Artificial Intelligence Trust, Risk and Security Management (AI TRiSM): Frameworks, applications, challenges and future research directions
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The People, Process, Technology (PPT) framework, widely used in cybersecurity, is also well-suited for evaluating LLM benchmarks due to its holistic approach, addressing not just technical factors, but also human and procedural elements.
“The People, Process, Technology (PPT) framework, widely used in cybersecurity, is also well-suited for evaluating LLM benchmarks due to its holistic approach, addressing not just technical factors, but also human and procedural elements [37].”
From Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence (2026) · cites this paper as [37]
Cites
1 retracted
Kamruzzaman, M. M., Alrashdi, I., & Alqazzaz, A. (2022) · Journal of Healthcare Engineering · doi:10.1155/2022/2950699 · Cited by 68 · see citing works
RetractedGenerative adversarial networks
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2020) · Communications of the ACM · doi:10.1145/3422622 · Cited by 18,384 · see citing works
Journal of Physics: Conference Series
Jui, J. J., Mohd Helmi, S., Mohd Riduwan, G., Mohd Ashraf, A., & Mohd Zaidi, M. T. (2013) · Journal of Physics Conference Series · doi:10.1088/issn.1742-6596 · Cited by 15,799 · see citing works
Artificial Intelligence in Education: A Review
Chen, L., Chen, P., & Lin, Z. (2020) · IEEE Access · doi:10.1109/access.2020.2988510 · Cited by 4,133 · see citing works
Human trust in artificial intelligence: Review of empirical research
Glikson, E., & Woolley, A. W. (2020) · Academy of Management Annals · doi:10.5465/annals.2018.0057 · Cited by 2,921 · see citing works
Artificial intelligence in healthcare
Yu, K.-H., Beam, A. L., & Kohane, I. S. (2018) · Nature Biomedical Engineering · doi:10.1038/s41551-018-0305-z · Cited by 2,817 · see citing works
A survey on federated learning
Zhang, C., Xie, Y., Bai, H., Yu, B., Li, W., & Gao, Y. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2021.106775 · Cited by 1,899 · see citing works
Blockchain for IoT security and privacy: The case study of a smart home
Dorri, A., Kanhere, S. S., Jurdak, R., & Gauravaram, P. (2017) · 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2017.7917634 · Cited by 1,843 · see citing works
Automatic analysis of facial expressions: the state of the art
Pantie, M., & Rothkrantz, L. J. M. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.895976 · Cited by 1,778 · see citing works
The rise of artificial intelligence in healthcare applications
Bohr, A., & Memarzadeh, K. (2020) · Artificial Intelligence in Healthcare · doi:10.1016/b978-0-12-818438-7.00002-2 · Cited by 1,636 · see citing works
Vaio, A. D., Palladino, R., Hassan, R., & Escobar, O. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.08.019 · Cited by 1,205 · see citing works
The Emergence of Deepfake Technology: A Review
Westerlund, M. (2019) · Technology Innovation Management Review · doi:10.22215/timreview/1282 · Cited by 1,138 · see citing works
Vaccari, C., & Chadwick, A. (2020) · Social Media + Society · doi:10.1177/2056305120903408 · Cited by 978 · see citing works
Addressing bias in big data and AI for health care: A call for open science
Norori, N., Hu, Q., Aellen, F. M., Faraci, F. D., & Tzovara, A. (2021) · Patterns · doi:10.1016/j.patter.2021.100347 · Cited by 903 · see citing works
A survey of emerging threats in cybersecurity
Jang-Jaccard, J., & Nepal, S. (2014) · Journal of Computer and System Sciences · doi:10.1016/j.jcss.2014.02.005 · Cited by 892 · see citing works
The roles of initial trust and perceived risk in public’s acceptance of automated vehicles
Zhang, T., Tao, D., Qu, X., Zhang, X. Y., Lin, R., & Zhang, W. (2018) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2018.11.018 · Cited by 853 · see citing works
Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians
Asan, O., Bayrak, A. E., & Choudhury, A. (2020) · Journal of Medical Internet Research · doi:10.2196/15154 · Cited by 825 · see citing works
Artificial intelligence for the metaverse: A survey
Huynh‐The, T., Pham, Q., Pham, X., Nguyen, T. T., Han, Z., & Kim, D. (2022) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2022.105581 · Cited by 788 · see citing works
A Survey on quantum computing technology
Gyongyosi, L., & Imre, S. (2019) · Computer Science Review · doi:10.1016/j.cosrev.2018.11.002 · Cited by 646 · see citing works
Sohn, K., & Kwon, O. (2020) · Telematics and Informatics · doi:10.1016/j.tele.2019.101324 · Cited by 646 · see citing works
Artificial intelligence applications in the development of autonomous vehicles: a survey
Ma, Y., Wang, Z., Yang, H., & Yang, L. (2020) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2020.1003021 · Cited by 639 · see citing works
Advances, challenges and opportunities in creating data for trustworthy AI
Liang, W., Tadesse, G. A., Ho, D. E., Fei-Fei, L., Zaharia, M., Zhang, C., & Zou, J. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00516-1 · Cited by 582 · see citing works
Fusing Blockchain and AI With Metaverse: A Survey
Yang, Q., Zhao, Y., Huang, H., Xiong, Z., Kang, J., & Zheng, Z. (2022) · IEEE Open Journal of the Computer Society · doi:10.1109/ojcs.2022.3188249 · Cited by 576 · see citing works
Differential Privacy Techniques for Cyber Physical Systems: A Survey
Hassan, M. U., Rehmani, M. H., & Chen, J. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2944748 · Cited by 564 · see citing works
Use of AI-based tools for healthcare purposes: a survey study from consumers’ perspectives
Esmaeilzadeh, P. (2020) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-020-01191-1 · Cited by 507 · see citing works
Nikitas, A., Michalakopoulou, K., Njoya, E. T., & Karampatzakis, D. (2020) · Sustainability · doi:10.3390/su12072789 · Cited by 495 · see citing works
An introduction to quantum computing for non-physicists
Rieffel, E. G., & Polak, W. (2000) · ACM Computing Surveys · doi:10.1145/367701.367709 · Cited by 436 · see citing works
The demand for AI skills in the labor market
Alekseeva, L., Azar, J., Giné, M., Samila, S., & Taska, B. (2021) · Labour Economics · doi:10.1016/j.labeco.2021.102002 · Cited by 432 · see citing works
Mahbooba, B., Timilsina, M., Sahal, R., & Serrano, M. (2021) · Complexity · doi:10.1155/2021/6634811 · Cited by 333 · see citing works
An Enhanced AI-Based Network Intrusion Detection System Using Generative Adversarial Networks
Park, C.-H., Lee, J., Kim, Y., Park, J., Kim, H., & Hong, D. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3211346 · Cited by 319 · see citing works
Bias and Discrimination in AI: A Cross-Disciplinary Perspective
Ferrer, X., Nuenen, T. V., Such, J. M., Cote, M., & Criado, N. (2021) · IEEE Technology and Society Magazine · doi:10.1109/mts.2021.3056293 · Cited by 308 · see citing works
A risk analysis of a smart home automation system
Jacobsson, A., Boldt, M., & Carlsson, B. (2015) · Future Generation Computer Systems · doi:10.1016/j.future.2015.09.003 · Cited by 300 · see citing works
Kong, H., Yin, Z., Baruch, Y., & Yuan, Y. (2023) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2023.103928 · Cited by 291 · see citing works
Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions
King, T. C., Aggarwal, N., Taddeo, M., & Floridi, L. (2020) · Science and Engineering Ethics · doi:10.1007/s11948-018-00081-0 · Cited by 271 · see citing works
Clinical AI: opacity, accountability, responsibility and liability
Smith, H. (2021) · AI & SOCIETY · doi:10.1007/s00146-020-01019-6 · Cited by 245 · see citing works
Artificial Intelligence in Healthcare: Review, Ethics, Trust Challenges & Future Research Directions
Kumar, P., Chauhan, S., & Awasthi, L. K. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.105894 · Cited by 236 · see citing works
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence
Zhu, T., Ye, D., Wang, W., Zhou, W., & Yu, P. S. (2022) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2020.3014246 · Cited by 219 · see citing works
Artificial Intelligence in Transportation Systems A Critical Review
Bharadiya, J. (2023) · American Journal of Computing and Engineering · doi:10.47672/ajce.1487 · Cited by 209 · see citing works
Artificial Intelligence in Cancer Research: Trends, Challenges and Future Directions
Sebastian, A. M., & Peter, D. (2022) · Life · doi:10.3390/life12121991 · Cited by 199 · see citing works
The Impact and Limitations of Artificial Intelligence in Cybersecurity: A Literature Review
Ansari, M. F., Dash, B., Sharma, P., et al. (2022) · IJARCCE · doi:10.17148/ijarcce.2022.11912 · Cited by 196 · see citing works
Lukyanenko, R., Maaß, W., & Storey, V. C. (2022) · Electronic Markets · doi:10.1007/s12525-022-00605-4 · Cited by 194 · see citing works
Secrets and Lies: Digital Security in a Networked World
(2003) · Info · doi:10.1108/info.2003.5.1.78.4 · Cited by 190 · see citing works
Supply Chain 4.0: A Survey of Cyber Security Challenges, Solutions and Future Directions
Sobb, T., Turnbull, B., & Moustafa, N. (2020) · Electronics · doi:10.3390/electronics9111864 · Cited by 189 · see citing works
Tan, L., Yu, K., Ming, F., Cheng, X., & Srivastava, G. (2021) · IEEE Consumer Electronics Magazine · doi:10.1109/mce.2021.3081874 · Cited by 186 · see citing works
SAFE Artificial Intelligence in finance
Giudici, P., & Raffinetti, E. (2023) · Finance research letters · doi:10.1016/j.frl.2023.104088 · Cited by 182 · see citing works
Challenges and Opportunities of AI-Enabled Monitoring, Diagnosis & Prognosis: A Review
Zhao, Z., Wu, J., Li, T., Sun, C., Yan, R., & Chen, X. (2021) · Chinese Journal of Mechanical Engineering · doi:10.1186/s10033-021-00570-7 · Cited by 160 · see citing works
Open RAN security: Challenges and opportunities
Liyanage, M., Braeken, A., Shahabuddin, S., & Ranaweera, P. S. (2023) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2023.103621 · Cited by 156 · see citing works
Tonyalı, S., Akkaya, K., Saputro, N., Uluagac, A. S., & Nojoumian, M. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.04.031 · Cited by 147 · see citing works
Kim, J., Merrill, K., Xu, K., & Kelly, S. E. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107383 · Cited by 147 · see citing works
AI Empowered Communication Systems for Intelligent Transportation Systems
Lv, Z., Lou, R., & Singh, A. K. (2020) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.3017183 · Cited by 143 · see citing works
Ethical Considerations in AI-Based Recruitment
Mujtaba, D. F., & Mahapatra, N. R. (2019) · IEEE International Symposium on Technology and Society (ISTAS) · doi:10.1109/istas48451.2019.8937920 · Cited by 142 · see citing works
Why do users trust algorithms? A review and conceptualization of initial trust and trust over time
Cabiddu, F., Moi, L., Patriotta, G., & Allen, D. G. (2022) · European Management Journal · doi:10.1016/j.emj.2022.06.001 · Cited by 138 · see citing works
Weapon Detection using Artificial Intelligence and Deep Learning for Security Applications
Jain, H., Vikram, A., Mohana, Kashyap, A., & Jain, A. (2020) · International Conference on Electronics and Sustainable Communication Systems (ICESC) · doi:10.1109/icesc48915.2020.9155832 · Cited by 124 · see citing works
On Artificial Intelligence and Manipulation
Ienca, M. (2023) · Topoi · doi:10.1007/s11245-023-09940-3 · Cited by 117 · see citing works
Algorithmic Political Bias in Artificial Intelligence Systems
Peters, U. (2022) · Philosophy & Technology · doi:10.1007/s13347-022-00512-8 · Cited by 111 · see citing works
Chauhan, C., & Gullapalli, R. R. (2021) · American Journal Of Pathology · doi:10.1016/j.ajpath.2021.06.011 · Cited by 107 · see citing works
AIT: An AI-Enabled Trust Management System for Vehicular Networks Using Blockchain Technology
Zhang, C., Li, W., Luo, Y., & Hu, Y. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3044296 · Cited by 106 · see citing works
Blockchain-Aided Secure Semantic Communication for AI-Generated Content in Metaverse
Lin, Y.-J., Du, H.-Y., Niyato, D., Nie, J.-T., Zhang, J.-Y., Cheng, Y., & Yang, Z. (2023) · IEEE Open Journal of the Computer Society · doi:10.1109/ojcs.2023.3260732 · Cited by 106 · see citing works
ModelOps: Cloud-Based Lifecycle Management for Reliable and Trusted AI
Hummer, W., Muthusamy, V., Rausch, T., Dube, P., El Maghraoui, K., Murthi, A., & Oum, P. (2019) · 2019 IEEE International Conference on Cloud Engineering (IC2E) · doi:10.1109/ic2e.2019.00025 · Cited by 105 · see citing works
Applications of Artificial Intelligence in Evolution of Smart Cities and Societies
Veselov, G., Tselykh, A., Sharma, A., et al. (2021) · Informatica · doi:10.31449/inf.v45i5.3600 · Cited by 103 · see citing works
González-Gonzalo, C., Thee, E. F., Klaver, C. C. W., Lee, A. Y., Schlingemann, R. O., Tufail, A., Verbraak, F., & Sánchez, C. I. (2022) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2021.101034 · Cited by 103 · see citing works
Smart Collaborative Balancing for Dependable Network Components in Cyber-Physical Systems
Song, F., Ai, Z., Zhang, H., et al. (2020) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.3029766 · Cited by 102 · see citing works
Bias in Artificial Intelligence
Nelson, G. S. (2019) · North Carolina Medical Journal · doi:10.18043/ncm.80.4.220 · Cited by 100 · see citing works
Attention based multi-agent intrusion detection systems using reinforcement learning
Sethi, K., Madhav, Y. V., Kumar, R., & Bera, P. (2021) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2021.102923 · Cited by 95 · see citing works
Enhancing trust in AI through industry self-governance.
Roski, J., Maier, E. J., Vigilante, K., Kane, E. A., & Matheny, M. E. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab065 · Cited by 83 · see citing works
Francisco, M., & Linnér, B. (2023) · Environmental Science & Policy · doi:10.1016/j.envsci.2023.103590 · Cited by 77 · see citing works
Artificial Intelligence Based Commercial Risk Management Framework for SMEs
Žigienė, G., Rybakovas, E., & Alzbutas, R. (2019) · Sustainability · doi:10.3390/su11164501 · Cited by 76 · see citing works
Владимировна, Ф. Е., Novikova, E. S., & Shulepov, A. (2022) · Algorithms · doi:10.3390/a15070247 · Cited by 74 · see citing works
Architecture, Protocols, and Security in IoV: Taxonomy, Analysis, Challenges, and Solutions
Karim, S. M., Habbal, A., Chaudhry, S. A., & Irshad, A. (2022) · Security and Communication Networks · doi:10.1155/2022/1131479 · Cited by 73 · see citing works
Self-citationThree Ethical Challenges of Applications of Artificial Intelligence in Cybersecurity
Taddeo, M. (2019) · Minds and Machines · doi:10.1007/s11023-019-09504-8 · Cited by 72 · see citing works
Trustworthy AI Development Guidelines for Human System Interaction
Wickramasinghe, C. S., Marino, D. L., Grandio, J., & Manic, M. (2020) · 2020 13th International Conference on Human System Interaction (HSI) · doi:10.1109/hsi49210.2020.9142644 · Cited by 71 · see citing works
Mitrou, L. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3386914 · Cited by 70 · see citing works
van Bekkum, M., & Zuiderveen Borgesius, F. (2023) · Computer Law & Security Review · doi:10.1016/j.clsr.2022.105770 · Cited by 69 · see citing works
Ethics of autonomous weapons systems and its applicability to any AI systems
Gómez de Ágreda, Á. (2020) · Telecommunications Policy · doi:10.1016/j.telpol.2020.101953 · Cited by 65 · see citing works
Criminal courts’ artificial intelligence: the way it reinforces bias and discrimination
Malek, A. (2022) · AI and Ethics · doi:10.1007/s43681-022-00137-9 · Cited by 64 · see citing works
IoT Security in Healthcare using AI: A Survey
Gopalan, S. S., Raza, A., & Almobaideen, W. A. (2021) · International Conference on Communications, Signal Processing, and their Applications (ICCSPA) · doi:10.1109/iccspa49915.2021.9385711 · Cited by 62 · see citing works
Using artificial intelligence to support compliance with the general data protection regulation
Kingston, J. (2017) · Artificial Intelligence and Law · doi:10.1007/s10506-017-9206-9 · Cited by 60 · see citing works
Habbal, A., Goudar, S. I., & Hassan, S. (2019) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2019.02.019 · Cited by 60 · see citing works
Self-citationChen, Y., Zahedi, F. M., Abbasi, A., & Dobolyi, D. (2021) · Information & Management · doi:10.1016/j.im.2020.103394 · Cited by 53 · see citing works
De, T., Giri, P., Mevawala, A., Nemani, R., & Deo, A. (2020) · Procedia Computer Science · doi:10.1016/j.procs.2020.02.255 · Cited by 52 · see citing works
Contribution of Artificial Intelligence to Risk Assessment of Railway Accidents
Hadj‐Mabrouk, H. (2019) · Urban Rail Transit · doi:10.1007/s40864-019-0102-3 · Cited by 48 · see citing works
Benmoussa, A., Kerrache, C. A., Lagraa, N., et al. (2022) · ACM Computing Surveys · doi:10.1145/3539730 · Cited by 46 · see citing works
Build confidence and acceptance of AI-based decision support systems - Explainable and liable AI
Nicodème, C. (2020) · Conference on Human System Interactions · doi:10.1109/hsi49210.2020.9142668 · Cited by 43 · see citing works
CTMF: Context-Aware Trust Management Framework for Internet of Vehicles
Rehman, A., Hassan, M. F., Hooi, Y. K., Qureshi, M. A., Shukla, S., Susanto, E., Rubab, S., & Abdel‐Aty, A. (2022) · IEEE Access · doi:10.1109/access.2022.3189349 · Cited by 40 · see citing works
1987 IEEE Symposium on Security and Privacy
Systemtransactions, T. E., Jana, S., Porter, D. E., et al. (1986) · Computer · doi:10.1109/mc.1986.1663329 · Cited by 38 · see citing works
Malicious Use of Artificial Intelligence
Bazarkina, D., & Pashentsev, E. N. (2020) · Russia in Global Affairs · doi:10.31278/1810-6374-2020-18-4-154-177 · Cited by 37 · see citing works
Solomon, A., Michaelshvili, M., Bitton, R., Shapira, B., Rokach, L., Puzis, R., & Shabtai, A. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.108709 · Cited by 34 · see citing works
Orchestrating artificial intelligence for urban sustainability
Zhang, D., Pee, L. G., Pan, S. L., & Liu, W. (2022) · Government Information Quarterly · doi:10.1016/j.giq.2022.101720 · Cited by 34 · see citing works
Kumar, G., James, A. T., Choudhary, K., Sahai, R., & Song, W. K. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.122080 · Cited by 33 · see citing works
Face deidentification with controllable privacy protection
Meden, B., González-Hernández, M., Peer, P., et al. (2023) · Image and Vision Computing · doi:10.1016/j.imavis.2023.104678 · Cited by 32 · see citing works
Toward Scalable Artificial Intelligence in Finance
Sanz, J. L. C., & Zhu, Y. (2021) · IEEE International Conference on Services Computing · doi:10.1109/scc53864.2021.00067 · Cited by 31 · see citing works
Explanations in warning dialogs to help users defend against phishing attacks
Desolda, G., Aneke, J., Ardito, C. A., Lanzilotti, R., & Costabile, M. F. (2023) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2023.103056 · Cited by 31 · see citing works
Roadmap toward the metaverse: An AI perspective
Cheng, S., Zhang, Y., Li, X., Yang, L., Yuan, X., & Li, S. Z. (2022) · The Innovation · doi:10.1016/j.xinn.2022.100293 · Cited by 28 · see citing works
The roles of outcome and race on applicant reactions to AI systems
Bedemariam, R. S., & Wessel, J. L. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107869 · Cited by 28 · see citing works
Technological advancements and 2020
Khan, M. K. (2019) · Telecommunication Systems · doi:10.1007/s11235-019-00647-8 · Cited by 27 · see citing works
Artificial Intelligence In Healthcare
Rekha, K. P. (2021) · KYAMC Journal · doi:10.3329/kyamcj.v11i4.51989 · Cited by 27 · see citing works
Askar, N. A., Habbal, A., Alden, F. Z., Wei, X., Alaidaros, H., Guo, J., & Yu, H. (2023) · IEEE Access · doi:10.1109/access.2023.3276713 · Cited by 27 · see citing works
Self-citationKim, J., Kang, S., & Bae, J. (2021) · International Journal of Advertising · doi:10.1080/02650487.2021.1963098 · Cited by 26 · see citing works
Artificial Intelligence in Finance: Possibilities and Threats
Eluwole, O. T., & Akande, S. (2022) · IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) · doi:10.1109/iaict55358.2022.9887488 · Cited by 22 · see citing works
Efficient and privacy-preserving tree-based inference via additive homomorphic encryption
Zhao, J., Zhu, H., Wang, F., Lu, R., & Li, H. (2023) · Information Sciences · doi:10.1016/j.ins.2023.119480 · Cited by 21 · see citing works
Online handwriting Arabic recognition system using k-nearest neighbors classifier and DCT features
Abuzaraida, M. A., Elmehrek, M., & Elsomadi, E. (2021) · International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering · doi:10.11591/ijece.v11i4.pp3584-3592 · Cited by 18 · see citing works
Self-citationTrust Management for Public Key Infrastructures: Implementing the X.509 Trust Broker
Wazan, A. S., Laborde, R., Chadwick, D. W., et al. (2017) · Security and Communication Networks · doi:10.1155/2017/6907146 · Cited by 16 · see citing works
On the Characterization and Risk Assessment of AI-Powered Mobile Cloud Applications
Elahi, H., Wang, G., Xu, Y., Castiglione, A., Yan, Q., & Shehzad, M. N. (2021) · Computer Standards & Interfaces · doi:10.1016/j.csi.2021.103538 · Cited by 15 · see citing works
Homomorphic Encryption within Lattice-Based Encryption System
Kadykov, V., Levina, A. B., & Voznesensky, A. S. (2021) · Procedia Computer Science · doi:10.1016/j.procs.2021.04.149 · Cited by 14 · see citing works
Wogu, I. A. P., Misra, S., Assibong, P. A., et al. (2018) · Springer eBooks · doi:10.1007/978-981-13-2348-5_16 · Cited by 13 · see citing works
Dhiman, A., & Toshniwal, D. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.117338 · Cited by 12 · see citing works
A Matter of (Joint) control? Virtual assistants and the general data protection regulation
van Mil, J., & Quintais, J. P. (2022) · Computer law & security review · doi:10.1016/j.clsr.2022.105689 · Cited by 12 · see citing works
Assessing Experimental Private Cloud Using Web of System Performance Model
Habbal, A., Abdullah, S. A., Mkpojiogu, E. O. C., et al. (2017) · International Journal of Grid and High Performance Computing · doi:10.4018/ijghpc.2017040102 · Cited by 10 · see citing works
Self-citationKumar, D., & Kumar, K. P. (2023) · International Conference for Innovation in Technology (INOCON) · doi:10.1109/inocon57975.2023.10100967 · Cited by 10 · see citing works
The Future of Wars: Artificial Intelligence (AI) and Lethal Autonomous Weapon Systems (LAWS)
Pedron, S. M., & da Cruz, J. D. A. (2020) · Cited by 9 · see citing works
Печегин, Д. (2022) · Transportation research procedia · doi:10.1016/j.trpro.2022.05.010 · Cited by 2 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence
McIntosh, T. R., Susnjak, T., Arachchilage, N., Liu, T., Xu, D., Watters, P., & Halgamuge, M. N. (2026) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2025.3569516 · Cited by 104 · see citing works
Abiona, O. O., Oladapo, O. J., Modupe, O. T., Oyeniran, O. C., Adewusi, A. O., & Komolafe, A. M. (2024) · World Journal of Advanced Engineering Technology and Sciences · doi:10.30574/wjaets.2024.11.2.0093 · Cited by 48 · see citing works
Klüver, C., Greisbach, A., Kindermann, M., & Püttmann, B. (2024) · Security and Safety · doi:10.1051/sands/2024020 · Cited by 8 · see citing works
“Due to the large number of publications, we focus on recent developments that affect SCS in the selected examples.”
- Authors
- Habbal, A., Ali, M. K., & Abuzaraida, M. A.
- Affiliations
- Karabük University (TR)
- Misurata University (LY)
- Corresponding author
- Habbal, Adib
- Ali, Mohamed Khalif
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2024-04
- Volume
- 240
- Pages
- 122442
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W4388720055
- Cited by
- 407
- References
- 112
- Citations by year
- 2026: 117 · 2025: 164 · 2024: 114 · 2023: 12
- FWCI
- 36.02
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Expert Systems with Applications (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Sociology and Political Science › Access Control and Trust
- Keywords
- AI risk management, trustworthy AI, adversarial attacks, regulatory compliance, skills gap, AI ethics, metaverse, smart healthcare, stakeholder collaboration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
