Smart Cyber Research Articles

Advancing Smart Cyber Physical System with Self-Adaptive Software

The proposed integration of DevOps and Digital Twins presents a ground-breaking approach to enhancing the resilience and adaptability of Cyber-Physical Systems in the context of Industry 4.0 and the forthcoming Industry 5.0 era. This research explores the synergistic potential of DevOps principles in fostering collaborative and efficient development and maintenance processes for embedded systems and distributed control systems within CPS. Concurrently, the utilization of Digital Twins offers real-time monitoring and simulation capabilities, heralding a shift towards a human-centric approach to CPS operation. The emphasis on self-adaptive systems within CPS anticipates the ability to address dynamic conditions and unforeseen challenges, paving the way for the evolution of resilient and responsive industrial systems. This research explores the integration of DevOps and Digital Twins in the context of Industry 4.0 and anticipates the requirements of Industry 5.0, emphasizing the need for resilient and human-centric Cyber-Physical Systems. This study investigates the integration of DevOps and Digital Twins to enhance the resilience and adaptability of Cyber-Physical Systems in the context of Industry 4.0 and Industry 5.

SURG-05. HYPER SMART CYBER OPERATING THEATER TO PERFORM FUTURE PREDICTIVE SURGERY

Abstract Gliomas are invasive tumors in which the extent of tumor resection is believed to correlate with prognosis. However, aggressive extraction risks deterioration due to functional tissue damage. One strategy for resolving this conflict is the technology of new modalities. The basis of this technology is digital transformation (DX), converting analog information called tacit knowledge on experiences into digital information for explicit knowledge. In the future, we will develop an AI system, generated by DX data, and support intraoperative decision-making with highly accurate future predictions. In order to realize this future-prediction surgery, we have developed a smart cyber operating theater (SCOT) with intraoperative MRI. More than 20 medical devices are connected by middleware (OPeLiNK®), and navigation spatial records and time-synchronized data are displayed on the strategy desk. A hyper version of SCOT has currently performed 277 surgeries, including 262 gliomas, 51 awake craniotomies, and 88 photodynamic therapies. For WHO grade 4 glioblastomas, we try to remove contrast-enhanced areas, and for grade 2/3 gliomas, to formulate an extraction strategy for each 3 genotypes, we perform preoperative AI prediction and intraoperative genetic diagnosis for genotype. Intraoperative flow cytometry is useful to predict the genotype (oligodendroglioma) and determine the extent of resection in some cases. Time-synchronized data showed points of surgical maneuvers causing speech arrest in awake surgery and decreases in MEP, and provided feedback during and after surgery. AI technology is also used for preoperative surgical simulation (GRID®), artifact reduction in iMRI, and brain shift prediction. The hyper SCOT supports the optimal removal of gliomas through intraoperative future prognosis prediction through device data and AI analysis. Furthermore, we are developing an AI robot (AIREC) that performs surgery through deep predictive learning, with the aim of commercialization after 2040. This work was partially supported by JST [Moonshot R&D] [Grant Number JPMJMS2031].

Village Open Data Implementation: Lesson Learned from Alang-alang Vilalge, Madura

Alang-alang village is one of the villages in Bangkalan, Madura, near the Suramadu bridge. This village has a vision to be a smart cyber village. However, the application of open data need to be explored, especially in the village area. We just found the implementation of the open data application in Wonosobo and Bantul. Therefore, researching implementing Open data applications at the village level is important. This study aims to capture the open data application 1.0 implementation for the Alang-Alang Village Government. It will explore the richness of the village open data implementation's success factors, challenges, and uniqueness. This research contributes by providing a lesson learned and a novel model for Village Open Data Implementation based on the case study of the Alang-alang village open data application. Moreover, this research also has some implications for knowledge and practice for other villages’ governments, researchers, practitioners, and village ministries worldwide, such as the implementation model can be adopted for other contexts and villages. In the body of knowledge, it develops a body of e-Government and smart village knowledge and research fields. Based on this case study, there are some success factors for village open data implementation: Vision and commitment of the village leader, regulation, people’s support and participation, infrastructure, and digital literacy.

Threat modeling in smart firefighting systems: Aligning MITRE ATT&CK matrix and NIST security controls

Industrial automation technologies are envisioned as multi-device systems that are constantly interacting with one another and with enterprise systems. In these industrial systems, the industrial internet of things (IIoT) significantly improves system efficiency, scalability, ease of control, and monitoring. These benefits have been achieved at the cost of greater security risks, thus making the system vulnerable to cyberattacks. Historically, industrial networks and systems lacked security features like authentication and encryption due to intended isolation over the Internet. Lately, remote access to these IIoT systems has made an attempt of holistic security alarmingly critical. In this research paper, a threat modeling framework for smart cyber–physical system (CPS) is proposed to get insight of the potential security risks. To carry out this research, the smart firefighting use case based on the MITRE ATT&CK matrix was investigated. The matrix analysis provided structure for attacks detection and mitigation, while system requirement collection (SRC) was applied to gather generic assets’ information related to hardware, software and network. With the help of SRC and MITRE ATT&CK, a threat list for the smart firefighting system was generated. Conclusively, the generated threat list was mapped on the national institute of standards and technology (NIST) security and privacy controls. The results show that these mapped controls can be well-utilized for protection and mitigation of threats in smart firefighting system. In future, critical cyber–physical systems can be modeled upon use case specific threats and can be secured by utilizing the presented framework.

Review of smart cyber city: keys requirements, tools and issues

With the continuous growth of the urban population, the world is confronting numerous challenges in the near future of cities, related to environmental, economic and social aspects (e.g., traffic congestion, air pollution, waste management, etc.). The smart cyber city concept is introduced as a solution to achieve sustainability, effective management of energy, and smart living. Designing such complex systems with such features is an equally complex challenge. The cyber physical system (CPS) and the Internet of thing (IoT) are keys to achieve the realization of current smart city. In this paper, a survey of smart city vision is given while highlighting the potential benefits of a smart cyber city. A bibliometric network with Vosviewer software was created in order to select the most significant papers. It reviews smart city's key requirements and smart city enabling technologies. It then highlights the potential role of CPS and IoT. Finally, an outline of future research areas is given.

A Novel Framework for Smart Cyber Defence: A Deep-Dive Into Deep Learning Attacks and Defences

A Novel Framework for Smart Cyber Defence: A Deep-Dive Into Deep Learning Attacks and Defences

SeVuc: A study on the Security Vulnerabilities of Capsule Networks against adversarial attacks

Capsule Networks (CapsNets) preserve the hierarchical spatial relationships between objects, and thereby bear the potential to surpass the performance of traditional Convolutional Neural Networks (CNNs) in performing tasks like image classification. This makes CapsNets suitable for the smart cyber–physical systems (CPS), where a large amount of training data may not be available. A large body of work has explored adversarial examples for CNNs, but their effectiveness on CapsNets has not yet been studied systematically. In our work, we perform an analysis to study the vulnerabilities in CapsNets to adversarial attacks. These perturbations, added to the test inputs, are small and imperceptible to humans, but can fool the network to mispredict. We propose a greedy algorithm to automatically generate imperceptible adversarial examples in a black-box attack scenario. We show that this kind of attacks, when applied to the German Traffic Sign Recognition Benchmark and CIFAR10 datasets, mislead CapsNets in making a correct classification, which can be catastrophic for smart CPS, like autonomous vehicles. Moreover, we apply the same kind of adversarial attacks to a 5-layer CNN (LeNet), to a 9-layer CNN (VGGNet), and to a 20-layer CNN (ResNet), and analyze the outcome, compared to the CapsNets, to study their different behaviors under the adversarial attacks.

The Current Status in Intraoperative Image-Guided Neurosurgery Associated with Progressive Operating Rooms: A Retrospective Analysis

Shinshu University Hospital has advanced operating rooms including a mobile computed tomography (mCT) room, Smart Cyber Operating Theater (SCOT) with intraoperative magnetic resonance imaging, hybrid operating room (hOR) with intraoperative image-guided surgery, and conventional operating rooms. We investigated the characteristics of cases assigned to each operating room. Five hundred forty neurosurgery cases from January 2018 to April 2021 were analyzed. We analyzed the selection of operating room according to pathology, surgical device requirement, and urgency, and we examined associations between operating room characteristics and these factors. Neurological surgeries were performed in an mCT room, an hOR, a SCOT, and a conventional operating room in 333 (61.7%), 64 (11.9%), 49 (9.1%), and 94 (17.4%) cases, respectively. mCT rooms were more frequently selected than other rooms for vascular/extra-axial tumors, which have a lower need for intraoperative image guidance. Spinal surgeries with segment diagnosis or intraoperative bone removal tended to be performed in the hOR. The rate of SCOT use tended to be higher for intra-axial tumors with poorly circumscribed borders than for vascular/extra-axial tumors. Endoscopic procedures were more frequently performed in the SCOT and mCT rooms than in hORs and conventional operating rooms. Emergency surgeries were often performed in the conventional operating rooms, even in cases where SCOT and hOR seemed suitable. Intraoperative image-guided surgeries were performed according to the characteristics of each operating room best suited for various diseases and operative methods. Further research is needed to prove whether operating room selection improves neurosurgical outcomes.

Guest Editorial: Computational Intelligence for Human-in-the-Loop Cyber Physical Systems

The papers in this special section focus on human-in-the-loop cyber-physical systems. Recent advances in computational intelligence, real-time computing and control, have given momentum to Humanin-the-Loop Cyber Physical Systems (HitLCPS) to enable gamechanging communication and collaboration paradigms that operate in connection with humans’ natural behaviour patterns. Despite the ongoing advancement of computational intelligence techniques for analyzing the interactions between the cognitive and cyber domains, there are growing concerns regarding the security, privacy, and safety of humans when they interact with smart cyber physical environments (IoT ecosystems). The large-scale integration of heterogeneous IoT devices to manage and control a wide variety of sensors and settings will hugely increase the attack surface and the scope for misconfigurations. These could lead to unsafe or conflicting behaviour of various devices and subsystems, which in turn, can place the human in unsafe and hazardous situations, both mentally and physically. It is still unclear how to design optimized collaborative systems between people and machines in a scalable manner, how to design triggers for pro-active engagement and disengagement, and how to handle the consequences of implied actions. For example, when the system misbehaves as a result of erroneous data, it is important to have real-time rules that can guarantee a fail-safe state for the HitLCPS. The verification of operations in a large HitLCPS can be very complex due to the evolving nature of human-in-the-loop networks both in terms of physical aspects and the operational environment. Therefore, understanding the semantics of HitLCPS and the context of control behaviour is critical to detect or entirely avoid incorrect configurations and build a proactive resilience and a reactive defence against evolving threats.

Intraoperative Image-Guided Surgery for Gliomas in the Smart Cyber Operating Theater (SCOT): A Preliminary Clinical Application

Various devices exist for glioma image-guided surgery to improve tumor resection. These devices work as stand-alone units, making the flow of operative information complicated and disjointed. A novel networked operating room, the Smart Cyber Operating Theater (SCOT), has been developed, integrating stand-alone medical devices using the OPeLiNK communication interface. We report and evaluate the impact of SCOT for glioma surgery and our initial experiences. Patients with gliomas who underwent tumor resection in SCOT between July 2018 and June 2021 were retrospectively reviewed. Various types of intraoperative information were integrated, managed, and shared with the surgical strategy desk using OPeLiNK. Patients' demographics, tumor characteristics, treatment details, and outcomes were obtained. The impact of the SCOT system was evaluated. Twenty-seven patients, with a mean age of 48.6 years (range, 13-88 years), met the inclusion criteria. We successfully completed all the surgical procedures using SCOT. The mean operation time was 420.6 minutes (range, 225-667 minutes).Gross total resection was accomplished in 13 patients (48.1%), subtotal resection in 4 (14.8%), and partial resection in 10 (37.0%). The main surgeon in the operating room and other neurosurgeons at the strategy desk shared and discussed the information in real time during the procedures. The use of SCOT was shown to be safe and feasible in glioma surgery. This study suggests that SCOT may improve surgical outcomes and educational impact by sharing information in real time with the strategy desk.

STMO-14 Clinical experience of brain tumor surgery using middleware “OPeLiNK”

PURPOSEThe removal of brain tumors requires not only imaging information such as MRI and navigation systems, but also a variety of other information such as neurological function and biological information. To integrate this information, a novel operating room, “Smart Cyber Operating Theater (SCOT)”, which connects the medical devices in the operating room via a network has developed. In this SCOT, the intraoperative information is time-synchronized, recorded, and stored by the middleware “OPeLiNK”. Clinical experience of brain tumor surgery using OPeLiNK in our institute is reported.MethodsBrain tumor surgeries performed at SCOT, which had been started since July 2018, was enrolled. In all surgeries intraoperative information was integrated by OPeLiNK. Surgical procedure was discussed between main surgeon and supervising surgeon in the Strategy Desk through OPeLiNK intraoperatively, if necessary. Clinical and radiological data from patients who underwent resection at SCOT were analyzed retrospectively.ResultsSixty patients were involved. Histopathological diagnosis was glioma in 29 patients, pituitary adenoma in 29 patients, acoustic tumor in 1 patient and intravascular lymphoma in 1 patient. Intraoperative discussion with Strategy Desk through OPeLiNK was useful for not only surgeons but also for medical staff in operation room. Advice for extent of resection and craniotomy from Strategy Desk was conducted by OPeLiNK using conversation and drawing. Intraoperative comment was useful for postoperative review. OPeLiNK, which display multiple intraoperative information, was also used at postoperative conference.ConclusionWe have reported clinical experience with OPeLiNK for brain tumor surgery in our institute. OPeLiNK was useful for not only sharing intraoperative information with doctors outside the operation room but also postoperative review and education for young doctors.

Special Issue on Smart Applications and Data Analysis for Smart Cyber–Physical Systems

Special Issue on Smart Applications and Data Analysis for Smart Cyber–Physical Systems

Security framework for smart cyber infrastructure

Security framework for smart cyber infrastructure

Smart City Healthcare Cyber Physical System: Characteristics, Technologies andChallenges.

The recent pandemic has demanded a strong and smart healthcare system which can monitor the patients efficiently and handle the situation that arises from the outbreak of the disease. Smart healthcare cyber physical systems are the future systems as they integrate the physical and cyber world for efficient functioning of medical processes and treatment through external monitoring and control of patients, medical devices and equipment for continuous communication and information exchange of physiological data. Technologies like Internet of Things, Machine learning and Artificial Intelligence have given birth to smart cyber physical systems like Smart Healthcare Systems, Smart Homes, Smart Vehicular Systems and Smart Grid. Such systems are interdisciplinary in nature with multitude of technologies contributing to its effective working. This paper presents a case study on healthcare cyber physical systems presenting its characteristics, role of various technologies in its growth and major challenges in successful implementation of cyber physical medication systems.

Targeting uncertainty in smart CPS by confidence-based logic

Since Smart Cyber–Physical Systems (sCPS) are complex and decentralized systems of dynamically cooperating components, architecture-based adaptation is of high importance in their design. In this context, a key challenge is that they typically operate in uncertain environments. Thus, an inherent requirement in sCPS design is the need to deal with the uncertainty of data coming from the environment. Existing approaches often rely on the fact that an adequate model of the environment and/or base probabilities or a prior distribution of data are available. In this paper, we present a specific logic (CB logic), which, based on statistical testing, allows specifying transition guards in architecture-based adaptation without requiring knowledge of the base probabilities or prior knowledge about the data distribution. Applicable in state machines’ transition guards in general, CB logic provides a number of operators over time series that simplify the filtering, resampling, and statistics-backed comparisons of time series, making the application of multiple statistical procedures easy for non-experts. The viability of our approach is illustrated on a running example and a case study demonstrating how CB logic simplifies adaptation triggers. Moreover, a library with a Java and C ++ implementation of CB logic’s key operators is available on GitHub.

The Latest Glioma Surgical Support Devices and Intraoperative Applications of MRI

We previously proposed an information-guided surgery based on objective intraoperative information to achieve a high precision and maximum resection of gliomas. In 2000, an "intelligent operating room" was constructed and put into operation as a place to train new "eyes," "hands," and "brains" for surgeons. Based on the positive experience from this room, it was subsequently developed into the Smart Cyber Operating Theater (SCOT), and from October 2019, Hyper SCOT was introduced at Tokyo Women's Medical University Hospital. This report introduces the latest surgical support devices that we have implemented in glioma surgery with Hyper SCOT. As an intraoperative image information support device, intraoperative MRI can correct brain shift, visualize residual tumor, and aid in performing maximal tumor resection, thereby greatly contributing to surgical results. As an intraoperative histological information support device, intraoperative flow cytometry can evaluate the presence of tumor cells and malignancy based on the measurement of the amount of DNA in tumor cells, and also predict the prognosis intraoperatively. Photodynamic therapy has been shown to be effective in clinical trials as an intraoperative treatment support device, and it is covered by insurance. Therefore, it is expected to be established as a standard treatment method for primary glioblastoma patients.

A cross-layer approach towards developing efficient embedded Deep Learning systems

With the evolution of Smart Cyber–Physical Systems (CPS) and Internet-of-Things (IoT), the number of connected (intelligent) devices is increasing at an exponential rate, and so as the data being produced by them. To process this gigantic amount of data, algorithms are being proposed that can extract information from it without much human intervention. Deep Learning (DL) is one of the fields which has recently shown significant potential towards this direction, as it allows computational models (deep neural networks) composed of multiple processing layers to learn autonomously to interpret data with the help of the back-propagation algorithm. However, state-of-the-art deep neural networks (DNNs) are highly resource-hungry. To enable the use of DNNs in resource constraint mobile devices, several optimization techniques have been proposed at different abstraction layers of the computing stack. In this paper, we highlight the main categories of the optimization techniques and present a cross-layer methodology for developing performance/energy efficient DNN-based systems. At the software level, we employ a structured pruning technique along with the quantization of inputs and network parameters to reduce the computational complexity and memory requirements for the DNN inference process. At the hardware level, exploiting the error resilience characteristics of the DNNs, we make use of functional approximations in the arithmetic modules to further improve the efficiency of DNN-based systems.

Performance evaluation of Hyperledger Fabric-enabled framework for pervasive peer-to-peer energy trading in smart Cyber–Physical Systems

The in-depth collaboration of Cyber–Physical Systems (CPSs) and smart grids constitute the novel paradigm of distributed energy trading, in which computation and process control are managed in an adaptive Peer-to-Peer (P2P) manner. To further strengthen this collaboration, Hyperledger Fabric (HF) can be prominently considered as a mean to implement next-generation secure and intelligent communication. However, implementing real-world applications on this platform may concern performance issues. For the constructive exploration of these issues, initially, we design a novel P2P energy trading framework for improving resource utilization and consequently addressing the impending electricity crisis challenge. Thenceforward, we evaluate the results based on the different system operational parameters for establishing a proof-of-concept. For determining performance bottlenecks and best-configuration, these results are investigated independently by using the Nectar Research Cloud, thereby sustaining scalability. The proposed evaluation approach will largely contribute to determining the system operational-level parameters of enterprise applications that will utilize the HF platform as their communication tool-support. In addition, a benchmark is presented based on the Hyperledger Caliper tool to facilitate application designers and developers in the form of selecting an appropriate implementation model across the two latest stable HF model versions. The illustrative CPS-enabled energy trading scenario corroborates the feasibility of the proposed framework to foster the development of HF-assisted smart P2P energy trading mechanisms.

Smart Cyber Operating Theater (SCOT) and the expansion into the ICU field

Smart Cyber Operating Theater (SCOT) and the expansion into the ICU field

Experience with the Practical Application of the iArmS Surgical Support Robot and Smart Cyber Operating Theater

Experience with the Practical Application of the iArmS Surgical Support Robot and Smart Cyber Operating Theater