Distributed Denial of Service (DDoS) attacks are a global security concern, driven by the rapid digital transformation and the widespread adoption of 5G networks across industries. As networks connect more devices to the Internet, enabling use cases such as the industrial Internet of Things (IoT), the attack surface grows. Thus, applying deep learning techniques presents a promising approach for detecting DDoS attacks. For example, using the CIC-DDoS2019 dataset, a Convolutional Neural Network (CNN) model with multi-head attention achieved 97% accuracy. With a 5G slice-based dataset, the model achieved an accuracy of 91%. These results highlight the potential of CNNs as a scalable approach to mitigating DDoS threats. Beyond improving detection accuracy, this method enables real-time identification of attacks, supporting a proactive defense against evolving cybersecurity threats. The findings demonstrate that CNNs can help secure critical infrastructure, including IoT devices, telecommunications systems, and other networked services. Implementing such solutions enhances network security and strengthens resilience against emerging challenges.

Summary Model‐based testing (MBT) relies on models of the system's behaviour to generate abstract tests. Testers can reuse formal models using MBT to increase confidence in critical systems (e.g., medical and avionic systems). In this article, we investigate the current abstract test generation approaches for CPN to provide insights for testers who need to select a suitable one when applying the MBT using CPN. We conduct a systematic literature review to investigate the existing abstract test generation approaches designed for CPN. Subsequently, focusing on specific implementations and advantages/disadvantages, we experiment with formal models of medical systems during our empirical analysis to improve the discussion on existing abstract test generation approaches for CPN. Our study shows that CPN provides reliable tests quickly, depending on the abstract test generation approach applied.

Abstract A cyber‐physical system‐of‐systems (CPSoS) can be defined as a system‐of‐systems (SoS), composed of several operable and autonomous constituent systems (CSs) that are themselves cyber‐physical systems (CPSs). A main challenge in integrating CPSoS to function as a single integrated system is the autonomy of its components, which may result in undesirable, unsecure, or even unsafe situations. In this paper, we advocate that in order to facilitate the integration of CPSs within the overall context of their CPSoS, we may need to adjust their level of autonomy in a way that enables them to perform their activities and avoid undesirable, unsecure , and unsafe situations. Reducing such situations surely contributes to the dependability of the CPSoS. In particular, we propose a novel model‐based approach for modeling and analyzing the autonomy levels of CPSs based on their awareness concerning their operational environment as well as their capability to react in a timely, secure, and safe manner while performing their activities. The model is further described in a UML profile and applied to represent activities for autonomous driving scenarios. Using a driving simulator, we implement such models on a target vehicle, and we show the resulting safety improvement, especially in terms of reduced collisions.

Insulin infusion pumps are safety-critical systems that require the evaluation of government regulatory agencies (e.g., FDA) before commercialization. This paper presents a Coloured Petri Nets (CPN) reference model of insulin infusion pump control systems to assist manufacturers to generate safety evidence and evaluate quality for certification purposes. It also describes a case study on the ACCD-CHECK Spirit system version 2.XX to evaluate the CPN model. Therefore, the reference model is available and verified. Additionally, the case study is useful to show how manufacturers can reuse it during a certification process. The main contribution of this paper consists on a project artifact to decrease costs and development time of insulin infusion pump control systems, in addition to increase confidence on safety properties.

Bio-medical signal acquisition systems (or simply bio-medical systems) are commonly used during the diagnosis, monitoring, and treatment of patients. The Electrocardiograph (ECG) is an example of this type of system. It is necessary to submit bio-medical systems to regulatory agencies for certification. Regulatory agencies conduct evaluations seeking the commercialization of high-quality systems. In a previous work, we specified an ECG model by integrating the Coloured Petri Nets (CPN) and MATLAB® tools. However, this introduced an external component dependency that limited the application and re-usability of the model during the certification process. We present in this paper a mixed-radix Fast Fourier Transform (FFT) algorithm based on CPN aiming to assist the design of bio-medical systems using CPN. We improved the design of an ECG model to show how the mixed-radix FFT algorithm solves the previous limitations, and to evaluate the effectiveness of a CPN/ML implementation. The comparison of a system under development with similar certified systems is commonly accepted by regulatory agencies. The replacement of a similar system by the open source CPN/Tools software and the available reference model can decrease costs, and development and certification time.

A research work is reproducible when all research artifacts such as as text, data, figure and code are available for independent researchers reproduce the results. In this paper, we present a reproducible gait analysis to track Parkinson's Disease evolution by monitoring walking abnormalities. Weapplied Principal Component Analysis into gait data to detect user's abnormalities that may indicate the progression of Parkinson's Disease. We validated our approach with a public database of foot sensor data, which includes vertical ground reaction force records of subjects with healthy gait and Parkinson's Disease patients. We used the euclidean distance asdata classifier. We reached a classification accuracy of 81.00% with leave-one-out cross-validation, which demonstrates the feasibility of our approach for tracking PD's symptoms based on user gait. All relevant data to reproduce our results are available in a public web page.

Parkinson's disease (PD) is a degenerative neurological disorder. It causes motor symptoms such as resting tremor, bradykinesia and gait disorders. The disease's progressive nature requires continuous monitoring of the motor symptoms to assist the neurologist in managing medication. With this purpose, Health Monitoring Systems (HMS) are used as a decentralized healthcare approach. On the other hand, most patients reject the current HMS solutions because they are invasive and stigmatizing. In this work, we present a non-invasive HMS for PD motor symptoms based on games. Because of the nature of games, the approach is able to collect data from patients without reminding them that they are under a disease's treatment. We validated our approach with 30 research subjects divided between PD group and Control group. We used Support Vector Machine (SVM) to identify the occurrence of PD's bradykinesia motor symptoms and reached a classification precision of 92.31%. Furthermore, 90,00% of the patients approved our HMS considering it as non-invasive and easily integrated into their routine.

Electrocardiography (ECG) devices record the heart's electrical activity. These devices can be part of e-Health systems used to diagnose, treat, and monitor patients with cardiovascular diseases. Manufacturers must show to regulatory agencies the effectiveness of devices during the certification process. Nowadays, simulators are used to test and calibrate ECG devices. Besides, manufacturers can use formal methods to specify ECG device requirements to increase dependability. In this context, it is necessary to validate formal models to provide confidence in the specification. Validations can be performed comparing models and physical devices using the same data generated from simulators. However, the simulators available in the market do not enable one to control the amplitude and frequency of signals. This makes difficult the use of the same data into formal models and physical devices. We present in this paper an open and low cost ECG simulator to validate models of ECG devices. The simulator generates ECG signals from digitized characteristic and noise waveforms. We analyzed the quality of the simulator qualitatively using the MATLAB and the Proteus software.

Physicians analyze results obtained from biomedical signal acquisition devices to treat and diagnose patients with acute and chronic diseases. Therefore, results must be accurate to avoid errors during the evaluation of patients. Manufacturers should develop biomedical signal acquisition devices in order to be safe and effective. However, there are still problems related to safety and effectiveness in this type of device according to regulatory agencies such as the US Food and Drug Administration (FDA). In this context, manufacturers should use techniques to perform the formal specification, validation, and simulation to increase the dependability of devices. We propose in this paper a methodology for modeling and simulation of biomedical signal acquisition devices aiming to provide a reliable way to perform tests during its development. A case study of a non-invasive ECG device is presented as a use scenario of the methodology.

Medical devices help physicians to diagnose and treat patients at home and healthcare facilities. However, when complexity of devices grows, new risks can also arise and put users in hazard situations. Manufacturers must develop medical devices taking into account ways to mitigate risks and avoid injuries to users. In this context, regulatory agencies impose the ISO 14971 standard during the risk management of medical devices. The ISO 14971 specifies risk management process activities and suggests manufacturers to use techniques such as the Failure Mode Effects and Criticality Analysis (FMECA). Nevertheless, the ISO 14971 is a subjective document written in natural language. Therefore, the correct interpretation of its requirements depends on the understanding of manufacturers. This paper presents a Colored Petri Nets (CPN) model of the risk management process based on the ISO 14971 and FMECA technique. The model aims to deal with the subjectivity problem of the ISO 14971. Besides, we verified and validated abstract and detailed versions of the model using model checking and simulation results to increase confidence on the specification.

Electrocardiography devices are used to perform biomedicai signal acquisition from the cardiac electrical activity. Regulatory agencies, such as Food and Drug Administration (FDA) on the USA and National Agency for Sanitary Vigilance (ANVISA) in Brazil, classify Electrocardiography devices as medium risk Class 2 devices. Manufacturers must certify medical devices before commercialization according to some requirements. Prescriptive standards and clinical tests are examples of these requirements. However, problems are still common, and can cause injuries or death to patients. FDA recorded 1.210 computer-related recalls between 2006 and 2011, being 90.5 percent of Class 2. In this context, we are concerned with the use of formal methods to increase the confidence on these medical devices. This paper presents a Colored Petri Nets (CPN) model of a surface Electrocardiography device in order to aid manufacturers to increase the confidence during the devices' development and the certification process.

A surface Electrogastrography (EGG) system uses electrodes placed on the abdomen of the patient to verify the gastric myoelectric activity. Physicians use EGG systems to aid the patients' diagnosis with gastric disorders. In this context, the results of the EGG examinations must be accurate to avoid errors on the patient's evaluation. The medical device and the software to control the device must be safe and effective. This means that not only software behaviors must be verified, but also hardware components. Regulatory agencies verify the conformance of medical systems with these requirements. Nowadays, manufactures show this conformance performing activities such as risk management and clinical tests on devices. We present a methodology using Colored Petri Nets (CPN) in the requirements engineering to model software and hardware behaviors. This includes challenges such as which types of electrical components have to be modeled, and the level of abstraction of the models. Besides, a Matlab application is used to show model simulation results from the proposed CPN models.

The reliability on Safety Instrumented Systems (SIS) is critical for the safe operation of many industrial applications. In particular, SIS play an important role in oil and gas processing plants. SIS are responsible not only for the continuous operation of the plant, it also keeps the plant in a safe state, avoiding damages to the environment and minimizing risks to employees. Therefore, the correct behavior of such systems is an important goal to achieve when building industrial plants. Verification and testing of SIS programs is a very hard task to accomplish. This happens mainly for two reasons. First, testing the real system is very expensive and sometimes it may take a huge amount of time, weeks or even months. Second, those systems deal with a huge number of variables. It is not always possible for a human tester to check if all of them are correct when performing tests. Providing an automatic and formal testing approach for such systems is an important contribution for the development of such systems. In this work we introduce a new method for generating test cases for SIS programs running on Programable Logic Controller (PLC). As we did on previous work, ISA 5.2 diagrams are used as specification of the systems, but now we are using a hardware-in-the-loop technique, and the target artifact is a software running on a PLC. To avoid the execution of redundant tests, we introduced a new test case generation algorithm that is based on equivalence classes. Finally, we discussed a study case in which our method is used to detect error, that were introduced on purpose, on a simple system.

In this work, the problems and respective solutions for dealing with two of the most basic questions regarding handoff management are presented: to avoid total loss of connectivity; and to reduce overall time of the handoff procedure. The focus of this research is on handoff in WPANs for real-time applications. Therefore, Bluetooth stands out as the ideal technology for case study due to its particular alignment with the behavior and requirements of the WPAN’s network model. Bluetooth’s inquiry and paging operations may be calibrated for achieving fast discoveries and connections while scatternets may be used to avoid total loss of connectivity. However, the usage of scatternets and calibration of inquiry and paging unveil a series of challenging aspects when applied along with real-time applications. Such challenges are the priority of inquiry and paging data traffic over users’ applications and unpredictability of scatternet behavior. The key point to overwhelm these difficulties is to understand how they affect the real-time data transfers. In this article a set of discussions and experiments that demonstrate how inquiries, pagings and scatternets can aid achieving the goals of fast and uninterrupted handoffs, as well as the tenuous traps and tradeoffs behind such operations and configurations over real-time applications performance are presented.

Safety Instrumented Systems (SIS) are usually designed to prevent accidents, avoid undesirable situations and guarantee continuous operation of oil and gas production systems. An interruption in the operation can be caused by faults in sensors and/or actuators. Hence, SIS are usu ally integrated to the supervisory control system in order to use the information from sensors to prevent such unde sirable situations. In this scenario, it is important to be able to validate the SIS implementation against its spec ification in order to increase the reliability of the system. In this work a technique to improve the dependability of SIS is introduced. A method to obtain a timed automata from a ISA 5.2 specification is presented and applied to a case study provided by Petrobras (Brazilian oil company). Finally, an approach to perform automatic testing of the implementation using the generated model is discussed. The method introduced here is based on the use of the Up paal model checker and the Uppaal-TRON testing tool.

We present the tool Ticc ( Tool for Interface Compatibility and Composition ). In Ticc , a component interface describes both the behavior of a component, and the component’s assumptions on the environment’s behavior. Ticc can check the compatibility of such interfaces, and analyze their emergent behavior, via a symbolic implementation of game-theoretic algorithms. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.