The team proposes to develop an Indigenous Crypto Currency Investigation Tool to help analyze blockchain transactions and identify potential criminal activity. The tool would include features such as a blockchain explorer to search transactions across platforms, a wallet tracker to monitor fund movements, an automated risk assessment system, smart contract analysis, pattern recognition algorithms, and user identity verification. The team of 6 students from Bannari Amman Institute of Technology aims to build the tool using Python, JavaScript, cryptography libraries, blockchain APIs, distributed databases, machine learning frameworks, and cloud computing services. The academic mentor's area of expertise is data science.

1. BASIC DETAILS OF THE TEAM AND PROBLEM
STATEMENT
PSID: KVH-020
Problem Statement Title: Indigenous Crypto Currency Investigation Tool
Team Name: TECH SQUAD
Team Leader Name: NITESH P B
Institute Code (AISHE): 397
Institute Name: BANNARI AMMAN INSTITUTE OF TECHNOLOGY

2. IDEA/APPROACH DETAILS
1. Blockchain Explorer: A blockchain explorer that allows users to search through multiple
blockchain platforms to track and trace specific transactions, addresses, and blocks. This tool
can also provide detailed information about the origin, destination, and value of each
transaction.
2. Wallet Tracker: A tool that can track the movement of funds between different wallets and
identify any suspicious activity. This tool can also generate alerts when transactions are made to
known scam addresses or when funds are being transferred to a high-risk country.
3. Automated Risk Assessment: A tool that can automatically assess the risk level of specific
transactions and addresses based on factors such as volume, frequency, and destination. This
tool can provide a risk score for each transaction or address, which can help investigators
prioritize their efforts.
4. Smart Contract Analysis: A tool that can analyze smart contracts on various blockchain
platforms to identify potential vulnerabilities or security flaws. This tool can also be used to
review the code of smart contracts to ensure compliance with relevant regulations and
standards.
5. Pattern Recognition: A tool that can identify patterns in transaction data across multiple
blockchain platforms. This tool can help investigators identify potential money laundering or
other criminal activity by detecting unusual patterns of behavior.
6. User Identity Verification: A tool that can verify the identity of users on blockchain platforms
to ensure compliance with KYC (know your customer) and AML (anti-money laundering)
regulations. This tool can use biometric data or other forms of identity verification to ensure
that users are who they claim to be.
7. Machine Learning Algorithms: A tool that can use machine learning algorithms to analyze
transaction data and identify potential fraudulent activity. This tool can learn from past patterns
of behavior and use this knowledge to predict future behavior and identify high-risk
transactions.
Technology stack
1.Programming languages: Python, JavaScript, or
Solidity
2.Cryptography Libraries: OpenSSL or Nacl
3.Blockchain APIs: APIs such as Bitcoin, Ethereum,
or Ripple
4.Distributed databases: Apache Cassandra or
MongoDB
5.Machine learning frameworks: TensorFlow or
PyTorch
6.Web frameworks: Flask or Django
7.Cloud computing services: Amazon Web Services
(AWS) or Microsoft Azure
8.Security tools: Encryption, multi-factor
authentication, and secure coding practices

3. DETAILS
USE CASE DEPENDENCIES
1) PYTHON & JAVASCRIPT
2) OpenSSL or Nacl LIBRARIES
3) API’s (BITCOIN, ETHEREUM or
RIPPLE)
4) APPACHE CASSANDRA or MongoDB
5) TENSORFLOW or PYTORCH
6) FLASK or DJANGO
7) AWS or ASURE

4. TEAM MEMBER DETAILS
Sr. No. Name ofTeam Member Branch
(Btech/Mtech/P
hD etc):
Stream (ECE,
CSE etc):
Year Position in team
(Team Leader, Front end
Developer, Back end
Developer, Full Stack,
Data base management
etc.)
1 NITESH P B BE CSE II Team Leader(Full
stack developer)
2 BAWYAV BE ISE II Front end &
Back end developer
3 NIKITHA M BE ISE II Front end &
Back end developer
4 ARJUN SV BE CSE II Front end developer
5 KAVIYALAKSHMI S S BE ISE II Front end developer
6 VIKHASH J P BE CSE II Front end developer
Sr. No. Name of Mentor Category
(Academic/Industry):
Expertise
(AI/ML/Blockchain etc):
1 KARTHIGA M Academic DATA SCIENCE
Team Mentor Details