Biblio
Cyber-Physical Systems (CPSs), a class of complex intelligent systems, are considered the backbone of Industry 4.0. They aim to achieve large-scale, networked control of dynamical systems and processes such as electricity and gas distribution networks and deliver pervasive information services by combining state-of-the-art computing, communication, and control technologies. However, CPSs are often highly nonlinear and uncertain, and their intrinsic reliance on open communication platforms increases their vulnerability to security threats, which entails additional challenges to conventional control design approaches. Indeed, sensor measurements and control command signals, whose integrity plays a critical role in correct controller design, may be interrupted or falsely modified when broadcasted on wireless communication channels due to cyber attacks. This can have a catastrophic impact on CPS performance. In this paper, we first conduct a thorough analysis of recently developed secure and resilient control approaches leveraging the solid foundations of adaptive control theory to achieve security and resilience in networked CPSs against sensor and actuator attacks. Then, we discuss the limitations of current adaptive control strategies and present several future research directions in this field.
In construction machinery, connectivity delivers higher advantages in terms of higher productivity, lower costs, and most importantly safer work environment. As the machinery grows more dependent on internet-connected technologies, data security and product cybersecurity become more critical than ever. These machines have more cyber risks compared to other automotive segments since there are more complexities in software, larger after-market options, use more standardized SAE J1939 protocol, and connectivity through long-distance wireless communication channels (LTE interfaces for fleet management systems). Construction machinery also operates throughout the day, which means connected and monitored endlessly. Till today, construction machinery manufacturers are investigating the product cybersecurity challenges in threat monitoring, security testing, and establishing security governance and policies. There are limited security testing methodologies on SAE J1939 CAN protocols. There are several testing frameworks proposed for fuzz testing CAN networks according to [1]. This paper proposes security testing methods (Fuzzing, Pen testing) for in-vehicle communication protocols in construction machinery.