论文标题
法医伪像发现和归因于Android加密货币钱包应用
Forensic Artefact Discovery and Attribution from Android Cryptocurrency Wallet Applications
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
Cryptocurrency has been (ab)used to purchase illicit goods and services such as drugs, weapons and child pornography (also referred to as child sexual abuse materials), and thus mobile devices (where cryptocurrency wallet applications are installed) are a potential source of evidence in a criminal investigation. Not surprisingly, there has been increased focus on the security of cryptocurrency wallets, although forensic extraction and attribution of forensic artefacts from such wallets is understudied. In this paper, we examine Bitcoin and Dogecoin. The latter is increasingly popular partly due to endorsements from celebrities and being positioned as an introductory path to cryptocurrency for newcomers. Specifically, we demonstrate how one can acquire forensic artefacts from Android Bitcoin and Dogecoin cryptocurrency wallets, such as wallet IDs, transaction IDs, timestamp information, email addresses, cookies, and OAuth tokens.
