techsprint

Team Details Team name: The Quaternary Team leader name: Tanuj Kumar Problem Statement: Open Innovation.

[image]. SOLUTION. Network Anonymity: The TOR network uses multi-layered encryption to hide user identities and server locations, making it nearly impossible to trace traffic origin. Hidden Discovery: Traditional search engines cannot index the Dark Web, leading to a lack of centralized URL directories for active hidden servers. Illegal Content: Hidden servers are frequently used for criminal activities like selling drugs and weapons, which are difficult to monitor manually. Financial Untraceability: Transactions on these platforms primarily use Bitcoin, creating a massive barrier for law enforcement to link payments to real-world identities. Analysis Delay: There is a lack of real-time AI tools capable of automatically identifying faces, objects, and criminal patterns within dark web media.

[image]. Innovation & Differentiation Real-Time Intelligence: Unlike static search engines that provide old links, this tool performs real-time stream analysis for immediate threat detection. Multimodal AI: Moves beyond text-only indexing by using Computer Vision to identify faces, objects, and criminal scenes in images and videos. Financial Linkage: Integrates Bitcoin address tracing directly into the crawling workflow to link anonymous activity to a financial footprint. Autonomous Learning: Uses Deep Learning (TensorFlow) to continuously improve detection accuracy and adapt to new concealment tactics. How it Solves the Problem Automated Discovery: Systematically maps the Dark Web using a custom crawler with TOR proxies to find hidden sites not indexed by Google. Digital De-Anonymization: Uses NLP and Computer Vision to correlate aliases and identify the real-world personas behind hidden servers. Proactive Prevention: Identifies criminal patterns and anomalies (drugs, weapons, etc.) to alert authorities before illegal activities scale. Actionable Evidence: Extracts technical "fingerprints" and stores them in a POC (Proof of Concept) database for use by law enforcement. Massive Scalability: Replaces slow manual monitoring with an automated system capable of scanning thousands of hidden channels simultaneously..

[image]. List of Features Offered Custom Dark Web Crawler: Uses specialized software and TOR proxies to navigate the hidden corners of the internet anonymously and safely. Multimodal Data Extraction: Automatically retrieves and processes text, images, and videos from identified hidden pages for deep analysis. Real-Time AI Analysis: Employs Deep Learning algorithms to analyze data instantly, allowing for rapid identification of illegal activities and immediate alerts to authorities. Computer Vision (CV) Intelligence: Identifies objects, faces, and scenes within visual media to detect criminal patterns or sensitive content. Natural Language Processing (NLP): Interprets and analyzes text-based data from dark web forums and marketplaces to uncover hidden criminal trends. Financial Forensics: Integrates Bitcoin address tracing to map transaction histories and identify the availability of users behind anonymous servers. Network Mapping: Utilizes Network Analysis, DNS Lookups, and Tor Spam Site Lists to verify the activeness and history of hidden servers. Actionable Database: Automatically stores extracted links and evidence in a Sadhak Database for further law enforcement investigation and "Proof of Concept" (POC) generation..

[image]. Google Technologies Used TensorFlow: This is the primary Google technology used as the core engine for building and training the Deep Learning algorithms. It enables the software to learn and improve its data analysis over time. Google Vision AI (Implementation Core): The project's Computer Vision (CV) capabilities—used for identifying objects, scenes, and faces within images and videos—are built upon the frameworks provided by Google’s ML ecosystem. Natural Language Processing (NLP) Tools: Google-based NLP libraries and models are utilized to analyze and interpret text-based data extracted from hidden forums to detect criminal patterns. Android/Google Cloud (Potential Scale): While not explicitly detailed in the PDF, the Technology Stack mentions "AIM" (likely AI/ML) and Flask, which are commonly deployed on Google Cloud Platform (GCP) for scalable processing of large-scale dark web datasets..

[image]. USE CASE DIAGRAM. [image].

Future Development. [image]. Google Technology: TensorFlow Federated (TFF) for decentralized, privacy-safe collaborative learning. Security Layer: Blockchain-based immutable logs to ensure evidence gathered is tamper-proof and legally admissible. Analytics: Time-series forecasting (LSTM networks) for predicting market movement and illegal product surges..

[image]. Thank you!.