Skip to content
Log in

Author

Nazmus Sakib

View on Semantic Scholar

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Conference Aug 2026

Enhancing AD/ADRD Management Through iHelpCare: A Compliant and Culturally Sensitive AI-Driven Digital Healthcare Platform

The digital healthcare field is expanding fast, and now it requires platforms that use advanced technology and maintain robust data security and compliance practices. In this paper, we present the main architecture, key methodologies, and compliance strategies of iHelpCare, a digital healthcare system designed to meet HIPAA and GDPR standards while improving healthcare accessibility, efficiency, and inclusivity. The platform uses AI-based features to deliver personalized care solutions, focuses on preventive health management, and offers adaptive tools for people with disabilities. iHelpCare enables real-time patient monitoring, ensures secure medical data management, and facilitates convenient communication among patients, caregivers, and healthcare providers. Moreover, special attention is provided to people with Alzheimer’s through memory aid tools, cognitive exercises, caregiver resources, and AI-based detection analytics. All these characteristics are intended to detect cognitive decline at an early stage, enabling prompt interventions and improving patients’ quality of life. Also, iHelpCare considers unique health needs by providing access to culturally appropriate healthcare materials, telehealth consultations in multiple languages, and community support networks, making healthcare easier and more effective for this community. The platform’s AI analytics provide predictive insights that help medical professionals anticipate health conditions, optimize treatment plans, and reduce caregiver burden. To improve accessibility, features such as voice command, screen reader, and gesture recognition are included to help users with cognitive and physical disabilities. iHelpCare is envisioned to evolve through advanced sensor integration, personalized and inclusive care models, enhanced security, smart home support, and clinically validated tools for patients and caregivers.

Soarov Chakra Borty, Trisha Bhowmick, Mehedi Hasan et al. · 0 citations
Review Jul 2026

Trust but Verify? Uncovering the Security Debt of Autonomous Coding Agents

The increasing adoption of autonomous coding agents accelerates software development but also introduces scoped security risks within high-impact file paths that can outpace traditional human review capacity. While prior research has primarily evaluated these systems in terms of functional correctness and productivity, this paper presents a large-scale empirical study using the AIDev dataset to systematically characterize security code smells in agent-generated pull requests (PRs). Through a combination of a validated LLM-as-a-judge framework and manual qualitative analysis, we identify and classify security misconfigurations across 16,112 file changes spanning 4,022 pull requests. Our results reveal that 38.9% of agent-generated PRs contain at least one security smell, with supply chain integrity issues accounting for 82.3% of all detected security smells. Furthermore, hard-coded credentials constitute 99.6% of all critical-severity security smells. Crucially, we find that human collaborators are responsible for introducing 67.6% of genuine leaked secrets within these agent-assisted workflows, while existing automated and human review processes fail to detect 81.1% of these credentials prior to integration. These findings highlight substantial security risks in agent-assisted software development workflows and suggest a potential reduction in developer vigilance. They also underscore the urgent need for context-aware security guardrails implemented directly at the point of human-AI collaboration.

Nazmus Sakib, Dipayan Banik, Murtuza Jadliwala · 0 citations