[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119602-en":3,"doc-seo-119602-105":30,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119602,1099514068365,"Aurelia","https://ap-avatar.wpscdn.com/avatar/10000253d8d9f28188e?_k=1776742907772140068",7,"Healthcare","Security Hardening of Pharmacy Information System Against Machine Learning Attack - Alumni Series","A pharmacy information system (PIS) is presented as a specialized software platform that supports pharmacy operations including dispensing, inventory, patient data handling, billing, and administrative functions. The material outlines how to harden such a system against machine learning attacks by protecting sensitive data with strong encryption and access controls, securing model development with safe coding and timely patching, improving training quality, and adding defenses such as adversarial robustness, validation testing, monitoring with anomaly detection, and strong authentication. It also emphasizes ongoing updates and security awareness training.","ALUMNI SERIES  \nSecurity Hardening of Pharmacy Information System Against Machine Learning Attack  \nA pharmacy information system ( PIS) is a specialised software application designed to support and manage the operations of a pharmacy or a pharmacy department within a healthcare organisation. It is a comprehensive solution that automates various tasks and processes involved in pharmacy management, including medication dispensing, inventory management, patient data management, billing and invoicing, and other administrative functions. The P IS streamlines pharmacy workflows, reduces medication errors, improves efficiency, and enhances patient safety. They play a vital role in supporting the day-to-day operations of pharmacies, ensuring accurate dispensing of medications, and maintaining proper medication management practises.  \nWhen it comes to securing a PIS against machine learning attacks, there are several steps that the users can take to enhance its security. Machine learning attacks typically involve exploiting vulnerabilities in the system to manipulate or compromise the machine learning models. Here are some security hardening measures for the users to consider:  \n1. Data Protection:  \n Ensure that sensitive patient and prescription data is stored securely using strong encryption techniques.  \n Implement access controls to restrict data access based on user roles and privileges.  \n Regularly backup the data and store it securely to prevent data loss or corruption.  \n2. Secure Model Development:  \n Follow secure coding practises when developing machine learning models to prevent common vulnerabilities such as injection attacks or buffer overflows.  \n Regularly update and patch the machine learning frameworks and libraries to address any security vulnerabilities discovered.  \n3. Robust Model Training:  \n Use quality, diverse, and representative data for training the machine learning models. This helps prevent biassed models that could lead to discriminatory or unfair outcomes.  \n Regularly retrain the models to incorporate new data and address concept drift, ensuring the models are up-to-date and accurate.  \n4. Adversarial Robustness:  \n Consider implementing techniques to detect and defend against adversarial attacks, where an attacker intentionally manipulates inputs to deceive the machine learning models.  \n Techniques like adversarial training, input sanitization, or anomaly detection can help improve the resilience of the models against such attacks.  \n5. Model Validation and Testing:  \n Perform rigorous testing and validation of the models to ensure their effectiveness and security.  \n Conduct penetration testing and vulnerability assessments to identify and address any weaknesses in the system.  \n6. Monitoring and Anomaly Detection:  \n Implement monitoring and logging mechanisms to detect unusual or suspicious activities within the P IS.  \n Utilise anomaly detection techniques to identify potential attacks or abnormalities in the system's behaviour.  \n7. User Authentication and Access Control:  \n Enforce strong user authentication mechanisms, such as multi-factor authentication, to prevent unauthorised access.  \n Implement role-based access controls to ensure that users only have access to the information and functionality they require.  \n8. Security Awareness and Training:  \n Educate system users, administrators, and developers about machine learning security best practices, potential threats, and common attack vectors.  \n Foster a culture of security awareness to ensure that everyone involved in the system understands their role in maintaining its security.  \nRemember that security is an ongoing process, and it is important to stay updated with the latest security practises, vulnerabilities, and defence techniques. Regularly review and update your security measures to address emerging threats and protect your PIS effectively.  \nMr. Mohd Ghazali Ismail RX2 Alumni  \nLatest news and updates from the Faculty of Pharm","cbCaieepMDkeroBW","https://ap.wps.com/l/cbCaieepMDkeroBW","pdf",1370913,1,3,"English","en",105,"# Security Hardening Measures for PIS Against Machine Learning Attacks\n## Data Protection\n## Secure Model Development\n## Robust Model Training\n## Adversarial Robustness\n## Model Validation and Testing\n## Monitoring and Anomaly Detection\n## User Authentication and Access Control\n## Security Awareness and Training","[{\"question\":\"What is a pharmacy information system (PIS) and what functions does it support?\",\"answer\":\"A PIS is specialized software that automates pharmacy operations such as medication dispensing, inventory management, patient data management, billing and invoicing, and other administrative tasks.\"},{\"question\":\"How can sensitive patient and prescription data be protected in a PIS?\",\"answer\":\"Use strong encryption to store sensitive data, implement role-based access controls, and perform regular secure backups to prevent loss or corruption.\"},{\"question\":\"What measures help defend machine learning models in the PIS against attacks?\",\"answer\":\"Adopt secure model development practices, update and patch ML frameworks, train models with quality representative data, apply adversarial robustness techniques, and perform rigorous validation and testing including penetration assessments.\"}]","Security Hardening of Pharmacy Information System Against Machine Learning Attack - 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