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Security-Aware Modeling and Efficient Mapping for CAN-Based Real-Time Distributed Automotive Systems

机译:基于CAN的实时分布式汽车系统的安全意识建模和有效映射

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Security has become a critical issue for automotive electronic systems. To protect against attacks, security mechanisms have to be applied, but the overhead of those mechanisms may impede system performance and cause violations of design constraints. To remedy this problem, we proposed an integrated mixed integer linear programming (MILP) formulation that is the first to address both security and safety constraints during system mapping for controller area network (CAN) based systems . However, its signal-based security constraints do not fully reflect real security requirements, and its objective function is to minimize functional path latencies rather than minimize security risk. Furthermore, its MILP-based approach has high computation complexity. In this work, we present a new formulation that defines path-based security constraints and minimizes security risk directly, and propose a new heuristic algorithm to solve the formulation efficiently. Experiments on an industrial example show that our new algorithm achieves comparable solution quality as the MILP-based approach with much better efficiency.
机译:安全性已成为汽车电子系统的关键问题。为了防止受到攻击,必须应用安全性机制,但是这些机制的开销可能会阻碍系统性能并导致违反设计约束。为了解决这个问题,我们提出了一种集成混合整数线性规划(MILP)公式,该公式是第一个在基于控制器局域网(CAN)的系统映射期间解决安全性和安全性约束的方法。但是,其基于信号的安全性约束不能完全反映实际的安全性要求,并且其目标功能是最小化功能路径延迟而不是最小化安全风险。此外,其基于MILP的方法具有很高的计算复杂性。在这项工作中,我们提出了一种新的公式,该公式定义了基于路径的安全约束并直接最小化了安全风险,并提出了一种新的启发式算法来有效地解决该公式。一个工业示例的实验表明,我们的新算法可达到与基于MILP的方法相当的解决方案质量,并且效率更高。

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