勒索软件检测动态：洞察与启示
Ransomware Detection Dynamics: Insights and Implications
AI总结：
本研究提出基于基尼不纯度和互信息的特征选择算法（RFSA），利用UGRansome数据集区分勒索软件相关交易，实验显示约68%事件涉及1.46至2.56 BTC，有助于早期检测。
摘要：
勒索软件攻击的兴起使得制定有效的识别和缓解策略成为必要。本研究探讨了利用特征选择算法来区分比特币（BTC）和美元（USD）交易中的勒索软件相关交易与良性交易。利用UGRansome数据集（一个包含勒索软件相关BTC和USD交易的全面存储库），我们提出了一组新颖的特征，旨在捕捉加密货币生态系统中勒索软件活动的独特特征。这些特征涵盖交易元数据、赎金分析和行为模式，提供了勒索软件相关金融交易的多方面视角。通过严格的实验和评估，我们证明了我们的特征集在准确提取BTC和USD交易方面的有效性，从而有助于早期检测和预防勒索软件相关的金融流动。我们引入了一种基于基尼不纯度和互信息（MI）的勒索软件特征选择算法（RFSA），用于从UGRansome数据集中选择关键的勒索软件特征。可视化的洞察凸显了基于基尼不纯度和MI的特征选择在通过有效区分勒索软件类别来增强勒索软件检测系统方面的潜力。分析显示，大约68%的勒索软件事件涉及BTC交易，金额范围在1.46至2.56之间，每次攻击平均有2.01笔BTC交易。研究结果强调了勒索软件需求的动态性和适应性，表明特定网络攻击没有固定的金额，凸显了勒索软件威胁不断演变的格局。
英文摘要：
The rise of ransomware attacks has necessitated the development of effective strategies for identifying and mitigating these threats. This research investigates the utilization of a feature selection algorithm for distinguishing ransomware-related and benign transactions in both Bitcoin (BTC) and United States Dollar (USD). Leveraging the UGRansome dataset, a comprehensive repository of ransomware related BTC and USD transactions, we propose a set of novel features designed to capture the distinct characteristics of ransomware activity within the cryptocurrency ecosystem. These features encompass transaction metadata, ransom analysis, and behavioral patterns, offering a multifaceted view of ransomware-related financial transactions. Through rigorous experimentation and evaluation, we demonstrate the effectiveness of our feature set in accurately extracting BTC and USD transactions, thereby aiding in the early detection and prevention of ransomware-related financial flows. We introduce a Ransomware Feature Selection Algorithm (RFSA) based on Gini Impurity and Mutual Information (MI) for selecting crucial ransomware features from the UGRansome dataset. Insights from the visualization highlight the potential of Gini Impurity and MI-based feature selection to enhance ransomware detection systems by effectively discriminating between ransomware classes. The analysis reveals that approximately 68% of ransomware incidents involve BTC transactions within the range of 1.46 to 2.56, with an average of 2.01 BTC transactions per attack. The findings emphasize the dynamic and adaptable nature of ransomware demands, suggesting that there is no fixed amount for specific cyberattacks, highlighting the evolving landscape of ransomware threats.
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