论文标题
关于针对建筑自动化系统的虚假数据注射攻击
On False Data Injection Attack against Building Automation Systems
论文作者
论文摘要
KNX是建筑自动化系统（BAS）的一种流行通信协议。但是，它缺乏安全性会遭受各种攻击。我们是第一个研究针对基于KNX的BAS的虚假数据注射攻击的人。我们设计了中间人（MITM）攻击，以将数据从温度传感器更改，并将虚假数据注入BAS。我们对BAS进行建模并分析虚假数据注射攻击对系统的影响。由于MITM攻击可能会干扰KNX流量，因此我们设计了基于机器学习的检测策略，以使用基于Jensen Shannon Divergence（JSD）的新型功能来检测错误的数据注射攻击，该功能衡量了KNX Telegram Inter-Arm-Arm-Artival Inter-Arrival Time分配与攻击和无攻击的相似性。我们执行现实世界实验，并验证提出的虚假数据注射攻击和基于ML的检测策略。我们还模拟了BAS，并证明虚假的数据注射攻击在功耗方面对BAS产生了巨大影响。
KNX is one popular communication protocol for a building automation system (BAS). However, its lack of security makes it subject to a variety of attacks. We are the first to study the false data injection attack against a KNX based BAS. We design a man-in-the-middle (MITM) attack to change the data from a temperature sensor and inject false data into the BAS. We model a BAS and analyze the impact of the false data injection attack on the system in terms of energy cost. Since the MITM attack may disturb the KNX traffic, we design a machine learning (ML) based detection strategy to detect the false data injection attack using a novel feature based on the Jensen Shannon Divergence (JSD), which measures the similarity of KNX telegram inter-arrival time distributions with attack and with no attack. We perform real-world experiments and validate the presented false data injection attack and the ML based detection strategy. We also simulate a BAS, and show that the false data injection attack has a huge impact on the BAS in terms of power consumption.
