Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges

Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrigue across scientific, commercial, and societal arenas. This fascination extends particularly to the Internet of Things (IoT), a landscape characterized by the interconnection of countless devices, sensors, and systems, collectively gathering and sharing data to enable intelligent decision-making and automation. This research embarks on an exploration of the opportunities and challenges towards achieving AGI in the context of the IoT. Specifically, it starts by outlining the fundamental principles of IoT and the critical role of Artificial Intelligence (AI) in IoT systems. Subsequently, it delves into AGI fundamentals, culminating in the formulation of a conceptual framework for AGI's seamless integration within IoT. The application spectrum for AGI-infused IoT is broad, encompassing domains ranging from smart grids, residential environments, manufacturing, and transportation to environmental monitoring, agriculture, healthcare, and education. However, adapting AGI to resource-constrained IoT settings necessitates dedicated research efforts. Furthermore, the paper addresses constraints imposed by limited computing resources, intricacies associated with large-scale IoT communication, as well as the critical concerns pertaining to security and privacy

Fault-tolerance in cyber-physical systems: literature review and challenges

Modern industry demands techniques that ensure the operability of its processes, and even though the exponential technological advance in the last two decades in the manufacturing field, failures, waste, and unexpected interruptions are still present in this sector’s daily routine. Within the Industry 4.0 context, fault-tolerant (FT) production systems remain a complex issue and sometimes represent a vulnerable aspect. Faulttolerance techniques dedicated to autonomous and distributed systems, in a cyber-physical system (CPS) perspective, need to be investigated to follow the evolutionary pace of the manufacturing scenarios. This paper overviews these concepts and analyses the current situation in developing FT for CPS systems through a systematic literature review. The paper also discusses the research challenges in this new kind of FT systems due to new distributed architectures and emerging technologies, matching the several fault-tolerance phases.This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020. This work has been partially supported by the European Regional Development Fund (ERDF) through the Interreg Spain-Portugal V-A Program (POCTEP) under grant 0677 DISRUPTIVE 2 E (Intensifying the activity of Digital Innovation Hubs within the PocTep region to boost the development of disruptive and last generation ICTs through cross-border cooperation).info:eu-repo/semantics/publishedVersio

Adaptation of the human nervous system for self-aware secure mobile and IoT systems

IT systems have been deployed across several domains, such as hospitals and industries, for the management of information and operations. These systems will soon be ubiquitous in every field due to the transition towards the Internet of Things (IoT). The IoT brings devices with sensory functions into IT systems through the process of internetworking. The sensory functions of IoT enable them to generate and process information automatically, either without human contribution or having the least human interaction possible aside from the information and operations management tasks. Security is crucial as it prevents system exploitation. Security has been employed after system implementation, and has rarely been considered as a part of the system. In this dissertation, a novel solution based on a biological approach is presented to embed security as an inalienable part of the system. The proposed solution, in the form of a prototype of the system, is based on the functions of the human nervous system (HNS) in protecting its host from the impacts caused by external or internal changes. The contributions of this work are the derivation of a new system architecture from HNS functionalities and experiments that prove the implementation feasibility and efficiency of the proposed HNS-based architecture through prototype development and evaluation. The first contribution of this work is the adaptation of human nervous system functions to propose a new architecture for IT systems security. The major organs and functions of the HNS are investigated and critical areas are identified for the adaptation process. Several individual system components with similar functions to the HNS are created and grouped to form individual subsystems. The relationship between these components is established in a similar way as in the HNS, resulting in a new system architecture that includes security as a core component. The adapted HNS-based system architecture is employed in two the experiments prove its implementation capability, enhancement of security, and overall system operations. The second contribution is the implementation of the proposed HNS-based security solution in the IoT test-bed. A temperature-monitoring application with an intrusion detection system (IDS) based on the proposed HNS architecture is implemented as part of the test-bed experiment. Contiki OS is used for implementation, and the 6LoWPAN stack is modified during the development process. The application, together with the IDS, has a brain subsystem (BrSS), a spinal cord subsystem (SCSS), and other functions similar to the HNS whose names are changed. The HNS functions are shared between an edge router and resource-constrained devices (RCDs) during implementation. The experiment is evaluated in both test-bed and simulation environments. Zolertia Z1 nodes are used to form a 6LoWPAN network, and an edge router is created by combining Pandaboard and Z1 node for a test-bed setup. Two networks with different numbers of sensor nodes are used as simulation environments in the Cooja simulator. The third contribution of this dissertation is the implementation of the proposed HNS-based architecture in the mobile platform. In this phase, the Android operating system (OS) is selected for experimentation, and the proposed HNS-based architecture is specifically tailored for Android. A context-based dynamically reconfigurable access control system (CoDRA) is developed based on the principles of the refined HNS architecture. CoDRA is implemented through customization of Android OS and evaluated under real-time usage conditions in test-bed environments. During the evaluation, the implemented prototype mimicked the nature of the HNS in securing the application under threat with negligible resource requirements and solved the problems in existing approaches by embedding security within the system. Furthermore, the results of the experiments highlighted the retention of HNS functions after refinement for different IT application areas, especially the IoT, due to its resource-constrained nature, and the implementable capability of our proposed HNS architecture.--- IT-järjestelmiä hyödynnetään tiedon ja toimintojen hallinnassa useilla aloilla, kuten sairaaloissa ja teollisuudessa. Siirtyminen kohti esineiden Internetiä (Internet of Things, IoT) tuo tällaiset laitteet yhä kiinteämmäksi osaksi jokapäiväistä elämää. IT-järjestelmiin liitettyjen IoT-laitteiden sensoritoiminnot mahdollistavat tiedon automaattisen havainnoinnin ja käsittelyn osana suurempaa järjestelmää jopa täysin ilman ihmisen myötävaikutusta, poislukien mahdolliset ylläpito- ja hallintatoimenpiteet. Turvallisuus on ratkaisevan tärkeää IT-järjestelmien luvattoman käytön estämiseksi. Valitettavan usein järjestelmäsuunnittelussa turvallisuus ei ole osana ydinsuunnitteluprosessia, vaan otetaan huomioon vasta käyttöönoton jälkeen. Tässä väitöskirjassa esitellään uudenlainen biologiseen lähestymistapaan perustuva ratkaisu, jolla turvallisuus voidaan sisällyttää erottamattomaksi osaksi järjestelmää. Ehdotettu prototyyppiratkaisu perustuu ihmisen hermoston toimintaan tilanteessa, jossa se suojelee isäntäänsä ulkoisten tai sisäisten muutosten vaikutuksilta. Tämän työn keskeiset tulokset ovat uuden järjestelmäarkkitehtuurin johtaminen ihmisen hermoston toimintaperiaatteesta sekä tällaisen järjestelmän toteutettavuuden ja tehokkuuden arviointi kokeellisen prototyypin kehittämisen ja toiminnan arvioinnin avulla. Tämän väitöskirjan ensimmäinen kontribuutio on ihmisen hermoston toimintoihin perustuva IT-järjestelmäarkkitehtuuri. Tutkimuksessa arvioidaan ihmisen hermoston toimintaa ja tunnistetaan keskeiset toiminnot ja toiminnallisuudet, jotka mall-innetaan osaksi kehitettävää järjestelmää luomalla näitä vastaavat järjestelmäkomponentit. Nä-istä kootaan toiminnallisuudeltaan hermostoa vastaavat osajärjestelmät, joiden keskinäinen toiminta mallintaa ihmisen hermoston toimintaa. Näin luodaan arkkitehtuuri, jonka keskeisenä komponenttina on turvallisuus. Tämän pohjalta toteutetaan kaksi prototyyppijärjestelmää, joiden avulla arvioidaan arkkitehtuurin toteutuskelpoisuutta, turvallisuutta sekä toimintakykyä. Toinen kontribuutio on esitetyn hermostopohjaisen turvallisuusratkaisun toteuttaminen IoT-testialustalla. Kehitettyyn arkkitehtuuriin perustuva ja tunkeutumisen estojärjestelmän (intrusion detection system, IDS) sisältävä lämpötilan seurantasovellus toteutetaan käyttäen Contiki OS -käytöjärjestelmää. 6LoWPAN protokollapinoa muokataan tarpeen mukaan kehitysprosessin aikana. IDS:n lisäksi sovellukseen kuuluu aivo-osajärjestelmä (Brain subsystem, BrSS), selkäydinosajärjestelmä (Spinal cord subsystem, SCSS), sekä muita hermoston kaltaisia toimintoja. Nämä toiminnot jaetaan reunareitittimen ja resurssirajoitteisten laitteiden kesken. Tuloksia arvioidaan sekä simulaatioiden että testialustan tulosten perusteella. Testialustaa varten 6LoWPAN verkon toteutukseen valittiin Zolertia Z1 ja reunareititin on toteutettu Pandaboardin ja Z1:n yhdistelmällä. Cooja-simulaattorissa käytettiin mallinnukseen ymp-äristönä kahta erillistä ja erikokoisuta sensoriverkkoa. Kolmas tämän väitöskirjan kontribuutio on kehitetyn hermostopohjaisen arkkitehtuurin toteuttaminen mobiilialustassa. Toteutuksen alustaksi valitaan Android-käyttöjärjestelmä, ja kehitetty arkkitehtuuri räätälöidään Androidille. Tuloksena on kontekstipohjainen dynaamisesti uudelleen konfiguroitava pääsynvalvontajärjestelmä (context-based dynamically reconfigurable access control system, CoDRA). CoDRA toteutetaan mukauttamalla Androidin käyttöjärjestelmää ja toteutuksen toimivuutta arvioidaan reaaliaikaisissa käyttöolosuhteissa testialustaympäristöissä. Toteutusta arvioitaessa havaittiin, että kehitetty prototyyppi jäljitteli ihmishermoston toimintaa kohdesovelluksen suojaamisessa, suoriutui tehtävästään vähäisillä resurssivaatimuksilla ja onnistui sisällyttämään turvallisuuden järjestelmän ydintoimintoihin. Tulokset osoittivat, että tämän tyyppinen järjestelmä on toteutettavissa sekä sen, että järjestelmän hermostonkaltainen toiminnallisuus säilyy siirryttäessä sovellusalueelta toiselle, erityisesti resursseiltaan rajoittuneissa IoT-järjestelmissä

Distributed Deep Neural-Network-Based Middleware for Cyber-Attacks Detection in Smart IoT Ecosystem: A Novel Framework and Performance Evaluation Approach

Cyberattacks always remain the major threats and challenging issues in the modern digital world. With the increase in the number of internet of things (IoT) devices, security challenges in these devices, such as lack of encryption, malware, ransomware, and IoT botnets, leave the devices vulnerable to attackers that can access and manipulate the important data, threaten the system, and demand ransom. The lessons from the earlier experiences of cyberattacks demand the development of the best-practices benchmark of cybersecurity, especially in modern Smart Environments. In this study, we propose an approach with a framework to discover malware attacks by using artificial intelligence (AI) methods to cover diverse and distributed scenarios. The new method facilitates proactively tracking network traffic data to detect malware and attacks in the IoT ecosystem. Moreover, the novel approach makes Smart Environments more secure and aware of possible future threats. The performance and concurrency testing of the deep neural network (DNN) model deployed in IoT devices are computed to validate the possibility of in-production implementation. By deploying the DNN model on two selected IoT gateways, we observed very promising results, with less than 30 kb/s increase in network bandwidth on average, and just a 2% increase in CPU consumption. Similarly, we noticed minimal physical memory and power consumption, with 0.42 GB and 0.2 GB memory usage for NVIDIA Jetson and Raspberry Pi devices, respectively, and an average 13.5% increase in power consumption per device with the deployed model. The ML models were able to demonstrate nearly 93% of detection accuracy and 92% f1-score on both utilized datasets. The result of the models shows that our framework detects malware and attacks in Smart Environments accurately and efficiently.publishedVersio

Context-aware Security for Vehicles and Fleets: A Survey

Vehicles are becoming increasingly intelligent and connected. Interfaces for communication with the vehicle, such as WiFi and 5G, enable seamless integration into the user’s life, but also cyber attacks on the vehicle. Therefore, research is working on in-vehicle countermeasures such as authentication, access controls, or intrusion detection. Recently, legal regulations have also become effective that require automobile manufacturers to set up a monitoring system for fleet-wide security analysis. The growing amount of software, networking, and the automation of driving create new challenges for security. Context-awareness, situational understanding, adaptive security, and threat intelligence are necessary to cope with these ever-increasing risks. In-vehicle security should be adaptive to secure the car in an infinite number of (driving) situations. For fleet-wide analysis and alert triage, knowledge and understanding of the circumstances are required. Context-awareness, nonetheless, has been sparsely considered in the field of vehicle security. This work aims to be a precursor to context-aware, adaptive and intelligent security for vehicles and fleets. To this end, we provide a comprehensive literature review that analyzes the vehicular as well as related domains. Our survey is mainly characterized by the detailed analysis of the context information that is relevant for vehicle security in the future

Towards a Secure and Resilient Vehicle Design: Methodologies, Principles and Guidelines

The advent of autonomous and connected vehicles has brought new cyber security challenges to the automotive industry. It requires vehicles to be designed to remain dependable in the occurrence of cyber-attacks. A modern vehicle can contain over 150 computers, over 100 million lines of code, and various connection interfaces such as USB ports, WiFi, Bluetooth, and 4G/5G. The continuous technological advancements within the automotive industry allow safety enhancements due to increased control of, e.g., brakes, steering, and the engine. Although the technology is beneficial, its complexity has the side-effect to give rise to a multitude of vulnerabilities that might leverage the potential for cyber-attacks. Consequently, there is an increase in regulations that demand compliance with vehicle cyber security and resilience requirements that state vehicles should be designed to be resilient to cyber-attacks with the capability to detect and appropriately respond to these attacks. Moreover, increasing requirements for automotive digital forensic capabilities are beginning to emerge. Failures in automated driving functions can be caused by hardware and software failures as well as cyber security issues. It is imperative to investigate the cause of these failures. However, there is currently no clear guidance on how to comply with these regulations from a technical perspective.In this thesis, we propose a methodology to predict and mitigate vulnerabilities in vehicles using a systematic approach for security analysis; a methodology further used to develop a framework ensuring a resilient and secure vehicle design concerning a multitude of analyzed vehicle cyber-attacks. Moreover, we review and analyze scientific literature on resilience techniques, fault tolerance, and dependability for attack detection, mitigation, recovery, and resilience endurance. These techniques are then further incorporated into the above-mentioned framework. Finally, to meet requirements to hastily and securely patch the increasing number of bugs in vehicle software, we propose a versatile framework for vehicle software updates