DefacementAttackDataset

Published: 24 October 2024| Version 1 | DOI: 10.17632/jtz9gzjgbp.1
Contributor:
jacob neyole

Description

The dataset titled "DefacementAttackDataset" contains 3,400 entries with 18 columns, documenting social media defacement attacks. The key fields in the dataset include: - User ID, Username, Account Status: Information about the affected users. - Followers Count: The number of followers of each user. - Post ID, Content Before and After Defacement: The original and altered content of the defaced posts. - Post Timestamp, Defacement Method, Type of Attack: Details on when the post was made, the method used to deface it, and the type of attack. - IP Address, Location, Device Information: Information about the attacker's IP address, location, and device. - Time of Defacement, Detection, Recovery: Timelines of the attack, detection, and recovery efforts. - Action Taken, Restoration Status: The actions taken after the attack and the current status of the defaced content. ** Note that this dataset can be used to analyze patterns in social media defacement attacks, focusing on attack methods, recovery times, and the effectiveness of response actions.

Files

Steps to reproduce

To reproduce a dataset similar to the DefacementAttackDataset documenting social media defacement attacks, the following steps are important: 1. Define the Objective and Scope 2. Collect Real-World Data (If Possible) 3. Simulate Defacement Attacks 4. Create Data Fields 5. Add Randomization 6. Validate and Clean Data 7. Store the Data

Categories

Machine Learning, Computer Security Models

Licence