International Conference on Artificial Intelligence and Cybersecurity

ASHRAF SYED Profile

ASHRAF SYED

ASHRAF SYED

Biography

  • Over 14 years of extensive experience as an Oracle APEX developer, delivering scalable, secure web applications.
  • Proficient in analysis, development, and maintenance of business applications using Oracle 12c/11g/10g, PL/SQL Developer, Oracle APEX 3.2?24.2, Application Server, and web tools.
  • Expert in Oracle database programming using PL/SQL (Stored Procedures, Functions, Packages, Triggers), built-in Oracle packages, and UNIX environments.
  • Skilled in managing schema objects (Tables, Global Temporary Tables, Views, Materialized Views, Constraints, Indexes, Packages, Procedures, Functions, Triggers, Synonyms, Sequences, DB Links, Types), with expertise in Bulk Collects/Inserts, Analytical Functions, Dynamic SQL, Exception Handling, and XMLTYPE.
  • Advanced skills in web application tools, including APEX, HTML-DB, Oracle Developer Suite (Forms/Reports 6i?10g), HTML5, CSS3, JavaScript, jQuery, AJAX.
  • Extensive experience in REST and SOAP Web Services, leveraging Oracle APEX APIs, REST Data Sources, Web Source Modules, and Web Service References for seamless integrations.
  • Developed several stopgap solutions, including custom forms and reports using REST-enabled SQL and Web Service APIs for ERP integrations (e.g., Oracle EBS).
  • Using Oracle APEX framework, created several REST APIs with types of parameters for GET, POST, PUT, DELETE, PATCH methods.
  • Implemented several APEX workflows streamlining complex business processes. 
  • Extensive experience in creating interactive dashboards for senior management using Bar, Line, Bubble, Gantt, Pie, Pyramid, and Combination Charts, enhanced with APEX 24.2?s advanced visualization options.
  • Designed diverse forms and reports, including Master-Detail Reports, Forms on Tables, Multi-Table Custom Forms, Tabular Forms, Editable Interactive Reports, Interactive Grids, and Classic SQL Reports.
  • Leveraged Oracle APEX 24.2 features, including enhanced Faceted Search with dynamic facets, improved Interactive Grid capabilities for inline editing, and advanced REST Data Source synchronization for real-time data updates.
  • Implemented Progressive Web Apps (PWAs) in APEX 24.2, enabling offline capabilities, push notifications, and mobile-optimized user experiences.
  • Utilized APEX 24.2?s Smart Filters and enhanced Card Regions to deliver intuitive, user-driven data exploration and visualization.
  • Configured and managed Oracle APEX Redwood Theme and Universal Theme enhancements in APEX 24.2 for modern, responsive UI designs.
  • Experienced in installing and upgrading Oracle APEX instances on Oracle databases, ensuring compatibility and performance optimization.
  • Proficient in deploying and managing Apache Tomcat instances on Linux servers for hosting APEX applications.
  • Customized Oracle APEX team-recommended and Google Plugins to meet complex business requirements.
  • Implemented robust security using SSO, LDAP, and custom authentications, with user-level access authorization schemes across APEX objects.
  • Strong knowledge of data dictionary views, tablespaces, data files, users, profiles, backup/recovery procedures, and database performance tuning.
  • Expert in performance tuning using Hints, Partitioning, Indexes, Explain Plans, and AWR report analysis.
  • Served as Lead and Subject Matter Expert (SME) in multiple projects, driving successful outcomes.
  • Provided team leadership, mentoring, and training to enhance developer productivity and code quality.
  • Excellent communication and interpersonal skills, thriving in both individual and collaborative team environments.

Research Interest

Dynamic Risk-Based Authentication Using AI Scoring Models in Healthcare Applications

Abstract

As digital healthcare systems grow increasingly complex and globally interconnected, safeguarding patient data while ensuring seamless access has become a critical challenge. Traditional authentication methods, such as static passwords and inflexible multi-factor authentication (MFA), often fail to provide context-aware security without disrupting usability. This paper presents a novel Dynamic Risk-Based Authentication (RBA) framework that integrates AI-powered risk scoring into a healthcare application developed on the Oracle APEX 24.2 low-code platform. The proposed solution evaluates real-time contextual data such as device fingerprinting, geolocation, behavioral history, and temporal patterns during each login attempt. This data is transmitted to an OpenAI-powered inference engine via RESTful APIs, which returns a normalized risk score. Depending on the risk classification (low, medium, or high), the application dynamically adjusts authentication mechanisms?ranging from seamless login to OTP verification or full access denial. This approach demonstrated a 35% reduction in false positives and effectively blocked 92% of high-risk login attempts in pilot studies conducted within healthcare domains. The architecture also includes adaptive learning feedback loops, enabling model refinement over time. Designed for regulatory compliance (HIPAA, GDPR) and operational scalability, this AI-RBA framework demonstrates that low-code platforms can deliver enterprise-grade, context-sensitive cybersecurity solutions. This research contributes a scalable, cross-domain authentication paradigm that enhances both data security and user experience, addressing a key challenge in AI-enhanced cybersecurity systems. Keywords Risk-Based Authentication (RBA); Oracle APEX; AI Risk Scoring; OpenAI GPT-4; Healthcare Cybersecurity; Low-Code Security; Dynamic Authentication; REST API Integration; Behavioral Biometrics; Federated Learning; Compliance (HIPAA/GDPR); Adaptive MFA.