Blockchains

Understanding Rug Pulls: An In-Depth Behavioral Analysis of Fraudulent NFT Creators

The explosive growth of non-fungible tokens (NFTs) on Web3 has created a new frontier for digital art and collectibles, but also an emerging space for fraudulent activities. This study provides an in-depth analysis of NFT rug pulls, which are …

Identifying malicious accounts in Blockchains using Domain Names and associated temporal properties

The rise in the adoption of blockchain technology has led to increased illegal activities by cybercriminals costing billions of dollars. Many machine learning algorithms are applied to detect such illegal behavior. These algorithms are often trained …

DNS based In-Browser Cryptojacking Detection

The metadata aspect of Domain Names (DNs) enables us to perform a behavioral study of DNs and detect if a DN is involved in in-browser cryptojacking. Thus, we are motivated to study different temporal and behavioral aspects of DNs involved in …

Reputation-based PoS for the Restriction of Illicit Activities on Blockchain: Algorand Usecase

In cryptocurrency-based permissionless blockchain networks, the decentralized structure enables any user to join and operate across different regions. The criminal entities exploit it by using cryptocurrency transactions on the blockchain to …

Towards Malicious address identification in Bitcoin

The temporal aspect of blockchain transactions enables us to study the address's behavior and detect if it is involved in any illicit activity. However, due to the concept of change addresses (used to thwart replay attacks), temporal aspects are not …

Understanding Money Trails of Suspicious Activities in a cryptocurrency-based Blockchain

The decentralization, redundancy, and pseudo-anonymity features have made permission-less public blockchain platforms attractive for adoption as technology platforms for cryptocurrencies. However, such adoption has enabled cybercriminals to exploit …

Vulnerability and Transaction behavior based detection of Malicious Smart Contracts

Smart Contracts (SCs) in Ethereum can automate tasks and provide different functionalities to a user. Such automation is enabled by the Turing-complete nature of the programming language (Solidity) in which SCs are written. This also opens up …

Security of Healthcare Data Using Blockchains: A Survey

The advancement in the healthcare sector is entering into a new era in the form of Health 4.0. The integration of innovative technologies like Cyber-Physical Systems (CPS), Big Data, Cloud Computing, Machine Learning, and Blockchain with Healthcare …

Analyzing malicious activities and detecting adversarial behavior in cryptocurrency based permissionless blockchains: An Ethereum usecase

Different malicious activities occur in cryptocurrency-based permissionless blockchains such as Ethereum and Bitcoin. Some activities are due to the exploitation of vulnerabilities which are present in the blockchain infrastructure, some activities …

Detecting Malicious Accounts in Permissionless Blockchains using Temporal Graph Properties

Directed Graph based models of a blockchain that capture accounts as nodes and transactions as edges, evolve over time. This temporal nature of a blockchain model enables us to understand the behavior (malicious or benign) of the accounts. Predictive …