569 research outputs found

    Проектування інформаційного забезпечення для оцінки якості ПЗ вбудованих систем

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    This article presents a system for evaluating the quality of embedded software using a decision system based on fuzzy logic. These approaches will improve the assessment of software quality, due to its features. This article defines the main criteria for software quality used in assessing the quality of the software. The main literature was examined, in which fuzzy logic was described, decision-making systems using fuzzy logic, as well as software quality assessment systems, including software for embedded systems. The main characteristics and properties of embedded syst ems were considered. Based on the considered characteristics and properties of embedded systems, the ranking of criteria was made, which will be further used in the software quality assessment methodology. The main criteria that are used to evaluate the quality of software were considered, and the criteria presented were distributed according to the degree of influence on the assessment of the quality of software of embedded systems. Fuzzy logic was considered, and more precisely: the basic properties of fuzzy logic and fuzzy numbers, the basic mathematical operators applied to fuzzy numbers. The system for constructing rules for the rule base, as well as the defuzzification process, built on the basis of the centroid method, is analyzed. An example of software evaluation for embedded systems was considered. In this example, linguistic variables were determined, as well as their numerical ranges, which were used for the initial assessment of the quality criteria of this software. Each range of ratings was distributed according to the influence of a criterion on software quality. The output linguistic variable and its numerical value were also determined. In the end, based on the set values, an estimate of the set software was derived. The theoretical result obtained in this article is the basis for constructing a system for evaluating software quality for embedded systems.У даній статті представлена система для оцінки якості програмного забезпечення вбудованих систем з використанням системи прийняття рішень на основі нечіткої логіки. Дані підхід дозволить поліпшити оцінку якості програмного забезпечення, за рахунок урахування його особливостей. У даній статті визначено основні критерії якості програмного забезпечення, використовувані при оцінці якості даного програмного забезпечення. Була оглянута основна література, в якій була описана нечітка логіка, системи прийняття рішень, що використовують нечітку логіку, а також системи оцінки якості програмного забезпечення, в тому числі і програмного забезпечення для вбудованих систем. Були розглянуті основні характеристики та властивості вбудованих систем. На підставі розглянутих характеристик і властивостей вбудованих систем виробилося ранжування критеріїв, які в подальшому будуть використовуватися в методиці оцінки якості програмного забезпечення. Були розглянуті основні критерії, які використовуються для оцінки якості програмного забезпечення, а також представлені критерії, які були розподілені за ступенем впливу на оцінку якості програмного забезпечення вбудованих систем. Була розглянута нечітка логіка, а точніше: основні властивості нечіткої логіки і нечітких чисел, основні математичні оператори, що застосовуються до нечітким числах. Розібрана система побудови правил для бази правил, а також процес дефазифікації, побудований на підставі центоїдного методу. Було розглянуто приклад оцінки програмного забезпечення для вбудованих систем. В даному прикладі були визначені лінгвістичні змінні, а також їх числові діапазони, які використовувалися для первісної оцінки критеріїв якості даного програмного забезпечення. Кожен діапазон оцінок був розподілений згідно впливу критерію на якість програмного забезпечення. Також була визначена вихідна лінгвістична змінна і її числове значення. В кінці, на основі заданих значень була виведена оцінка заданого програмного забезпечення. Отриманий теоретичний результат в даній статті є основою для побудови системи для оцінки якості програмного забезпечення для вбудованих системи

    Reconfigurable Antenna Systems: Platform implementation and low-power matters

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    Antennas are a necessary and often critical component of all wireless systems, of which they share the ever-increasing complexity and the challenges of present and emerging trends. 5G, massive low-orbit satellite architectures (e.g. OneWeb), industry 4.0, Internet of Things (IoT), satcom on-the-move, Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles, all call for highly flexible systems, and antenna reconfigurability is an enabling part of these advances. The terminal segment is particularly crucial in this sense, encompassing both very compact antennas or low-profile antennas, all with various adaptability/reconfigurability requirements. This thesis work has dealt with hardware implementation issues of Radio Frequency (RF) antenna reconfigurability, and in particular with low-power General Purpose Platforms (GPP); the work has encompassed Software Defined Radio (SDR) implementation, as well as embedded low-power platforms (in particular on STM32 Nucleo family of micro-controller). The hardware-software platform work has been complemented with design and fabrication of reconfigurable antennas in standard technology, and the resulting systems tested. The selected antenna technology was antenna array with continuously steerable beam, controlled by voltage-driven phase shifting circuits. Applications included notably Wireless Sensor Network (WSN) deployed in the Italian scientific mission in Antarctica, in a traffic-monitoring case study (EU H2020 project), and into an innovative Global Navigation Satellite Systems (GNSS) antenna concept (patent application submitted). The SDR implementation focused on a low-cost and low-power Software-defined radio open-source platform with IEEE 802.11 a/g/p wireless communication capability. In a second embodiment, the flexibility of the SDR paradigm has been traded off to avoid the power consumption associated to the relevant operating system. Application field of reconfigurable antenna is, however, not limited to a better management of the energy consumption. The analysis has also been extended to satellites positioning application. A novel beamforming method has presented demonstrating improvements in the quality of signals received from satellites. Regarding those who deal with positioning algorithms, this advancement help improving precision on the estimated position

    Anomaly detection with machine learning for automotive cyber-physical systems

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    2022 Spring.Includes bibliographical references.Today's automotive systems are evolving at a rapid pace and there has been a seismic shift in automotive technology in the past few years. Automakers are racing to redefine the automobile as a fully autonomous and connected system. As a result, new technologies such as advanced driver assistance systems (ADAS), vehicle-to-vehicle (V2V), 5G vehicle to infrastructure (V2I), and vehicle to everything (V2X), etc. have emerged in recent years. These advances have resulted in increased responsibilities for the electronic control units (ECUs) in the vehicles, requiring a more sophisticated in-vehicle network to address the growing communication needs of ECUs with each other and external subsystems. This in turn has transformed modern vehicles into a complex distributed cyber-physical system. The ever-growing connectivity to external systems in such vehicles is introducing new challenges, related to the increasing vulnerability of such vehicles to various cyber-attacks. A malicious actor can use various access points in a vehicle, e.g., Bluetooth and USB ports, telematic systems, and OBD-II ports, to gain unauthorized access to the in-vehicle network. These access points are used to gain access to the network from the vehicle's attack surface. After gaining access to the in-vehicle network through an attack surface, a malicious actor can inject or alter messages on the network to try to take control of the vehicle. Traditional security mechanisms such as firewalls only detect simple attacks as they do not have the ability to detect more complex attacks. With the increasing complexity of vehicles, the attack surface increases, paving the way for more complex and novel attacks in the future. Thus, there is a need for an advanced attack detection solution that can actively monitor the in-vehicle network and detect complex cyber-attacks. One of the many approaches to achieve this is by using an intrusion detection system (IDS). Many state-of-the-art IDS employ machine learning algorithms to detect cyber-attacks for its ability to detect both previously observed as well as novel attack patterns. Moreover, the large availability of in-vehicle network data and increasing computational power of the ECUs to handle emerging complex automotive tasks facilitates the use of machine learning models. Therefore, due to its large spectrum of attack coverage and ability to detect complex attack patterns, we adopt and propose two novel machine learning based IDS frameworks (LATTE and TENET) for in-vehicle network anomaly detection. Our proposed LATTE framework uses sequence models, such as LSTMs, in an unsupervised setting to learn the normal system behavior. LATTE leverages the learned information at runtime to detect anomalies by observing for any deviations from the learned normal behavior. Our proposed LATTE framework aims to maximize the anomaly detection accuracy, precision, and recall while minimizing the false-positive rate. The increased complexity of automotive systems has resulted in very long term dependencies between messages which cannot be effectively captured by LSTMs. Hence to overcome this problem, we proposed a novel IDS framework called TENET. TENET employs a novel convolutional neural attention (TCNA) based architecture to effectively learn very-long term dependencies between messages in an in-vehicle network during the training phase and leverage the learned information in combination with a decision tree classifier to detect anomalous messages. Our work aims to efficiently detect a multitude of attacks in the in-vehicle network with low memory and computational overhead on the ECU

    Preliminaries of orthogonal layered defence using functional and assurance controls in industrial control systems

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    Industrial Control Systems (ICSs) are responsible for the automation of different processes and the overall control of systems that include highly sensitive potential targets such as nuclear facilities, energy-distribution, water-supply, and mass-transit systems. Given the increased complexity and rapid evolvement of their threat landscape, and the fact that these systems form part of the Critical National infrastructure (CNI), makes them an emerging domain of conflict, terrorist attacks, and a playground for cyberexploitation. Existing layered-defence approaches are increasingly criticised for their inability to adequately protect against resourceful and persistent adversaries. It is therefore essential that emerging techniques, such as orthogonality, be combined with existing security strategies to leverage defence advantages against adaptive and often asymmetrical attack vectors. The concept of orthogonality is relatively new and unexplored in an ICS environment and consists of having assurance control as well as functional control at each layer. Our work seeks to partially articulate a framework where multiple functional and assurance controls are introduced at each layer of ICS architectural design to further enhance security while maintaining critical real-time transfer of command and control traffic

    Ein mehrschichtiges sicheres Framework für Fahrzeugsysteme

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    In recent years, significant developments were introduced within the vehicular domain, evolving the vehicles to become a network of many embedded systems distributed throughout the car, known as Electronic Control Units (ECUs). Each one of these ECUs runs a number of software components that collaborate with each other to perform various vehicle functions. Modern vehicles are also equipped with wireless communication technologies, such as WiFi, Bluetooth, and so on, giving them the capability to interact with other vehicles and roadside infrastructure. While these improvements have increased the safety of the automotive system, they have vastly expanded the attack surface of the vehicle and opened the door for new potential security risks. The situation is made worse by a lack of security mechanisms in the vehicular system which allows the escalation of a compromise in one of the non-critical sub-systems to threaten the safety of the entire vehicle and its passengers. This dissertation focuses on providing a comprehensive framework that ensures the security of the vehicular system during its whole life-cycle. This framework aims to prevent the cyber-attacks against different components by ensuring secure communications among them. Furthermore, it aims to detect attacks which were not prevented successfully, and finally, to respond to these attacks properly to ensure a high degree of safety and stability of the system.In den letzten Jahren wurden bedeutende Entwicklungen im Bereich der Fahrzeuge vorgestellt, die die Fahrzeuge zu einem Netzwerk mit vielen im gesamten Fahrzeug verteile integrierte Systeme weiterentwickelten, den sogenannten Steuergeräten (ECU, englisch = Electronic Control Units). Jedes dieser Steuergeräte betreibt eine Reihe von Softwarekomponenten, die bei der Ausführung verschiedener Fahrzeugfunktionen zusammenarbeiten. Moderne Fahrzeuge sind auch mit drahtlosen Kommunikationstechnologien wie WiFi, Bluetooth usw. ausgestattet, die ihnen die Möglichkeit geben, mit anderen Fahrzeugen und der straßenseitigen Infrastruktur zu interagieren. Während diese Verbesserungen die Sicherheit des Fahrzeugsystems erhöht haben, haben sie die Angriffsfläche des Fahrzeugs erheblich vergrößert und die Tür für neue potenzielle Sicherheitsrisiken geöffnet. Die Situation wird durch einen Mangel an Sicherheitsmechanismen im Fahrzeugsystem verschärft, die es ermöglichen, dass ein Kompromiss in einem der unkritischen Subsysteme die Sicherheit des gesamten Fahrzeugs und seiner Insassen gefährdet kann. Diese Dissertation konzentriert sich auf die Entwicklung eines umfassenden Rahmens, der die Sicherheit des Fahrzeugsystems während seines gesamten Lebenszyklus gewährleistet. Dieser Rahmen zielt darauf ab, die Cyber-Angriffe gegen verschiedene Komponenten zu verhindern, indem eine sichere Kommunikation zwischen ihnen gewährleistet wird. Darüber hinaus zielt es darauf ab, Angriffe zu erkennen, die nicht erfolgreich verhindert wurden, und schließlich auf diese Angriffe angemessen zu reagieren, um ein hohes Maß an Sicherheit und Stabilität des Systems zu gewährleisten
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