Project Ideas for Fall 2024

 Here are some team project ideas. I expect my students to improve these ideas further.

AI-Driven Endpoint Security for BYOD (Bring Your Own Device) Environments

• Objective: Create a cybersecurity solution that uses AI to monitor and secure devices in a BYOD environment, detecting and mitigating potential risks caused by non-corporate devices accessing the network.
• Novelty: Implement a system that learns from device behavior, network usage, and data access patterns to recommend customized security measures or quarantine devices when suspicious activity is detected.
• Enterprise Use: Ensures security while allowing flexibility for employees using personal devices, especially in hybrid work models.

AI-Driven Identity and Access Management (IAM) System

• Objective: Develop an AI-powered platform that automates identity and access management by analyzing employee roles, data access patterns, and anomalies to recommend optimal access controls.
• Novelty: The system could predict and recommend least-privilege access policies based on AI insights, reducing the risk of excessive access permissions while balancing productivity.
• Enterprise Use: Enhances enterprise security by minimizing access-based risks and improving compliance with regulatory frameworks.

AI-Driven Employee Wellness and Productivity Tracker

• Objective: Build an AI-based platform that tracks employee productivity metrics (e.g., project completion rates, time spent on tasks) and correlates them with wellness data (e.g., stress levels, absenteeism, survey responses).
• Novelty: The platform should suggest personalized interventions (break times, counseling) and productivity boosters using AI models trained on behavioral data.
• Enterprise Use: Improves employee well-being and enhances productivity across teams.

AI-Enabled Enterprise Document Summarizer

• Objective: Create an AI platform that automatically summarizes lengthy enterprise documents (such as meeting notes, reports, and contracts) into concise, actionable insights using NLP techniques.
• Novelty: Integrate the summarizer with enterprise chatbots, allowing employees to query the system for real-time, contextual document summaries and quick answers.
• Enterprise Use: Improves efficiency in handling large volumes of information in daily operations.

Enterprise Expense Fraud Detection System

• Objective: Develop a platform that uses AI and anomaly detection techniques to flag fraudulent or unusual employee expenses in an organization.
• Novelty: The system should learn from employee spending patterns, detect outliers, and also provide insights into common fraud patterns across departments or locations.
• Enterprise Use: Reduces risk and enhances financial integrity.

AI-Driven Talent Acquisition and Retention Tool

• Objective: Develop a tool that uses AI to analyze patterns in employee recruitment and retention. The tool should predict which candidates are likely to succeed and stay longer in the organization based on data from resumes, interviews, and performance reviews.
• Novelty: The platform should continuously improve its model by considering industry trends, skill shortages, and company-specific needs.
• Enterprise Use: Helps HR departments in making better hiring and retention decisions.

AI-Powered Insider Threat Detection System

• Objective: Develop an AI-driven platform that monitors employee activity to detect potential insider threats based on behavior patterns, communication anomalies, and unusual system access.
• Novelty: Include predictive analytics to forecast potential insider threats before they occur, based on changes in employee sentiment or workload (e.g., using sentiment analysis from internal communications).
• Enterprise Use: Prevents data breaches and intellectual property theft caused by internal actors.

Data-Driven Cybersecurity Risk Scoring for Enterprises

• Objective: Develop a platform that calculates a dynamic cybersecurity risk score for an enterprise by analyzing system vulnerabilities, threat intelligence feeds, and employee behaviors.
• Novelty: Integrate external data sources such as social media and dark web activity to provide predictive risk scoring, identifying potential upcoming attacks based on public information leaks or discussions.
• Enterprise Use: Helps organizations prioritize security resources by focusing on high-risk areas and potential threats.

AI-Based Adaptive Firewall System

• Objective: Build an adaptive firewall that uses machine learning to dynamically adjust its rules based on real-time network traffic and emerging threat patterns.
• Novelty: Include the ability for the firewall to autonomously add or remove rules based on continuous monitoring of network health, and also provide insights into why certain rules were adjusted.
• Enterprise Use: Provides more robust and adaptable network defense mechanisms, improving protection against evolving cyber threats.

No-Code API Integration Platform

• Objective: Build a no-code platform where users can easily integrate different enterprise APIs (e.g., CRM, ERP, and HR systems) by dragging and dropping pre-built connectors.
• Novelty: The platform should automatically generate the necessary authentication and API calls, allowing users to visually map data between APIs without needing coding expertise.
• Enterprise Use: Simplifies the process of integrating multiple enterprise systems, making it accessible to non-developers in business teams.

Low-Code Multi-API Security Gateway

• Objective: Build a low-code platform that allows enterprises to secure their API ecosystem by creating custom security rules (authentication, rate limiting, encryption) for multiple APIs through a visual interface.
• Novelty: Include AI-driven security recommendations based on detected vulnerabilities or common security gaps in the enterprise's API infrastructure.
• Enterprise Use: Enhances API security across the organization, allowing security teams to enforce best practices with minimal coding effort.

AI-Assisted No-Code Business Rule Engine

• Objective: Develop a no-code business rule engine that allows users to define and enforce rules for enterprise workflows (e.g., approvals, notifications, data validation) by integrating with APIs and setting conditions through a visual interface.
• Novelty: Incorporate AI to suggest rule optimizations, identify inefficiencies, and predict outcomes based on historical data and trends.
• Enterprise Use: Streamlines decision-making processes in enterprise workflows, reducing errors and speeding up processes by allowing non-developers to create business logic without coding.

No-Code Custom API Builder with AI Code Generation

• Objective: Build a no-code tool that allows users to create their own APIs by defining data structures, business rules, and endpoints through a visual interface.
• Novelty: The platform could use AI to automatically generate backend code (in Python, Node.js, etc.) based on the user's visual inputs, enabling rapid API deployment.
• Enterprise Use: Empowers business users and non-developers to create custom APIs tailored to specific organizational needs without writing a single line of code.

AI-Driven Kubernetes Network Policy Generator

• Objective: Create a platform that generates and enforces network policies for Kubernetes clusters based on traffic patterns and security needs, using AI to analyze and optimize the policies dynamically.
• Novelty: Include features where AI learns from past network behavior to suggest the most efficient and secure policies, improving cluster security without sacrificing performance.
• Enterprise Use: Enhances the security of Kubernetes environments, particularly in large-scale enterprise deployments with complex microservice architectures.

AI-Assisted Kubernetes Deployment Versioning and Rollback

• Objective: Develop a system that manages deployment versioning and rollback strategies in Kubernetes environments, using AI to predict the best time to deploy updates and automatically decide when to roll back based on performance metrics.
• Novelty: The AI model should continuously learn from past deployments to optimize future releases, ensuring that rollback decisions are timely and accurate.
• Enterprise Use: Improves the reliability of application updates in enterprise environments, reducing the risk of downtime or broken features during releases.

Automated AI-Enhanced Penetration Testing Platform

• Objective: Build an AI-driven penetration testing platform that automates the simulation of cyber-attacks to identify system vulnerabilities in real time.
• Novelty: Include adaptive learning features where the AI can tailor penetration tests to specific enterprise environments, making tests more efficient and relevant by learning from the enterprise's past security incidents.
• Enterprise Use: Provides continuous and autonomous security assessments, allowing enterprises to proactively identify and fix vulnerabilities before exploitation.