Boundaries and Future Trends of ChatGPT Based on AI and Security Perspectives
Abstract
Doi: 10.28991/HIJ-2024-05-01-010
Full Text: PDF
Keywords
References
OpenAI. (2024). OpenAI, California, United States. Available online: https://openai.com/ (accessed on January 2024).
Yang, J., Jin, H., Tang, R., Han, X., Feng, Q., Jiang, H., ... & Hu, X. (2023). Harnessing the power of LLMS in practice: A survey on chatgpt and beyond. ACM Transactions on Knowledge Discovery, 1-30. doi:10.1145/3649506.
Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., ... & McGrew, B. (2023). Gpt-4 Technical Report. arXiv preprint, arXiv:2303.08774. doi:10.48550/arXiv.2303.08774.
Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M. A., Lacroix, T., ... & Lample, G. (2023). Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971. doi:10.48550/arXiv.2302.13971.
Gallifant, J., Fiske, A., Levites Strekalova, Y. A., Osorio-Valencia, J. S., Parke, R., Mwavu, R., ... & Pierce, R. (2024). Peer review of GPT-4 technical report and systems card. PLOS Digital Health, 3(1), e0000417. doi:10.1371/journal.pdig.0000417.
Zhu, K., Wang, J., Zhou, J., Wang, Z., Chen, H., Wang, Y., ... & Xie, X. (2023). PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts. arXiv preprint. doi:10.48550/arXiv.2306.04528.
Spatharioti, S. E., Rothschild, D. M., Goldstein, D. G., & Hofman, J. M. (2023). Comparing Traditional and LLM-based Search for Consumer Choice: A Randomized Experiment. arXiv preprint. doi:10.48550/arXiv.2307.03744.
Yao, B., Jiang, M., Yang, D., & Hu, J. (2023). Empowering LLM-based Machine Translation with Cultural Awareness. arXiv preprint, arXiv.2305.14328. doi:10.48550/arXiv.2305.14328
Karpinska, M., & Iyyer, M. (2023). Large language models effectively leverage document-level context for literary translation, but critical errors persist. Conference on Machine Translation – Proceedings, 406–438. doi:10.18653/v1/2023.wmt-1.41.
Jain, R., Gervasoni, N., Ndhlovu, M., & Rawat, S. (2023). A Code Centric Evaluation of C/C++ Vulnerability Datasets for Deep Learning Based Vulnerability Detection Techniques. ACM International Conference Proceeding Series, 6, 1-10. doi:10.1145/3578527.3578530.
Thirunavukarasu, A. J., Ting, D. S. J., Elangovan, K., Gutierrez, L., Tan, T. F., & Ting, D. S. W. (2023). Large language models in medicine. Nature Medicine, 29(8), 1930–1940. doi:10.1038/s41591-023-02448-8.
Wu, S., Irsoy, O., Lu, S., Dabravolski, V., Dredze, M., Gehrmann, S., Kambadur, P., Rosenberg, D., & Mann, G. (2023). BloombergGPT: A Large Language Model for Finance. arXiv preprint. doi:10.48550/arXiv.2303.17564.
Mbakwe, A. B., Lourentzou, I., Celi, L. A., Mechanic, O. J., & Dagan, A. (2023). ChatGPT passing USMLE shines a spotlight on the flaws of medical education. PLOS Digital Health, 2(2), e0000205. doi:10.1371/journal.pdig.0000205.
Abdullah, M., Madain, A., & Jararweh, Y. (2022). ChatGPT: Fundamentals, Applications and Social Impacts. 9th International Conference on Social Networks Analysis, Management and Security, 1–8. doi:10.1109/SNAMS58071.2022.10062688.
Curtis, N. (2023). To ChatGPT or not to ChatGPT? The Impact of Artificial Intelligence on Academic Publishing. Pediatric Infectious Disease Journal, 42(4), 275. doi:10.1097/INF.0000000000003852.
Sallam, M. (2023). ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns. Healthcare (Switzerland), 11(6), 887. doi:10.3390/healthcare11060887.
Du, H., Teng, S., Chen, H., Ma, J., Wang, X., Gou, C., Li, B., Ma, S., Miao, Q., Na, X., Ye, P., Zhang, H., Luo, G., & Wang, F. Y. (2023). Chat With ChatGPT on Intelligent Vehicles: An IEEE TIV Perspective. IEEE Transactions on Intelligent Vehicles, 8(3), 2020–2026. doi:10.1109/TIV.2023.3253281.
Weidinger, L., Uesato, J., Rauh, M., Griffin, C., Huang, P. Sen, Mellor, J., Glaese, A., Cheng, M., Balle, B., Kasirzadeh, A., Biles, C., Brown, S., Kenton, Z., Hawkins, W., Stepleton, T., Birhane, A., Hendricks, L. A., Rimell, L., Isaac, W., … Gabriel, I. (2022). Taxonomy of Risks posed by Language Models. ACM International Conference Proceeding Series, 214–229. doi:10.1145/3531146.3533088.
Pearce, H., Tan, B., Ahmad, B., Karri, R., & Dolan-Gavitt, B. (2023). Examining Zero-Shot Vulnerability Repair with Large Language Models. Proceedings - IEEE Symposium on Security and Privacy, 2339–2356. doi:10.1109/SP46215.2023.10179324.
Wu, X., Duan, R., & Ni, J. (2023). Unveiling security, privacy, and ethical concerns of ChatGPT. Journal of Information and Intelligence, 1-14. doi:10.1016/j.jiixd.2023.10.007.
Qammar, A., Wang, H., Ding, J., Naouri, A., Daneshmand, M., & Ning, H. (2023). Chatbots to ChatGPT in a Cybersecurity Space: Evolution, Vulnerabilities, Attacks, Challenges, and Future Recommendations. arXiv preprint, 1-17. doi:10.48550/arXiv.2306.09255.
Tan, T. F., Thirunavukarasu, A. J., Campbell, J. P., Keane, P. A., Pasquale, L. R., Abramoff, M. D., ... & Ting, D. S. W. (2023). Generative artificial intelligence through ChatGPT and other large language models in ophthalmology: clinical applications and challenges. Ophthalmology Science, 3(4), 100394. doi:10.1016/j.xops.2023.100394.
Khoury, R., Avila, A. R., Brunelle, J., & Camara, B. M. (2024). How Secure is Code Generated by ChatGPT? Honolulu, United States. doi:10.1109/smc53992.2023.10394237.
Renaud, K., Warkentin, M., & Westerman, G. (2023). From ChatGPT to HackGPT: Meeting the Cybersecurity Threat of Generative AI. MIT Sloan Management Review, 64428, 5.
Derner, E., & Batistič, K. (2023). Beyond the Safeguards: Exploring the Security Risks of ChatGPT. arXiv preprint. doi:10.48550/arXiv.2305.08005.
Sebastian, G. (2023). Do ChatGPT and other AI chatbots pose a cybersecurity risk?: An exploratory study. International Journal of Security and Privacy in Pervasive Computing (IJSPPC), 15(1), 1-11. doi:10.4018/IJSPPC.320225.
Sebastian, G. (2023). Privacy and Data Protection in ChatGPT and Other AI Chatbots. International Journal of Security and Privacy in Pervasive Computing, 15(1), 1–14. doi:10.4018/ijsppc.325475.
Esmailzadeh, Y. (2023). Potential Risks of ChatGPT: Implications for Counterterrorism and International Security. International Journal of Multicultural and Multireligious Understanding, 10(4), 535–543. doi:10.18415/ijmmu.v10i4.4590.
Aiyappa, R., An, J., Kwak, H., & Ahn, Y. Y. (2023). Can we trust the evaluation on ChatGPT? Proceedings of the Annual Meeting of the Association for Computational Linguistics, 47–54. doi:10.18653/v1/2023.trustnlp-1.5.
Rahman, M. M., & Watanobe, Y. (2023). ChatGPT for Education and Research: Opportunities, Threats, and Strategies. Applied Sciences (Switzerland), 13(9), 5783. doi:10.3390/app13095783.
Li, J., Yang, Y., Wu, Z., Vydiswaran, V. G. V., & Xiao, C. (2023). ChatGPT as an Attack Tool: Stealthy Textual Backdoor Attack via Blackbox Generative Model Trigger. arXiv preprint. doi:10.48550/arXiv.2304.14475
Lande, D., & Strashnoy, L. (2023). Causality Network Formation with ChatGPT. SSRN Electronic Journal, 1-16. doi:10.2139/ssrn.4464477.
Sobania, D., Briesch, M., Hanna, C., & Petke, J. (2023). An Analysis of the Automatic Bug Fixing Performance of ChatGPT. Proceedings - IEEE/ACM International Workshop on Automated Program Repair, 23–30. doi:10.1109/APR59189.2023.00012.
Sarel, R. (2023). Restraining ChatGPT. SSRN Electronic Journal, 1-65. doi:10.2139/ssrn.4354486.
Shahriar, S., Allana, S., Hazratifard, S. M., & Dara, R. (2023). A Survey of Privacy Risks and Mitigation Strategies in the Artificial Intelligence Life Cycle. IEEE Access, 11, 61829–61854. doi:10.1109/ACCESS.2023.3287195.
Addington, S. (2023). ChatGPT: Cyber Security Threats and Countermeasures. SSRN Electronic Journal, 1-12. doi:10.2139/ssrn.4425678.
Khalid, N., Qayyum, A., Bilal, M., Al-Fuqaha, A., & Qadir, J. (2023). Privacy-preserving artificial intelligence in healthcare: Techniques and applications. Computers in Biology and Medicine, 158. doi:10.1016/j.compbiomed.2023.106848.
Hastings, M. C. (2021). Secure Multi-Party Computation in Practice. Doctoral Dissertation, University of Pennsylvania, Pennsylvania, United States.
Rajan, A. A., & Rajan, A. A. (2020). Data Anonymization Techniques for Preserving Privacy in Public Release Data Model A Technical Review. International Journal of Scientific Research in Computer Science and Engineering, 8(1), 58–62. doi:10.26438/ijsrcse/v8i1.5862.
Jiang, B., Li, J., Yue, G., & Song, H. (2021). Differential Privacy for Industrial Internet of Things: Opportunities, Applications, and Challenges. IEEE Internet of Things Journal, 8(13), 10430–10451. doi:10.1109/JIOT.2021.3057419.
Bai, T., Luo, J., Zhao, J., Wen, B., & Wang, Q. (2021). Recent Advances in Adversarial Training for Adversarial Robustness. IJCAI International Joint Conference on Artificial Intelligence, 4312–4321. doi:10.24963/ijcai.2021/591.
Zhao, W., Alwidian, S., & Mahmoud, Q. H. (2022). Adversarial Training Methods for Deep Learning: A Systematic Review. Algorithms, 15(8), 283. doi:10.3390/a15080283.
Malle, B., Schrittwieser, S., Kieseberg, P., & Holzinger, A. (2016). Privacy Aware Machine Learning and the Right to be forgotten. ERCIM News, 107(10), 22–23.
Park, J., & Lim, H. (2022). Privacy-Preserving Federated Learning Using Homomorphic Encryption. Applied Sciences (Switzerland), 12(2), 734. doi:10.3390/app12020734.
Angulo, E., Márquez, J., & Villanueva-Polanco, R. (2023). Training of Classification Models via Federated Learning and Homomorphic Encryption. Sensors, 23(4), 1966. doi:10.3390/s23041966.
Brauneck, A., Schmalhorst, L., Kazemi Majdabadi, M. M., Bakhtiari, M., Völker, U., Baumbach, J., ... & Buchholtz, G. (2023). Federated machine learning, privacy-enhancing technologies, and data protection laws in medical research: Scoping review. Journal of Medical Internet Research, 25, e41588. doi:10.2196/41588.
Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121–154. doi:10.1016/j.iotcps.2023.04.003.
Alawida, M., Mejri, S., Mehmood, A., Chikhaoui, B., & Isaac Abiodun, O. (2023). A Comprehensive Study of ChatGPT: Advancements, Limitations, and Ethical Considerations in Natural Language Processing and Cybersecurity. Information (Switzerland), 14(8), 462. doi:10.3390/info14080462.
Sharma, S., Ahmed, S., Naseem, M., Alnumay, W. S., Singh, S., & Cho, G. H. (2021). A survey on applications of artificial intelligence for pre-parametric project cost and soil shear-strength estimation in construction and geotechnical engineering. Sensors (Switzerland), 21(2), 1–44. doi:10.3390/s21020463.
Al-Mushayt, O. S. (2019). Automating E-Government Services with Artificial Intelligence. IEEE Access, 7, 146821–146829. doi:10.1109/ACCESS.2019.2946204.
Benzaïd, C., & Taleb, T. (2020). AI for beyond 5G Networks: A Cyber-Security Defense or Offense Enabler? IEEE Network, 34(6), 140–147. doi:10.1109/MNET.011.2000088.
Ahmed, A., Aziz, S., Abd-Alrazaq, A., Farooq, F., Househ, M., & Sheikh, J. (2023). The Effectiveness of Wearable Devices Using Artificial Intelligence for Blood Glucose Level Forecasting or Prediction: Systematic Review. Journal of Medical Internet Research, 25, 40259. doi:10.2196/40259.
Choraś, M., & Woźniak, M. (2022). The double-edged sword of AI: Ethical Adversarial Attacks to counter artificial intelligence for crime. AI and Ethics, 2(4), 631–634. doi:10.1007/s43681-021-00113-9.
Adadi, A., & Berrada, M. (2020). Explainable AI for Healthcare: From Black Box to Interpretable Models. Advances in Intelligent Systems and Computing, 1076, 327–337. doi:10.1007/978-981-15-0947-6_31.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30, 1-11.
Xu, P., Zhu, X., & Clifton, D. A. (2023). Multimodal Learning with Transformers: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(10), 12113–12132. doi:10.1109/TPAMI.2023.3275156.
Parisi, G. I., Kemker, R., Part, J. L., Kanan, C., & Wermter, S. (2019). Continual lifelong learning with neural networks: A review. Neural Networks, 113, 54–71. doi:10.1016/j.neunet.2019.01.012.
Rahman, W., Hasan, M. K., Lee, S., Zadeh, A., Mao, C., Morency, L. P., & Hoque, E. (2020). Integrating multimodal information in large pretrained transformers. Proceedings of the Annual Meeting of the Association for Computational Linguistics, 2359–2369. doi:10.18653/v1/2020.acl-main.214.
Hendrycks, D., Burns, C., Basart, S., Zou, A., Mazeika, M., Song, D., & Steinhardt, J. (2020). Measuring massive multitask language understanding. arXiv preprint, arXiv:2009.03300. doi:10.48550/arXiv.2009.03300.
Sangwan, R. S., Badr, Y., & Srinivasan, S. M. (2023). Cybersecurity for AI Systems: A Survey. Journal of Cybersecurity and Privacy, 3(2), 166–190. doi:10.3390/jcp3020010.
Kairouz, P., McMahan, H. B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A. N., ... & Zhao, S. (2021). Advances and open problems in federated learning. Foundations and Trends® in Machine Learning, 14(1–2), 1-210. doi:10.1561/2200000083.
Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023). Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. Journal of Information Technology Case and Application Research, 25(3), 277–304. doi:10.1080/15228053.2023.2233814.
Tawfeeq, T. M., Awqati, A. J., & Jasim, Y. A. (2023). The Ethical Implications of ChatGPT AI Chatbot: A Review. Journal of Modern Computing and Engineering Research, 2023, 49–57.
Wang, P. Q. (2024). Personalizing guest experience with generative AI in the hotel industry: there's more to it than meets a Kiwi’s eye. Current Issues in Tourism, 1-18. doi:10.1080/13683500.2023.2300030.
Stahl, B. C., & Eke, D. (2024). The ethics of ChatGPT–Exploring the ethical issues of an emerging technology. International Journal of Information Management, 74, 102700. doi:10.1016/j.ijinfomgt.2023.102700.
Parra, J. L., & Chatterjee, S. (2024). Social Media and Artificial Intelligence: Critical Conversations and Where Do We Go from Here? Education Sciences, 14(1), 68. doi:10.3390/educsci14010068.
Taddeo, M., McCutcheon, T., & Floridi, L. (2019). Trusting artificial intelligence in cybersecurity is a double-edged sword. Nature Machine Intelligence, 1(12), 557–560. doi:10.1038/s42256-019-0109-1.
Escobar-Viera, C. G., Porta, G., Coulter, R. W., Martina, J., Goldbach, J., & Rollman, B. L. (2023). A chatbot-delivered intervention for optimizing social media use and reducing perceived isolation among rural-living LGBTQ+ youth: Development, acceptability, usability, satisfaction, and utility. Internet Interventions, 34, 100668. doi:10.1016/j.invent.2023.100668.
Tsai, W. H. S., & Chuan, C. H. (2023). Humanizing Chatbots for Interactive Marketing. The Palgrave Handbook of Interactive Marketing, Springer International Publishing, 255–273. doi:10.1007/978-3-031-14961-0_12.
Kajtazi, M., Holmberg, N., & Sarker, S. (2023). The changing nature of teaching future IS professionals in the era of generative AI. Journal of Information Technology Case and Application Research, 25(4), 415–422. doi:10.1080/15228053.2023.2267330.
Gupta, M., Akiri, C., Aryal, K., Parker, E., & Praharaj, L. (2023). From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy. IEEE Access, 11, 80218–80245. doi:10.1109/ACCESS.2023.3300381.
DOI: 10.28991/HIJ-2024-05-01-010
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Albandari Alsumayt, Zeyad M. Alfawaer, Nahla El-Haggar, Majid Alshammari, Fatemah H. Alghamedy, Sumayh S. Aljameel, Dina A. Alabbad, May Issa Aldossary