Ransomware Dataset 2024

<p>The dataset we have created is focused on malware analysis and consists of 26 different malware families, categorized into four main categories. It includes both malicious and benign samples, providing a balanced total of 21,752 samples, with 10,876 malicious and 10,876 benign files.</p> <h3>Key Aspects of the Dataset:</h3> <ol> <li> <p><strong>Total Samples</strong>: 21,752 files (10,876 malicious and 10,876 benign).</p> </li> <li> <p><strong>Malware Families</strong>: The dataset contains 26 distinct malware families, with a strong focus on ransomware, which includes:</p> <ul> <li><strong>Cerber</strong></li> <li><strong>DarkSide</strong></li> <li><strong>Dharma</strong></li> <li><strong>GandCrab</strong></li> <li><strong>LockBit</strong></li> <li><strong>Maze</strong></li> <li><strong>Phobos</strong></li> <li><strong>REvil</strong></li> <li><strong>Ragnar Locker</strong></li> <li><strong>Ryuk</strong></li> <li><strong>Shade</strong></li> <li><strong>WannaCry</strong></li> </ul> <p>These 11 ransomware families represent some of the most notorious strains responsible for large-scale attacks in recent years.</p> </li> <li> <p><strong>Categories</strong>: The dataset is divided into four categories, although you haven&rsquo;t specified the exact categorization scheme (it could be based on behavior, type of attack, or other malware features). Typical categories could include <strong>Trojan</strong>, <strong>Ransomware</strong>, <strong>Spyware</strong>, and <strong>Adware</strong>.</p> </li> </ol> <h3>Significance of the Dataset:</h3> <ul> <li><strong>Balanced Distribution</strong>: The dataset is evenly distributed between malicious and benign files, making it ideal for machine learning models that can differentiate between malware and benign software.</li> <li><strong>Ransomware Focus</strong>: By including major ransomware families, this dataset allows for specialized research in ransomware detection, mitigation, and family classification.</li> <li><strong>Diversity in Malware Types</strong>: The inclusion of 26 malware families ensures a wide spectrum of malware behavior and characteristics, making the dataset versatile for research in various malware categories.</li> </ul> <h3>Applications:</h3> <ul> <li><strong>Machine Learning and AI</strong>: This dataset can be used to train models for malware classification, detection, and family identification.</li> <li><strong>Cybersecurity Research</strong>: It supports analysis and countermeasure development against ransomware and other forms of malware.</li> <li><strong>Forensic Analysis</strong>: Researchers can use it to investigate attack patterns, signature generation, and the impact of ransomware on different systems.</li> </ul> <p>This dataset is valuable for advancing malware analysis, specifically in understanding ransomware behavior, and for building robust defenses against increasingly sophisticated attacks.</p>