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Found 9 papers, 0 papers with code
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.
EPASAD: Ellipsoid decision boundary based Process-Aware Stealthy Attack Detector
Detection of an ongoing attack that escapes standard protection such as firewall, anti-virus, and host/network intrusion detection has gained importance as such attacks eventually affect the physical dynamics of the system.
Towards Malicious address identification in Bitcoin
We are motivated to study the Bitcoin transaction network and use the temporal features such as burst, attractiveness, and inter-event time along with several graph-based properties such as the degree of node and clustering coefficient to validate the applicability of already existing approaches known for other cryptocurrency blockchains on the Bitcoin blockchain.
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 cyber-criminals costing billions of dollars.
Vulnerability and Transaction behavior based detection of Malicious Smart Contracts
In this work, we study the correlation between malicious activities and the vulnerabilities present in SCs and find that some malicious activities are correlated with certain types of vulnerabilities.
Detecting Malicious Accounts showing Adversarial Behavior in Permissionless Blockchains
To that end, we identify a robust supervised machine learning (ML) algorithm that is resistant to any bias induced by an over representation of certain malicious activity in the available dataset, as well as is robust against adversarial attacks.
GDPR-inspired IoT Ontology enabling Semantic Interoperability, Federation of Deployments and Privacy-Preserving Applications
IoT data that belong to users and from which their personal information can be inferred are frequently shared in the background of IoT systems with third parties for experimentation and building quality services.
Databases
Detecting Malicious Accounts in Permissionless Blockchains using Temporal Graph Properties
The temporal nature of modeling accounts as nodes and transactions as directed edges in a directed graph -- for a blockchain, enables us to understand the behavior (malicious or benign) of the accounts.
A study of existing Ontologies in the IoT-domain
As a solution to this, semantic approaches have been proposed in the literature to tackle problems related to interoperability of sensor data.
