Intrusion Detection in Digital Twins for Industrial Control Systems

Nowadays, the growth of advanced technologies is paving the way for Industrial Control Systems (ICS) and making them more efficient and smarter. However, this makes ICS more connected to communication networks that provide a potential platform for attackers to intrude into the systems and cause damage and catastrophic consequences. In this paper, we propose implementing digital twins that have been equipped with an intrusion detection algorithm. Our novel algorithm is able to detect attacks in a timely manner and also diagnose the type of attack by classification of different types of attacks. With digital twins, which are a new concept in ICS, we have virtual replicas of physical systems so that they precisely mirror the internal behavior of the physical systems. So by placing the intrusion detection algorithm in digital twins, security tests can be done remotely without risking negative impacts on live systems

Synchronization in Digital Twins for Industrial Control Systems

Digital twins, which are a new concept in industrial control systems (ICS), play a key role in realizing the vision of a smart factory, and they can have different effective use cases. With digital twins, we have virtual replicas of physical systems so that they precisely mirror the internal behavior of the physical systems. Hence, synchronization is necessary to keep the states of digital twins in sync with those of their physical counterparts. Otherwise, their behavior may be different from each other, and it can lead to wrong decisions about the system that can have catastrophic consequences. In this paper, we propose three different architectures for digital twins, and then by investigating their ability to follow the physical system's behavior, we will determine the best architecture, whose output has the lowest error compared with the physical system's output.Comment: 4 pages, 6 figure

Surgical injury in the neonatal rat alters the adult pattern of descending modulation from the rostroventral medulla

Background: Neonatal pain and injury can alter long-term sensory thresholds. Descending rostroventral medulla (RVM) pathways can inhibit or facilitate spinal nociceptive processing in adulthood. As these pathways undergo significant postnatal maturation, the authors evaluated long-term effects of neonatal surgical injury on RVM descending modulation. Methods: Plantar hind paw or forepaw incisions were performed in anesthetized postnatal day (P)3 Sprague-Dawley rats. Controls received anesthesia only. Hind limb mechanical and thermal withdrawal thresholds were measured to 6 weeks of age (adult). Additional groups received pre- and post-incision sciatic nerve levobupivacaine or saline. Hind paw nociceptive reflex sensitivity was quantified in anesthetized adult rats using biceps femoris electromyography, and the effect of RVM electrical stimulation (5–200 μA) measured as percentage change from baseline. Results: In adult rats with previous neonatal incision (n = 9), all intensities of RVM stimulation decreased hind limb reflex sensitivity, in contrast to the typical bimodal pattern of facilitation and inhibition with increasing RVM stimulus intensity in controls (n = 5) (uninjured vs. neonatally incised, P < 0.001). Neonatal incision of the contralateral hind paw or forepaw also resulted in RVM inhibition of hind paw nociceptive reflexes at all stimulation intensities. Behavioral mechanical threshold (mean ± SEM, 28.1 ± 8 vs. 21.3 ± 1.2 g, P < 0.001) and thermal latency (7.1 ± 0.4 vs. 5.3 ± 0.3 s, P < 0.05) were increased in both hind paws after unilateral neonatal incision. Neonatal perioperative sciatic nerve blockade prevented injury-induced alterations in RVM descending control. Conclusions: Neonatal surgical injury alters the postnatal development of RVM descending control, resulting in a predominance of descending inhibition and generalized reduction in baseline reflex sensitivity. Prevention by local anesthetic blockade highlights the importance of neonatal perioperative analgesia

Is Cloud RAN a Feasible Option for Industrial Communication Network?

Cloud RAN (C-RAN) is a promising paradigm for the next generation radio access network infrastructure, which offers centralised and coordinated base-band signal processing in a cloud-based BBU pool. This requires extremely low latency responses to achieve real-time signal processing. In this paper, we analysed the challenges to introduce cloud native model for signal processing in C-RAN. We studied the difficulties of achieving real-time processing in a cloud infrastructure by addressing its latency-constraint. To evaluate the performance of such a system, we mainly investigated a massive MIMO pilot scheduling process in a C-RAN infrastructure under a factory automation scenario. We considered the stochastic delays incurred by the cloud execution environment as the main constraint that has has impact on the scheduling performance. We use simulations to provide insights on the feasibility of C-RAN deployment for industrial communication, which has stringent criteria to meet Industry 4.0 standards under this constraint. Our experiment results show that, concerning a pilot scheduling problem, the CRAN system is capable of meeting the industrial criteria when the fronthaul and the cloud execution environment has introduced latency in the order of milliseconds

Demonstration: A cloud-control system equipped with intrusion detection and mitigation

The cloud control systems (CCs) are inseparable parts of industry 4.0. The cloud, by providing storage and computing resources, allows the controllers to evaluate complex problems that are too computationally demanding to perform locally. However, connecting physical systems to the cloud through the network can provide an entry point for attackers to infiltrate the system and cause damage with potentially catastrophic consequences. Hence, in this paper, we present a demo of our proposed security framework for CCs and demonstrate how it can detect attacks on this system quickly and mitigate them

Massive MIMO Pilot Scheduling over Cloud RAN

Cloud-RAN (C-RAN) is a promising paradigm for the next generation radio access network infrastructure, which offers centralized and coordinated base-band signal processing. On the other hand, this requires extremely low latency fronthaul links to achieve real-time centralized signal processing. In this paper, we investigate massive MIMO pilot scheduling in a C- RAN infrastructure. Three commonly used scheduling policies are investigated with simulations in order to provide insight on how the scheduling performance is affected by the latency incurred by the C-RAN infrastructure

Demonstration: A cloud-control system equipped with intrusion detection and mitigation

The cloud control systems (CCs) are inseparable parts of industry 4.0. The cloud, by providing storage and computing resources, allows the controllers to evaluate complex problems that are too computationally demanding to perform locally. However, connecting physical systems to the cloud through the network can provide an entry point for attackers to infiltrate the system and cause damage with potentially catastrophic consequences. Hence, in this paper, we present a demo of our proposed security framework for CCs and demonstrate how it can detect attacks on this system quickly and mitigate them

Punctual Cloud : Unbinding Real-time Applications from Cloud-induced Delays

Cloud computing has become a prominent technology for the computing paradigm in various industrial sectors nowadays. For most industrial applications to perform in real-time, the support of periodic computing is required. However, it remains a challenge when the computing is executed in a cloud, since both the network connection and the cloud environment are uncertain. In this paper, we propose a new architecture to deploy real-time applications in the cloud. We call it punctual cloud. We detail the implementation and demonstrate how punctual cloud is deployed in a cloud-native manner on Kubernetes. We evaluate the system's performance with a real-time resource allocation problem and show that, compared to a system without punctual cloud, which has maximum 40% punctual deliveries, our proposed architecture can attain over 90% responses to be delivered punctually for the application, while also being capable of remedying the performance degradation caused by long and uncertain response delays in the system