Balancing Password Security and User Convenience: Exploring the Potential of Prompt Models for Password Generation
With the increasing prevalence of cyber attacks and data breaches, the importance of strong passwords cannot be overstated. Password generating software has been widely used to generate complex passwords that are difficult to crack, but it has its limitations. One of the main problems with this kind...
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Veröffentlicht in: | Electronics (Basel) 2023-05, Vol.12 (10), p.2159 |
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description | With the increasing prevalence of cyber attacks and data breaches, the importance of strong passwords cannot be overstated. Password generating software has been widely used to generate complex passwords that are difficult to crack, but it has its limitations. One of the main problems with this kind of software is that it often generates passwords that are difficult to remember, leading to users write them down or reuse them across multiple accounts. In recent years, prompt models such as ChatGPT have emerged as a promising solution for generating strong and memorable passwords. By leveraging machine learning algorithms, these models can generate unique and complex passwords tailored to individual users’ preferences, making them easier to remember and more secure. However, the use of prompt models to generate passwords also raises concerns about exposing vulnerable passwords. Hackers can potentially use these models to predict passwords by analyzing a user’s online activity and personal data. Additionally, the constant need to change passwords to stay secure poses a challenge for both password generating software and prompt models. As technology continues to evolve, finding a balance between password security and user convenience remains a complex issue. While prompt models such as ChatGPT can offer a promising solution, it is essential to consider the potential risks and challenges associated with their use, including the constant need for password changes and the potential vulnerability of the generated passwords. |
doi_str_mv | 10.3390/electronics12102159 |
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Password generating software has been widely used to generate complex passwords that are difficult to crack, but it has its limitations. One of the main problems with this kind of software is that it often generates passwords that are difficult to remember, leading to users write them down or reuse them across multiple accounts. In recent years, prompt models such as ChatGPT have emerged as a promising solution for generating strong and memorable passwords. By leveraging machine learning algorithms, these models can generate unique and complex passwords tailored to individual users’ preferences, making them easier to remember and more secure. However, the use of prompt models to generate passwords also raises concerns about exposing vulnerable passwords. Hackers can potentially use these models to predict passwords by analyzing a user’s online activity and personal data. Additionally, the constant need to change passwords to stay secure poses a challenge for both password generating software and prompt models. As technology continues to evolve, finding a balance between password security and user convenience remains a complex issue. While prompt models such as ChatGPT can offer a promising solution, it is essential to consider the potential risks and challenges associated with their use, including the constant need for password changes and the potential vulnerability of the generated passwords.</description><identifier>ISSN: 2079-9292</identifier><identifier>EISSN: 2079-9292</identifier><identifier>DOI: 10.3390/electronics12102159</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Access control (Computers) ; Algorithms ; Chatbots ; Cybersecurity ; Cyberterrorism ; Data mining ; Datasets ; Keyboards ; Machine learning ; Methods ; Neural networks ; Passwords ; Personal information ; Prevention ; Social networks ; Software ; Usability ; User behavior</subject><ispartof>Electronics (Basel), 2023-05, Vol.12 (10), p.2159</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. 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Password generating software has been widely used to generate complex passwords that are difficult to crack, but it has its limitations. One of the main problems with this kind of software is that it often generates passwords that are difficult to remember, leading to users write them down or reuse them across multiple accounts. In recent years, prompt models such as ChatGPT have emerged as a promising solution for generating strong and memorable passwords. By leveraging machine learning algorithms, these models can generate unique and complex passwords tailored to individual users’ preferences, making them easier to remember and more secure. However, the use of prompt models to generate passwords also raises concerns about exposing vulnerable passwords. Hackers can potentially use these models to predict passwords by analyzing a user’s online activity and personal data. Additionally, the constant need to change passwords to stay secure poses a challenge for both password generating software and prompt models. As technology continues to evolve, finding a balance between password security and user convenience remains a complex issue. 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Password generating software has been widely used to generate complex passwords that are difficult to crack, but it has its limitations. One of the main problems with this kind of software is that it often generates passwords that are difficult to remember, leading to users write them down or reuse them across multiple accounts. In recent years, prompt models such as ChatGPT have emerged as a promising solution for generating strong and memorable passwords. By leveraging machine learning algorithms, these models can generate unique and complex passwords tailored to individual users’ preferences, making them easier to remember and more secure. However, the use of prompt models to generate passwords also raises concerns about exposing vulnerable passwords. Hackers can potentially use these models to predict passwords by analyzing a user’s online activity and personal data. Additionally, the constant need to change passwords to stay secure poses a challenge for both password generating software and prompt models. As technology continues to evolve, finding a balance between password security and user convenience remains a complex issue. While prompt models such as ChatGPT can offer a promising solution, it is essential to consider the potential risks and challenges associated with their use, including the constant need for password changes and the potential vulnerability of the generated passwords.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/electronics12102159</doi><oa>free_for_read</oa></addata></record> |
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source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; MDPI - Multidisciplinary Digital Publishing Institute |
subjects | Access control (Computers) Algorithms Chatbots Cybersecurity Cyberterrorism Data mining Datasets Keyboards Machine learning Methods Neural networks Passwords Personal information Prevention Social networks Software Usability User behavior |
title | Balancing Password Security and User Convenience: Exploring the Potential of Prompt Models for Password Generation |
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