diff --git a/README.md b/README.md
index 3c4a14ad19414ff86398f21807d682d15877c5e0..47c2d896046d8ae31a8ac018bc417f7dfd1e3520 100644
--- a/README.md
+++ b/README.md
@@ -6,6 +6,7 @@
 The Graph-Based Dataset for IoT Network Attack Detection is a curated collection of data specifically designed for research and development in the field of cybersecurity, focusing on the detection of attacks in Internet of Things (IoT) networks. This graph-based dataset provides researchers, developers, and practitioners with a comprehensive resource to evaluate and benchmark various detection algorithms and systems in real-world IoT network environments.
 
 ## Dataset Description
+[comment]: # (Still another comment)
 
 The dataset consists of network traffic data captured from emulated IoT network environments, where various attack scenarios have been emulated. The network traffic data is represented in the form of graphs, capturing the interactions and relationships between different devices, services, and communication patterns within the IoT network. Each graph in the dataset represents a snapshot of network activity over a specific time period, enabling analysis of attack patterns and behaviors. The following figure presents the general netwok architecture.