http://hdl.handle.net/123456789/17506 2026-04-04T12:27:50Z 2026-04-04T12:27:50Z 03-243222-001, AMNA FAISAL http://hdl.handle.net/123456789/20011 2025-10-21T14:11:20Z 2025-11-01T00:00:00Z

HUMAN CENTERED DESIGN AND EVALUATION OF AI APPLICATIONS IN MEDICAL HEALTH 03-243222-001, AMNA FAISAL Through this research study, the study aims to facilitate AI-based medical health applications both local and international, more accessible and useable to semi-literate users of Pakistan. At the initial stage, systematic literature review (SLR) identified critical factors regarding AI-based medical health applications and semiliterate users. Twelve factors are identified within three categories: Usability, User Experience, and Content & Design. These factors included Ease of Navigation, Memorability, Learnability, Efficiency, Effectiveness, Accessibility, User Satisfaction, Interactivity, Readability, Ease of Use, Content, and Design. MCDM techniques like AHP and Fuzzy AHP are applied to prioritize the factors. From the results, the top six significant factors are selected for further analysis; these are Ease of Navigation, Learnability, Effectiveness, User Satisfaction, Memorability, and Readability. Then, a further SLR is conducted for choosing applications, which include ratings from the application, downloaded statistics, presence of AI features, and user reviews. Next, two validation methods are applied for this research. First, we will consider the match of 10 selected AI-based health applications to prioritized factors with expert assistance using the Google Form survey. Applications in compliance with these factors are further selected for the next method: heuristic evaluation. With this heuristic evaluation, experts draw attention to several usability issues and provide recommendations to enhance the applications' usability. Among the selected three applications that are WebMD, Healthwire, and Dawaai, least user experiences were satisfied through these applications, and for this reason, they are selected in the next phase of heuristic evaluation. A prototype is created with the feedback, which included all the changes it planned to make based on the issues. The same experts reviewed this prototype to check whether the new design met their expectations and whether they fully agreed with the proposed improvements. This iterative process highlights a need for AI-based health applications to be culturally sensitive and accessible, especially for semi-literate users in Pakistan. The research focuses on critical usability factors and iterates the design based on expert feedback. The improvement achieved is in terms of usability, user experience, and accessibility of AI-based health applications to cater to diverse populations more effectively. Dr. Abdul Hafeez

2025-11-01T00:00:00Z 03-243222-05, Hafiz Muhammad Ashja Khan http://hdl.handle.net/123456789/20015 2025-10-23T13:20:02Z 2024-11-01T00:00:00Z

TRUSTED SIMPLE NETWORK MANAGEMENT PROTOCOL FOR INTEGRITY EVALUATION IN DISTRIBUTED ENVIRONMENT 03-243222-05, Hafiz Muhammad Ashja Khan As computer technology continues to advance, the imperative for enhanced security and privacy for users becomes increasingly pronounced. A multitude of individuals are interconnected with networks in various ways, be it through mobile phones, online banking, ATM transactions, email communication, social networking, and more. With technology's pervasive integration into our daily lives, users face mounting security risks, particularly concerning the confidentiality, integrity, and accessibility of their data. Despite the myriad solutions proposed by researchers to shield user information from unauthorized access and ensure their security, grappling with these security challenges remains an arduous endeavor. In an era of rapid technological evolution, the Trusted Computing Group (TCG) has taken the lead in developing security specifications aligned with international standards for various industries. Among its notable contributions is the creation of the Trusted Platform Module (TPM), a security chip that incorporates cryptographic techniques within hardware to instill trust in computing systems. TPM functions as a specialized cryptographic processor meticulously designed to bolster system security. At its core, TPM serves the pivotal role of guaranteeing the integrity of a system. The foundation of trust is established from the moment of power-on boot, often referred to as the "core of assurance." Security-relevant gauges are securely stored in Platform Configuration Registers (PCRs), diligently monitoring, reporting any deviations from previous configurations. These reports inform decisions on how to proceed, ensuring that both users and applications running on the system can have unwavering confidence in its security. While we say the TPM checks the integrity of the individual node and their no such way to check the integrity of whole system and we have proposed that the solution is designed to centrally report the rectitude status of every system in the network. It involves extending the Simple Network Management Protocol (SNMP) to get integrity information from all network nodes and clients, along with other relevant status data and report to the administrator. A specific Object ID within the SNMP Management Information Base (MIB) has been designated to link the necessary rectitude information acquired through TPM PCR_QUOTE. This information is subsequently transmitted to the administrator in response to an SNMP GET. On the server side, the received PCR_QUOTE data is compared to the stored values representing both beneficial and harmful conditions. The proposed architecture the Simple Network Management Protocol securely gathering the integrity data of every node. Since SNMP is an open-source protocol, in this study we expand its functionality by reserving an Object Identifier (OID) to associate the extracted hash of integrity measurement. The study shows that it does not compromise the performance or integrity of the system or SNMP. Overall the proposed extended SNMP model offers a robust solution for trusted and secure network management with minimal performance impact.

2024-11-01T00:00:00Z 03-243222-001, Amna Faisal http://hdl.handle.net/123456789/20888 2026-03-06T04:40:21Z 2024-11-01T00:00:00Z

Human Centered Design and Evaluation of AI Application in Medical Health 03-243222-001, Amna Faisal Through this research study, the study aims to facilitate AI-based medical health applications both local and international, more accessible and useable to semi-literate users of Pakistan. At the initial stage, systematic literature review (SLR) identified critical factors regarding AI-based medical health applications and semiliterate users. Twelve factors are identified within three categories: Usability, User Experience, and Content & Design. These factors included Ease of Navigation, Memorability, Learnability, Efficiency, Effectiveness, Accessibility, User Satisfaction, Interactivity, Readability, Ease of Use, Content, and Design. MCDM techniques like AHP and Fuzzy AHP are applied to prioritize the factors. From the results, the top six significant factors are selected for further analysis; these are Ease of Navigation, Learnability, Effectiveness, User Satisfaction, Memorability, and Readability. Then, a further SLR is conducted for choosing applications, which include ratings from the application, downloaded statistics, presence of AI features, and user reviews. Next, two validation methods are applied for this research. First, we will consider the match of 10 selected AI-based health applications to prioritized factors with expert assistance using the Google Form survey. Applications in compliance with these factors are further selected for the next method: heuristic evaluation. With this heuristic evaluation, experts draw attention to several usability issues and provide recommendations to enhance the applications' usability. Among the selected three applications that are WebMD, Healthwire, and Dawaai, least user experiences were satisfied through these applications, and for this reason, they are selected in the next phase of heuristic evaluation. A prototype is created with the feedback, which included all the changes it planned to make based on the issues. The same experts reviewed this prototype to check whether the new design met their expectations and whether they fully agreed with the proposed improvements. This iterative process highlights a need for AI-based health applications to be culturally sensitive and accessible, especially for semi-literate users in Pakistan. The research focuses on critical usability factors and iterates the design based on expert feedback. The improvement achieved is in terms of usability, user experience, and accessibility of AI-based health applications to cater to diverse populations more effectively. Dr. Abdul Hafeez

2024-11-01T00:00:00Z 03-243222-011, MUHAMMAD HAMZA WASEEM http://hdl.handle.net/123456789/20008 2025-10-21T13:50:16Z 2024-10-24T00:00:00Z

SECURE DATA STORAGE ON CLOUD PLATFORM USING ENCRYPTION STANDARD 03-243222-011, MUHAMMAD HAMZA WASEEM Data security has emerged as the most significant area of study in recent years. Data security provides monitoring and protecting very sensitive data in cloud apps to enable cloud-based platforms. However, the organization is unable to use Cloud services because of an increasing problem with data security and privacy. The current privacy-preserving techniques had a number of flaws, including complete reliance on third parties, make a deficiency in performance efficiency, accurate data analysis, and data privacy. The Enhanced Triple Layers Data Encryption method is proposed to secure large amounts of data efficiently in the Cloud environment to address this problem. By raising the length of the keys in data encryption standards that is AES, the proposed Enhanced Triple Layers Data Encryption Standard approach offers a very simple solution to fend off inefficiency and maintain the privacy of data. Huge amounts of data will be effectively secured and kept private using the suggested strategy, especially in a cloud context. Comparing the suggested methodology to the current Triple DES (TDES) method, it was found that encryption and decryption took less execution time, and these are our main objectives. Also using proposed process where encryption and decryption works efficiently, network usage and CPU usage work very well compared to existing techniques. The suggested Triple Layer Encryption system execute in our tests on given dataset in just 4.9850 seconds, encryption duration of 0.3181 seconds, decryption time of 0.6556 seconds attained by our suggested method was much quicker than the existing systems. Our suggested solution surpasses TDES under the identical conditions, with a throughput of 0.2473 MBps. Our suggested solution utilises 1.9% of CPU resources, compared to 33% for TDES on same dataset. The effectiveness of our suggested system in managing data transfers is demonstrated by its 2.5003 second upload time and 0.9175 second download time. Our method is able to upload and download data fast without sacrificing security is a big benefit in applications where encrypted data has to be safely exchanged. Dr. Nadeem Sarwar

2024-10-24T00:00:00Z