From d10e64cfcaee0d12c76b59d11a7d6e98ce5d52d8 Mon Sep 17 00:00:00 2001 From: Mohamed feroz khan D <cb.en.p2cys21017@cb.students.amrita.edu> Date: Fri, 9 Jun 2023 12:49:20 +0530 Subject: [PATCH] Syncing with Github project repo --- README.md | 27 ++++++++++++++++++++++++++- 1 file changed, 26 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index ccc03e6..70dafd7 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# Blockchain Forensics using OSINT and Graph Temporal Logic  +# Blockchain Forensics using Graph Temporal Logic        <br/>   @@ -8,6 +8,31 @@ ## Abstract +Detection of Illegal and Malicious accounts and transactions in Blockchain through ev- +idences collected from blockchain (on-chain) and related sources (off-chain) by Open +Source Intelligence (OSINT) and analysis through Graph Temporal Properties. Blockchain +is a decentralized computing distributed ledger platform that enables us to store im- +mutable transactions. In an open and transparent system, it makes logical decisions +involving several stakeholders. In this paper, we are compiling a list of addresses that +have been reported on social media, and using the information we have gathered, we will +check the blockchain explorer and extract the address along with the transaction’s date, +time, and amount. This procedure is referred to as being “on-chain.” With the gathered +information, we create a dataset and conduct Off-chain Open Source Intelligence (OS- +INT) on the addresses to see whether they have appeared somewhere else online, such as +forums, Wikileaks, or other websites. +With the use of OSINT, we will utilise our techniques to determine the wallet address +of that user, and we will then use Graph Temporal Properties to examine the information +we have gathered. In Graph Temporal properties, we are uploading the dataset that we +created. When the graph gets executed, we will have an idea of how many times the +malicious address made contact with other collected addresses, and here we can find the +neighborhood stability and attractive for every address that we gave in the temporal +graph. Here we have to take Graph Temporal for the malicious address per day, week, +and month. Using the temporal graph, we can determine which addresses have the most +communication with the malicious account, we will filter those addresses and do both Off- +chain and On-chain Open Source Intelligence on those addresses. If any of these address +identities are disclosed on the internet, we can readily determine what the malicious +account conducts, such as fraud, ransomware, silk route, and so on. + ## Architecture Diagram ## Results -- GitLab