9 research outputs found

    A Multi-Factor Homomorphic Encryption based Method for Authenticated Access to IoT Devices

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    Authentication is the first defence mechanism in many electronic systems, including Internet of Things (IoT) applications, as it is essential for other security services such as intrusion detection. As existing authentication solutions proposed for IoT environments do not provide multi-level authentication assurance, particularly for device-to-device authentication scenarios, we recently proposed the M2I (Multi-Factor Multi-Level and Interaction based Authentication) framework to facilitate multi-factor authentication of devices in device-to-device and device-to-multiDevice interactions. In this paper, we extend the framework to address group authentication. Two Many-to-One (M2O) protocols are proposed, the Hybrid Group Authentication and Key Acquisition (HGAKA) protocol and the Hybrid Group Access (HGA) protocol. The protocols use a combination of symmetric and asymmetric cryptographic primitives to facilitate multifactor group authentication. The informal analysis and formal security verification show that the protocols satisfy the desirable security requirements and are secure against authentication attacks

    Lightweight mutual authentication and privacy preservation schemes for IOT systems.

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    Internet of Things (IoT) presents a holistic and transformative approach for providing services in different domains. IoT creates an atmosphere of interaction between humans and the surrounding physical world through various technologies such as sensors, actuators, and the cloud. Theoretically, when everything is connected, everything is at risk. The rapid growth of IoT with the heterogeneous devices that are connected to the Internet generates new challenges in protecting and preserving user’s privacy and ensuring the security of our lives. IoT systems face considerable challenges in deploying robust authentication protocols because some of the IoT devices are resource-constrained with limited computation and storage capabilities to implement the currently available authentication mechanism that employs computationally expensive functions. The limited capabilities of IoT devices raise significant security and privacy concerns, such as ensuring personal information confidentiality and integrity and establishing end-to-end authentication and secret key generation between the communicating device to guarantee secure communication among the communicating devices. The ubiquity nature of the IoT device provides adversaries more attack surfaces which can lead to tragic consequences that can negatively impact our everyday connected lives. According to [1], authentication and privacy protection are essential security requirements. Therefore, there is a critical need to address these rising security and privacy concerns to ensure IoT systems\u27 safety. This dissertation identifies gaps in the literature and presents new mutual authentication and privacy preservation schemes that fit the needs of resource-constrained devices to improve IoT security and privacy against common attacks. This research enhances IoT security and privacy by introducing lightweight mutual authentication and privacy preservation schemes for IoT based on hardware biometrics using PUF, Chained hash PUF, dynamic identities, and user’s static and continuous biometrics. The communicating parties can anonymously communicate and mutually authenticate each other and locally establish a session key using dynamic identities to ensure the user’s unlinkability and untraceability. Furthermore, virtual domain segregation is implemented to apply security policies between nodes. The chained-hash PUF mechanism technique is implemented as a way to verify the sender’s identity. At first, this dissertation presents a framework called “A Lightweight Mutual Authentication and Privacy-Preservation framework for IoT Systems” and this framework is considered the foundation of all presented schemes. The proposed framework integrates software and hardware-based security approaches that satisfy the NIST IoT security requirements for data protection and device identification. Also, this dissertation presents an architecture called “PUF Hierarchal Distributed Architecture” (PHDA), which is used to perform the device name resolution. Based on the proposed framework and PUF architecture, three lightweight privacy-preserving and mutual authentication schemes are presented. The Three different schemes are introduced to accommodate both stationary and mobile IoT devices as well as local and distributed nodes. The first scheme is designed for the smart homes domain, where the IoT devices are stationary, and the controller node is local. In this scheme, there is direct communication between the IoT nodes and the controller node. Establishing mutual authentication does not require the cloud service\u27s involvement to reduce the system latency and offload the cloud traffic. The second scheme is designed for the industrial IoT domain and used smart poultry farms as a use case of the Industrial IoT (IIoT) domain. In the second scheme, the IoT devices are stationary, and the controller nodes are hierarchical and distributed, supported by machine-to-machine (M2M) communication. The third scheme is designed for smart cities and used IoV fleet vehicles as a use case of the smart cities domain. During the roaming service, the mutual authentication process between a vehicle and the distributed controller nodes represented by the Roadside Units (RSUs) is completed through the cloud service that stores all vehicle\u27s security credentials. After that, when a vehicle moves to the proximity of a new RSU under the same administrative authority of the most recently visited RSU, the two RSUs can cooperate to verify the vehicle\u27s legitimacy. Also, the third scheme supports driver static and continuous authentication as a driver monitoring system for the sake of both road and driver safety. The security of the proposed schemes is evaluated and simulated using two different methods: security analysis and performance analysis. The security analysis is implemented through formal security analysis and informal security analysis. The formal analysis uses the Burrows–Abadi–Needham logic (BAN) and model-checking using the automated validation of Internet security protocols and applications (AVISPA) toolkit. The informal security analysis is completed by: (1) investigating the robustness of the proposed schemes against the well-known security attacks and analyze its satisfaction with the main security properties; and (2) comparing the proposed schemes with the other existing authentication schemes considering their resistance to the well-known attacks and their satisfaction with the main security requirements. Both the formal and informal security analyses complement each other. The performance evaluation is conducted by analyzing and comparing the overhead and efficiency of the proposed schemes with other related schemes from the literature. The results showed that the proposed schemes achieve all security goals and, simultaneously, efficiently and satisfy the needs of the resource-constrained IoT devices

    Request for Comments: 4635 Motorola Laboratories

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    This document specifies an Internet standards track protocol for the Internet community, and requests discussion and suggestions for improvements. Please refer to the current edition of the "Internet Official Protocol Standards " (STD 1) for the standardization state and status of this protocol. Distribution of this memo is unlimited. Copyright Notice Copyright (C) The Internet Society (2006). Use of the Domain Name System TSIG resource record requires specification of a cryptographic message authentication code. Currently, identifiers have been specified only for HMAC MD5 (Hashed Message Authentication Code, Message Digest 5) and GSS (Generic Security Service) TSIG algorithms. This document standardizes identifiers and implementation requirements for additional HMAC SHA (Secure Hash Algorithm) TSIG algorithms and standardizes how t

    On the Design and Implementation of Secure Network Protocols

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    Decentralized Identity and Access Management Framework for Internet of Things Devices

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    The emerging Internet of Things (IoT) domain is about connecting people and devices and systems together via sensors and actuators, to collect meaningful information from the devices surrounding environment and take actions to enhance productivity and efficiency. The proliferation of IoT devices from around few billion devices today to over 25 billion in the next few years spanning over heterogeneous networks defines a new paradigm shift for many industrial and smart connectivity applications. The existing IoT networks faces a number of operational challenges linked to devices management and the capability of devices’ mutual authentication and authorization. While significant progress has been made in adopting existing connectivity and management frameworks, most of these frameworks are designed to work for unconstrained devices connected in centralized networks. On the other hand, IoT devices are constrained devices with tendency to work and operate in decentralized and peer-to-peer arrangement. This tendency towards peer-to-peer service exchange resulted that many of the existing frameworks fails to address the main challenges faced by the need to offer ownership of devices and the generated data to the actual users. Moreover, the diversified list of devices and offered services impose that more granular access control mechanisms are required to limit the exposure of the devices to external threats and provide finer access control policies under control of the device owner without the need for a middleman. This work addresses these challenges by utilizing the concepts of decentralization introduced in Distributed Ledger (DLT) technologies and capability of automating business flows through smart contracts. The proposed work utilizes the concepts of decentralized identifiers (DIDs) for establishing a decentralized devices identity management framework and exploits Blockchain tokenization through both fungible and non-fungible tokens (NFTs) to build a self-controlled and self-contained access control policy based on capability-based access control model (CapBAC). The defined framework provides a layered approach that builds on identity management as the foundation to enable authentication and authorization processes and establish a mechanism for accounting through the adoption of standardized DLT tokenization structure. The proposed framework is demonstrated through implementing a number of use cases that addresses issues related identity management in industries that suffer losses in billions of dollars due to counterfeiting and lack of global and immutable identity records. The framework extension to support applications for building verifiable data paths in the application layer were addressed through two simple examples. The system has been analyzed in the case of issuing authorization tokens where it is expected that DLT consensus mechanisms will introduce major performance hurdles. A proof of concept emulating establishing concurrent connections to a single device presented no timed-out requests at 200 concurrent connections and a rise in the timed-out requests ratio to 5% at 600 connections. The analysis showed also that a considerable overhead in the data link budget of 10.4% is recorded due to the use of self-contained policy token which is a trade-off between building self-contained access tokens with no middleman and link cost

    The Impact of DNSSEC on the Internet Landscape

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    In this dissertation we investigate the security deficiencies of the Domain Name System (DNS) and assess the impact of the DNSSEC security extensions. DNS spoofing attacks divert an application to the wrong server, but are also used routinely for blocking access to websites. We provide evidence for systematic DNS spoofing in China and Iran with measurement-based analyses, which allow us to examine the DNS spoofing filters from vantage points outside of the affected networks. Third-parties in other countries can be affected inadvertently by spoofing-based domain filtering, which could be averted with DNSSEC. The security goals of DNSSEC are data integrity and authenticity. A point solution called NSEC3 adds a privacy assertion to DNSSEC, which is supposed to prevent disclosure of the domain namespace as a whole. We present GPU-based attacks on the NSEC3 privacy assertion, which allow efficient recovery of the namespace contents. We demonstrate with active measurements that DNSSEC has found wide adoption after initial hesitation. At server-side, there are more than five million domains signed with DNSSEC. A portion of them is insecure due to insufficient cryptographic key lengths or broken due to maintenance failures. At client-side, we have observed a worldwide increase of DNSSEC validation over the last three years, though not necessarily on the last mile. Deployment of DNSSEC validation on end hosts is impaired by intermediate caching components, which degrade the availability of DNSSEC. However, intermediate caches contribute to the performance and scalability of the Domain Name System, as we show with trace-driven simulations. We suggest that validating end hosts utilize intermediate caches by default but fall back to autonomous name resolution in case of DNSSEC failures.In dieser Dissertation werden die Sicherheitsdefizite des Domain Name Systems (DNS) untersucht und die Auswirkungen der DNSSEC-Sicherheitserweiterungen bewertet. DNS-Spoofing hat den Zweck eine Anwendung zum falschen Server umzuleiten, wird aber auch regelmäßig eingesetzt, um den Zugang zu Websites zu sperren. Durch messbasierte Analysen wird in dieser Arbeit die systematische Durchführung von DNS-Spoofing-Angriffen in China und im Iran belegt, wobei sich die Messpunkte außerhalb der von den Sperrfiltern betroffenen Netzwerke befinden. Es wird gezeigt, dass Dritte in anderen Ländern durch die Spoofing-basierten Sperrfilter unbeabsichtigt beeinträchtigt werden können, was mit DNSSEC verhindert werden kann. Die Sicherheitsziele von DNSSEC sind Datenintegrität und Authentizität. Die NSEC3-Erweiterung sichert zudem die Privatheit des Domainnamensraums, damit die Inhalte eines DNSSEC-Servers nicht in Gänze ausgelesen werden können. In dieser Arbeit werden GPU-basierte Angriffsmethoden auf die von NSEC3 zugesicherte Privatheit vorgestellt, die eine effiziente Wiederherstellung des Domainnamensraums ermöglichen. Ferner wird mit aktiven Messmethoden die Verbreitung von DNSSEC untersucht, die nach anfänglicher Zurückhaltung deutlich zugenommen hat. Auf der Serverseite gibt es mehr als fünf Millionen mit DNSSEC signierte Domainnamen. Ein Teil davon ist aufgrund von unzureichenden kryptographischen Schlüssellängen unsicher, ein weiterer Teil zudem aufgrund von Wartungsfehlern nicht mit DNSSEC erreichbar. Auf der Clientseite ist der Anteil der DNSSEC-Validierung in den letzten drei Jahren weltweit gestiegen. Allerdings ist hierbei offen, ob die Validierung nahe bei den Endgeräten stattfindet, um unvertraute Kommunikationspfade vollständig abzusichern. Der Einsatz von DNSSEC-Validierung auf Endgeräten wird durch zwischengeschaltete DNS-Cache-Komponenten erschwert, da hierdurch die Verfügbarkeit von DNSSEC beeinträchtigt wird. Allerdings tragen zwischengeschaltete Caches zur Performance und Skalierbarkeit des Domain Name Systems bei, wie in dieser Arbeit mit messbasierten Simulationen gezeigt wird. Daher sollten Endgeräte standardmäßig die vorhandene DNS-Infrastruktur nutzen, bei Validierungsfehlern jedoch selbständig die DNSSEC-Zielserver anfragen, um im Cache gespeicherte, fehlerhafte DNS-Antworten zu umgehen

    Security and Trust in Safety Critical Infrastructures

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    Critical infrastructures such as road vehicles and railways are undergoing a major change, which increases the dependency of their operation and control on Information Technology (IT) and makes them more vulnerable to malicious intent. New complex communication infrastructures emerge using the increased connectivity of these safety-critical systems to enable efficient management of operational processes, service provisioning, and information exchange for various (third-party) actors. Railway Command and Control Systems (CCSs) turn with the introduction of digital interlocking into an “Internet of Railway Things”, where safety-critical railway signaling components are deployed on common-purpose platforms and connected via standard IP-based networks. Similarly, the mass adoption of Electric Vehicles (EVs) and the need to supply their batteries with energy for charging has given rise to a Vehicle-to-Grid (V2G) infrastructure, which connects vehicles to power grids and multiple service providers to coordinate charging and discharging processes and maintain grid stability under varying power demands. The Plug-and-Charge feature brought in by the V2G communication standard ISO 15118 allows an EV to access charging and value-added services, negotiate charging schedules, and support the grid as a distributed energy resource in a largely automated way, by leveraging identity credentials installed in the vehicle for authentication and payment. The fast deployment of this advanced functionality is driven by economical and political decisions including the EU Green Deal for climate neutrality. Due to the complex requirements and long standardization and development cycles, the standards and regulations, which play the key role in operating and protecting critical infrastructures, are under pressure to enable the timely and cost-effective adoption. In this thesis, we investigate security and safety of future V2G and railway command and control systems with respect to secure communication, platform assurance as well as safety and security co-engineering. One of the major goals in this context is the continuous collaboration and establishment of the proposed security solutions in upcoming domain-specific standards, thus ensuring their practical applicability and prompt implementation in real-world products. We first analyze the security of V2G communication protocols and requirements for secure service provisioning via charging connections. We propose a new Plug-and-Patch protocol that enables secure update of EVs as a value-added service integrated into the V2G charging loop. Since EVs can also participate in energy trading by storing and feeding previously stored energy to grid, home, or other vehicles, we then investigate fraud detection methods that can be employed to identify manipulations and misbehaving users. In order to provide a strong security foundation for V2G communications, we propose and analyze three security architectures employing a hardware trust anchor to enable trust establishment in V2G communications. We integrate these architectures into standard V2G protocols for load management, e-mobility services and value-added services in the V2G infrastructure, and evaluate the associated performance and security trade-offs. The final aspect of this work is safety and security co-engineering, i.e., integration of safety and security processes vital for the adequate protection of connected safety-critical systems. We consider two application scenarios, Electric Vehicle Charging System (EVCS) and Object Controller (OC) in railway CCS, and investigate how security methods like trusted computing can be applied to provide both required safety and security properties. In the case of EVCS, we bind the trust boundary for safety functionality (certified configuration) to the trust boundary in the security domain and design a new security architecture that enforces safety properties via security assertions. For the railway use case, we focus on ensuring non-interference (separation) between these two domains and develop a security architecture that allows secure co-existence of applications with different criticality on the same hardware platform. The proposed solutions have been presented to the committee ISO/TC 22/SC 31/JWG 1 that develops the ISO 15118 standard series and to the DKE working group “Informationssicherheit für Elektromobilität” responsible for the respective application guidelines. Our security extension has been integrated in the newest edition ISO 15118-20 released in April 2022. Several manufacturers have already started concept validation for their future products using our results. In this way, the presented analyses and techniques are fundamental contributions in improving the state of security for e-mobility and railway applications, and the overall resilience of safety-critical infrastructures to malicious attacks

    Bioinspired metaheuristic algorithms for global optimization

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    This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions

    Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

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    In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF
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