving psychosocial outcomes through robotics, 94
- In-band SQL injection, 337
- Industrial revolution, 164
- Industries and robotics, 98
- Inferential SQL injection, 337, 338
- Information, 296, 297, 303, 304, 305, 306
- Input validation, 341, 357
- Integer factorization, 46
- Integrity, 9
- International organization on computer evidences, 109, 110
- Internet of Things (IoT), 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 16, 17, 19, 24, 25, 26, 31, 33, 35, 36, 167
- Introduction, 60–61, 73–76, 127, 241
- Intrusion, 296, 298, 299, 301, 305, 307, 309, 310
- Inventions in ASD clinical practice, 94
- Investigation, 247
- IoT, 205–208, 211–216, 219–221ß, 296, 310, 317, 321
- IoT domains, 205, 212–213, Fig. 9.3, Fig. 9.4
- IoT forensics, 116, 155–157 ISOT, 306
- Machine learning, 100, 274
- Macie, 297
- Malicious, 215, 217, 296, 297, 298, 299, 301, 302, 303, 304, 306, 309, 312
- Malicious inputs, 335, 336, 338, 358
- Malware, 274, 296, 299, 300, 301, 305, 306, 307, 308, 309
- Malwares, 142–144, 152, 157
- Mathematical optimization, 99
- MAWILab, 307
- Medical Cyber Physical Systems (MCPS), 163
- Medical device-security assessment corpus, 173
- Medical diagnosis, 99
- Memory forensics, 144
- Mental healthcare training, 94
- Micro controller units, 169
- Microsoft, 295, 311, 312
- Middleware, 172
- MITM, 296
- ML, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 307, 309, 310, 311, 312, 313
- Mobile forensics, 116, 149–152, 154
- MODBUS, 298
- Model driven testing, 198
- Model for pattern recognition in forensic analysis, 65, Fig-3.5
- Models, 297, 299, 300, 302, 303, 305, 309, 311, 313
- MONAX, 210
- Morphological analysis, 231
- Most Vulnerable Module (MVM), 176, 189, 195
- MQTT, 206
- Multi-disciplinary, 165, 173
- Multi-party quantum key agreement protocol, 53
- Multithreading, 80, 82, 83, Table 4.2
- Partial homomorphic encryption schemes, 77
- Partial occlusion, 233, 235, 237, Fig. 10.11 Pattern recognition in deep learning algorithm, 68, Fig-3.7
- Pattern recognition techniques, 63
- Phases of digital investigation provides knowledge in forensic science analysis, 67 Fig-3.6
- Phishing, 250, 274, 296, 298, 299, 131–133, 140, 142, 306, 312
- Photo anthropometry, 231
- Photon Number Splitting (PNS) Attack, 53
- PHP-Data Object (PDO), 342
- Physical capabilities of robots, 92
- Physical security assessment corpus, 181, 182
- Polarization, 50, 52
- Post-quantum digital signatures, 45, 53
- practical Byzantine Fault Tolerance (pBFT), 210
- Practical challenges of quantum key distribution, 52
- Precision, 284
- Pre-processing, 283
- Privacy, 9, 10 (Fig 1.2), 32 (Table 1.5), 33 (Table 1.6), 34 (Table 1.7), 73, 74, 75, 85, 86
- Privacy breaching, 252
- Proof of Burn (PoB), 209
- Proof of Importance (PoI), 209
- Proof of Stake (PoS), 209, 216
- Proof of Work (PoW), 209, 216–217
- Proposed key verification phase for BB84, 51
- Protection techniques, 341, 347, 351, 355, 357, 358
- Psychiatric care settings, 94
- Radio frequency identification (RFID), 2, 5, 7 (Fig 1.1), 8, 12 (Fig 1.5), 17, 20 (Table 1.3), 30 (Fig 1.9), 34
- Recall, 284
- Recryption, 82, 83, Table 4.2
- Rectilinear basis, 50, 51
- Recurrent neural network, 277–278
- References, 69–72, 161–162, 219–221, 267
- Reflected cross site scripting (Reflected XSS), 344
- Reinforcement learning, 275
- Reliability, 9, 10 (Fig 1.2)
- Reliable, Replicated, Redundant, And Fault-Tolerant (RAFT), 210
- Relinearization, 82, 83, Table 4.2
- Remote file inclusion (RFI), 355
- Report writing, 265
- Restricted Boltzmann Machine, 277
- RFI vulnerability, 357
- Ring learning with errors (RLWE), 78
- Role of Artificial Intelligence in data science, 64, Fig-3.4
- Router forensics, 137, 139
- Routing based trust, 218
- RSA, 77, 87 Fig. 4.2
- Salami fraud attack, 251
- SANS, 119, 121
- SCADA, 317, 318, 322
- Scenario-based, 168
- Score-based, 174, 200
- SEAL, 79, 80, 81, 82, 83, Table 4.1, Table 4.2
- Secure computations, 79
- Security, 296, 297, 298, 299, 300, 301, 302, 304, 305, 306, 310, 311, 312, 313
- Security of modern cryptographic systems, 46, Table 2.1
- Security pivotal, 164, 200
- Service-Oriented Architecture (SOA), 1, 2, 3, 4, 10, 11, 12, 17, 24, 33
- Session cookie handling mechanism, 350
- Session hijacking, 250
- SHA256, 205, 208
- Shell Injection, 354
- Shor’s algorithm, 46, 47, 48, 49
- Signature, 295, 297, 298, 300, 301, 309, 310
- Signatures based on lattice techniques, 54, 55
- Signatures based on multivariate quadratic techniques, 55
- SIM swapping, 252
- Sketch based recognition, 236, 237, Fig 10.9
- Smart healthcare, 212–214, Fig. 9.3, Fig. 9.4
- SMOTE, 298
- Social skill development, 93
- Socially assistive robots, 93
- Somewhat homomorphic encryption, 77, 78
- Spam, 297, 298, 299, 305, 306, 312
- Spyware, 282
- SQL injection, 167, 183, 190, 196, 249, 336, 337, 339
- SQL injection attack, 343
- SQL injection vulnerabilities, 340, 341, 342, 343, 344, 353
- SQL statement, 336, 337, 342, 343
- Stage I, 112
- Stage II, 113
- Stage III, 114
- Stages of digital forensics process, 112
- Steal FTP password, 250
- Step-by-step, 165, 166, 174
- Stored Cross Site Scripting (Stored XSS), 344, 345
- Strength of asymmetric cryptographic systems, 47
- Structured phase, 111
- Subject Matter Experts (SME), 165
- Summary, 123
- Superimposition, 231
- Supervised Learning, 274
- Support vector machine, 284–289
- SVM, 309
- Symbolic computations, 99
- Symmetric algorithms, 47
- Symmetric key cryptographic systems, 46, 47
- Synthetic psychology and robotics, 97
- Synthetic psychology, 95
- Synthetic psychology: The foresight, 98
- System Preparedness Level (SPL), 182, 191, 192, 193, 194, 196, 197, 198, 199
- Systematic, 175, 200
- Task-oriented algorithms, 170
- Terrorist, 319, 320
- Testing, 299, 302, 303, 305
- TFHE, 80, 81, 82, 83, Table 4.1, Table 4.2
- The Sleuth Kit, 389
- Threat, 296, 297, 299, 300, 301, 302, 304, 310, 311, 312
- Time-based SQL injection, 339
- Training, 297, 298, 302, 303, 305
- Trojan virus, 274
- Types of digital forensics, 389
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