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@article{186166,
        author = {Yash Sushil Zope and Vishal Natha Sukale and Yash Sandip Kakade and Khushi Arvind Tiwari and Prof. Saba Chaugule},
        title = {AI Driven Control Mapping And Evidence Analyzer},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {1854-1857},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186166},
        abstract = {Managing information security is getting harder every year. With standards like ISO/IEC 27001 and SOC 2 raising the bar, manual control mapping and evidence checks just can’t keep up—they’re slow, messy, and honestly, a pain for everyone involved. Our research brings something new to the table: an AI-powered Control Mapping and Evidence Analyzer. It uses AI, Natural Language Processing (NLP), and Machine Learning (ML) to handle compliance checks and audit prep automatically. Here’s how it works. The system relies on semantic embeddings, LangChain-powered retrieval-augmented generation (RAG), and FAISS vector search to connect company policies and evidence to the right ISMS controls. We built the backend on Django and MySQL to handle the AI workflows and evidence data. On the frontend, a React dashboard gives you real-time updates and clear reports about compliance. This setup slashes the manual work, boosts how accurately controls get mapped, and lets organizations keep tabs on compliance at all times. Our tests show the AI-driven mapping nails control-policy matches with up to 87% accuracy and cuts audit prep time by 65%. In short, this system gives the whole compliance process a much-needed upgrade and fits right in with ISO/IEC 27001:2022 goals.},
        keywords = {Artificial Intelligence (AI), Compliance Automation, Control Mapping, Evidence Analyzer, FAISS (Facebook AI Similarity Search), Governance, Risk, and Compliance (GRC), ISO/IEC 27001 (ISMS), LangChain, Machine Learning (ML), Natural Language Processing (NLP), SOC 2, Semantic Search.},
        month = {November},
        }