Subverting adversarial attribution

当恶意软件攻击威胁成为您的首要任务时，一切都会改变。最近的网络攻击在医疗保健、金融业和国防等关键领域造成了严重后果。恶意软件或恶意软件已成为这些攻击的终极工具。2016年，恶意软件导致乌克兰电网停电。2017年，英国各地的医院遭到勒索软件攻击，要求支付解锁医院IT系统的费用。恶意软件具有自适应性、破坏性和不断进化的特性，可以逃避我们的传统防御。攻击者比以往任何时候都更多地使用模糊技术来伪装他们的身份，以及他们的恶意代码，使其难以检测，分析或理解。我们研究的长期目标是设计和开发有效和有弹性的技术，用于识别，理解，评估和中和软件中的混淆防御。这不仅将为我们提供更有效的软件保护工具，还将大大增强我们对对抗行为的理解。

Everything changes when a threat of malware attack becomes your number one priority. Recent cyberattacks have caused severe consequences in critical sectors including healthcare, the financial industry, and national defense. Malicious software, or malware, has become an ultimate tool in these attacks. In 2016, malware was responsible for Ukraine's power grid blackout. In 2017, hospitals across UK were hit with a ransomware attack demanding payment for unlocking the hospital's IT systems. Adaptive, destructive, and constantly evolving, malware evades our traditional defenses. More than ever adversaries use obfuscation techniques to disguise their identity, and their malicious code to make it hard to detect, analyze or understand. The long-term goal of our research is to design and develop efficient and resilient techniques for identifying, understanding, evaluating and neutralizing obfuscation defenses in software. This will not only give us more effective software protection tools, but will also greatly enhance our understanding of adversarial behavior.