In this work we introduce a defeasible Description logic for abductive reasoning. Our proposal exploits a fragment of a probabilistic extension of a Description logic of typicality, whose semantics corresponds to a na...
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Programmable logic Controller plays a pivotal role in the operation of Industrial Control Systems, which are widely used to monitor and control critical infrastructure and manufacturing processes. However, the rise of...
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Programmable logic Controller plays a pivotal role in the operation of Industrial Control Systems, which are widely used to monitor and control critical infrastructure and manufacturing processes. However, the rise of Industry 4.0, coupled with the increasing sophistication of cyber threats poses a significant risk to the security of PLC. This study implements a wide range of attacks on a PLC, including Code Injection, Man in the Middle, and a Denial-of-Service attack. The study further scrutinizes the impact of these attacks on the performance of the PLC with a view to developing effective security measures to mitigate cyber risks in Operational Technology systems. The study employs throughput and round trip time as the key metrics to evaluate PLC performance under normal conditions and during cyberattacks. The results indicate a significant degradation in the PLC performance metrics during the attacks, with DoS having the highest impact followed by Man in the Middle attack. These results highlight the need for robust cybersecurity measures to secure PLC from potential cyber threats. Copyright (C) 2024 The Authors.
This article analyzes the usage in the programming of ChatGPT, a natural language processing tool, along with how it may enhance teamwork, communication, and code quality. ChatGPT is an effective tool for developers s...
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Software-defined networking and network function virtualization have brought unparalleled flexibility in defining and managing network architectures. With the widespread diffusion of cloud platforms, more resources ar...
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ISBN:
(纸本)9789819608072;9789819608089
Software-defined networking and network function virtualization have brought unparalleled flexibility in defining and managing network architectures. With the widespread diffusion of cloud platforms, more resources are available to execute virtual network functions concurrently, but the current approach to defining networks in the cloud development is held back by the lack of tools to manage the composition of more complex flows than simple sequential invocations. In this paper, we advocate for the usage of choreographic programming for defining the multiparty workflows of a network. When applied to the composition of virtual network functions, this approach yields multiple advantages: a single program expresses the behavior of all components, in a way that is easier to understand and check;a compiler can produce the executable code for each component, guaranteeing correctness properties of their interactions such as deadlock freedom;and the bottleneck of a central orchestrator is removed. We describe the proposed approach and show its feasibility via a case study where different functions cooperatively solve a security monitoring task.
Plenty of unconventional computing techniques aim to compete with, if not outperform, traditional computers in solving high-complexity problems. The classical von Neumann computing architecture depends on centralized ...
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ISBN:
(数字)9781665452250
ISBN:
(纸本)9781665452250
Plenty of unconventional computing techniques aim to compete with, if not outperform, traditional computers in solving high-complexity problems. The classical von Neumann computing architecture depends on centralized and sequential data processing, while biological nervous systems work on principles of distributed, parallel, and event-driven operations. Spiking or oscillation based computing is emerging as a valuable candidate on implementing these principles in circuit level. In this work we are exploiting the unipolar behavior of fabricated CBRAM devices to design a memristor-based oscillator capable of performing computations through oscillation interactions. A compact physical CBRAM model has been utilized, which has been fitted in the fabricated devices, to extract an accurate and realistic circuit simulation.
A coordinated control method integrating emergency brake and direct yaw moment control (DYC) for distributed vehicles is established. The model predictive control (MPC) framework incorporates motor characteristics as ...
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We introduce a logic for representing the deontic notion of knowingly complying -associated to an agent's conciousness of taking a normative course of action for achieving a certain goal. Our logic features an ope...
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Obstacle avoidance in dense obstacle environments is difficult to be both efficient and effective owing to the characterics of the nonlinear optimization problems. This article proposed an Efficient Collision-Free Dua...
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Road pavement anomalies can result in many negative effects such as damages to vehicles, poor ride quality, additional ride time and road traffic accidents. Therefore it is important to regularly monitor and maintain ...
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ISBN:
(纸本)9798350346138
Road pavement anomalies can result in many negative effects such as damages to vehicles, poor ride quality, additional ride time and road traffic accidents. Therefore it is important to regularly monitor and maintain roads, according to the standards. The traditional methods of road anomaly detection are expensive, time-consuming, and require the supervision of experts. Crowdsourcing systems provide an inexpensive and robust solution to overcome these challenges in traditional approaches. This paper proposes a platform to identify and classify road anomalies from crowdsourced accelerometer smartphone data, adjusting to different vehicle speeds and other characteristics. The collected accelerometer data is preprocessed using noise filtering and reorientation techniques and the anomalies are identified through a fuzzy logic approach and further classified based on the anomaly severity using machine learning models. The results from the conducted experiments suggest that the proposed method is capable of successfully identifying and classifying anomalies from crowdsourced data.
Mobile applications have been widely used in people's daily life, and lots of data is generated in use of these mobile applications. These data including various context elements and contains rich user information...
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ISBN:
(纸本)9798350319910
Mobile applications have been widely used in people's daily life, and lots of data is generated in use of these mobile applications. These data including various context elements and contains rich user information. How to construct user features and discover user requirements from these data is vital for developer to improve the mobile application and providing smartly service for users. Therefore, a user feature construction and requirements generation method is proposed in this study. The main constructions of the study including three parts. Firstly, a time smoothing strategy is proposed to assist the generation of users' time-related features. Secondly, a fuzzy logic based method is proposed to generate user requirements. Thirdly, a tool is developed to automate and standardize the method. Finally, an experiment is conducted, and the results show the method is effective.
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