论文标题
量化城市道路网络脆弱性和对攻击的韧性
Quantifying Urban Road Network Vulnerability and Resilience to Attacks
论文作者
论文摘要
连接和自动驾驶汽车的兴起，结合了物联网和连接的表面的扩散，导致了新型复杂的网络风险的出现。网络安全专家，汽车和OEM制造商普遍认为，内部车辆网络中缺乏加密和身份验证是值得关注的原因。这种关注只会随着网络安全事件的增加和示威的增加而增加，显示出不同的车辆脆弱性，这几乎不可能使车辆完全保护网络攻击。特别关注的是，大规模车辆网络攻击的潜力可能是级联到运输网络的级联，这是城市的生命线。在这里，我们开发了一个基于复杂网络理论，流量流和基于新数据的技术的框架，以量化城市规模运输到网络攻击的脆弱性。我们在波士顿的道路网络中的应用表明，针对一小部分节点的针对性攻击会导致途径的较大破坏。我们开发了一个早期检测框架，以量化基于收集多维交通流，事件和社交媒体数据集的实时风险。我们的结果说明了通过知情的，智能的车辆代理商采用基于效果的运输网络防御方法。
The rise of connected and autonomous vehicles, combined with the proliferation of IoT and connected surfaces, lead to the emergence of novel complex cyber risks. Lack of encryption and authentication in internal vehicular networks are widely recognized as cause for concern by cybersecurity experts, automobile, and OEM manufacturers. This concern has only been growing with the increase in cybersecurity incidents and demonstrations showing different vehicular vulnerabilities, making it nearly impossible to completely secure vehicles against cyber-attacks. Of particular concern is the potential for large-scale vehicular cyber-attacks to cascade to transportation networks, which are the lifeline of cities. Here, we develop a framework based on complex network theory, traffic flow, and new data based technologies to quantify the vulnerability of city-scale transportation to cyber-attacks. Application of our framework to the road network of Boston reveals that targeted attacks on a small fraction of nodes leads to disproportionately larger disruptions of routes. We develop an early-detection framework to quantify real-time risk based on gathering multidimensional traffic flow, incident, and social media data sets. Our results illustrate an effects based approach to transportation cyber-defense, through informed, intelligent vehicular agents.
