Volume 10, Issue 6 - IJIRTM
November - December (2026)
Impact Factor: 5.86 | Volume 10 | Issue 6
VIGILIS: A Lightweight Compliance Framework for Organizational Management
👥 Rahul, Sakshi, Ms.Anju Arya
📙 Abstract : In most small and mid-sized organisations, compliance work is still done in spreadsheets. Controls get updated when somebody remembers to do it, risks sit in a register with no owner attached, and vendor audit dates pass by quietly until someone notices months later. Commercial GRC platforms deal with all of this, but their pricing and the effort needed to set them up puts them out of reach for smaller teams, college groups included. This paper looks at how GRC is currently handled by different tools and then presents Vigilis, a lightweight self-hosted dashboard we are developing that sits somewhere between a spreadsheet and an enterprise suite. Vigilis tracks controls against ISO/IEC 27001 and the NIST Cybersecurity Framework, scores risks using a 5 × 5 Likelihood × Impact grid, and runs a small rule engine that points out stale controls, high risks with no owner, risks that have stayed open too long, and overdue vendor audits. Beyond that it offers a Compliance Debt Score, impact and what-if simulation, cross-framework mapping, an audit trail, and one-click PDF reports. Since Vigilis is still under development, the paper compares its design with existing approaches and does not report experimental results.
🔖 Keywords :️ Governance, risk and compliance (GRC); ISO/IEC 27001; NIST CSF; risk scoring; rule engine; compliance monitoring.
A Review of Lightweight Vulnerability Assessment Tools and Their Role in Supporting Cyber security and GRC Workflows
👥 Sapna, Palak, Prof.Vaishali Mehta
📙 Abstract : Organizations frequently run vulnerability assessments first to discover network exposures and potential known weaknesses. Gathering this data has become straightforward thanks to tools like Nmap alongside public databases such as the National Vulnerability Database (NVD). Manual effort remains the tougher obstacle, involving the interpretation of scan results, validation of suspected flaws, and creation of standardized reports. This study examines lightweight vulnerability assessment tools together with their underlying standards and data sources, specifically focusing on network scanners, vulnerability databases, severity scoring systems, and reporting workflows. We also outline a basic prototype developed using Python, Streamlit, Nmap, and the NVD Common Vulnerabilities and Exposures (CVE) API, exploring its potential support for governance, risk and compliance (GRC) tasks. Four major shortcomings emerge: incomplete version detection, inaccurate or uncertain vulnerability matches, limited risk insight from severity scores alone, and a frequent lack of connection between technical findings and remediation. Ultimately, lightweight tools help reduce documentation overhead and improve reporting consistency, provided operators treat their output as provisional findings requiring careful human review.
🔖 Keywords :️ Cyber security, GRC, network scanning, vulnerability assessment, vulnerability reporting.
Extended Detection and Response (XDR): A Review of Concepts, Architectures, Capabilities, and Open Challenges
👥 Jigyansh, Vikram Pawar, Dr.Shakti Arora
📙 Abstract : Since its emergence in the late 2010s, Extended Detection and Response (XDR) has been one of the most important categories in security operations. It offers the promise of unifying endpoint, network, identity, email, and cloud workload telemetry, correlating it into coherent incidents and enabling coordinated response. This paper covers the origins and definitions of XDR, its reference architecture, the native, open and hybrid deployment models, its relationship to EDR, SIEM, SOAR and MDR, the role of machine learning and agentic AI, and the main obstacles to adoption including data management cost, correlation quality, vendor lock-in and definitional ambiguity.
🔖 Keywords :️ Extended Detection and Response, XDR, EDR, SIEM, SOAR, security operations, Agentic AI.
Trust X: A Blockchain-Backed, Context-Aware Platform for Identity Access Control and Digital Asset Management – Literature Review and System
👥 Sagar, Harsh Ruhal, Nisha Sharma
📙 Abstract : Organizations now keep confidential reports, academic records and business files as digital assets, and most guard them with a centralized database, role-based permissions and ordinary application logs. This arrangement is simple, but it struggles when an access decision depends on the sensitivity of the asset, the requested operation, the time or the device, and its audit records can be altered by anyone who controls the logging system. This paper reviews the literature on access control, zero-trust security, blockchain-based authorization and identity, encrypted off-chain storage and tamper-evident auditing, and describes the design of Trust X, a blockchain-backed, context-aware digital asset management platform. Trust X is a web application built with React, Express and Prisma that is intended to run on ordinary student hardware. It decides every protected request in a deterministic policy engine that returns ALLOW, STEP-UP or DENY, encrypts each file with AES-256-GCM before storing it off-chain, checks SHA-256 digests for each asset version, chains audit events by hash, and anchors Merkle roots and version records through a Solidity smart contract, with a local-ledger fallback. Drawing on thirty-four sources covering access-control models, standards, blockchain surveys, cryptographic primitives and smart-contract security, the paper sets out the architecture, the planned evaluation, the development schedule and the safeguards of the platform, and compares Trust X with existing categories of systems. Trust X is presented as an academic prototype, and its performance and security claims remain to be demonstrated through the planned evaluation.
🔖 Keywords :️ Blockchain, Identity Access Control, Digital Asset Management, Zero Trust, Context-Aware Authorization, RBAC, ABAC, Smart Contracts, AES-256-GCM, Data Integrity, Audit Logging.