Initial trust establishment for personal space IoT systems

University of Technology Sydney. Faculty of Engineering and Information Technology.Internet of Things (IoT) is becoming a reality with innovative applications, and IoT platforms have been developed to transfer technologies from research to business solutions. With IoT applications, we have greater control over personal devices and achieve more insights into the resource consumption habits; business processes can be streamlined; people are also better connected to each other. Despite the benefits derived from the IoT systems, users are concerned about the trustworthiness of their collected data and offered services. Security controls can prevent user’s data from being compromised during transmission, storage or unauthorized access, but do not provide a guarantee against the misbehaved devices that report incorrect information and poor services or avoid conducting a common task. Establishing trust relationship among devices and continuously monitoring their trust is the key to guarantee a reliable IoT system and hence mitigate user’s concerns. In this dissertation, we propose and investigate a novel initial trust establishment architecture for personal space IoT systems. In the initial trust establishment architecture, we propose a trust evidence generation module based on a challenge-response mechanism to generate the trust evidence relying on the device’s responses to the challenges, a trust knowledge assessment module to obtain the knowledge about the device from the generated trust evidence, and a trust evaluation scheme to quantify the initial trust level of the devices. We design and investigate a challenge-response information design to determine feasible designs of the challenge-response mechanism that ensure meaningful and related trust knowledge about the device’s trustworthiness captured from the challenge-response operations. A new trust-aware communication protocol is designed and implemented by incorporating the proposed initial trust establishment architecture into existing Bluetooth Low Energy (BLE) protocol to demonstrate the feasibility and efficiency of the proposed initial trust establishment architecture in practice. In this work, we first study building blocks and possible architectures of the IoT and analyze key requirements of an IoT system. Based on the analysis, we identify the critical role of the initial trust establishment model and the challenges of establishing initial trust in IoT systems due to the lack of knowledge for the trust assessment to work. To address the challenges, we propose a novel initial trust establishment architecture that can generate trust evidence for assessing the initial trust level of new devices by conducting challenge-response operations within a limited time window before they are admitted to the system. We propose three new initial trust establishment models based on the proposed architecture. An implicit relationship between the responses and the challenges is assumed for the system to judge the initial trustworthiness of the devices. The first model assesses the initial trust value based on a probability associated with the device’s behavior captured from the challenge-response process. The second model investigates the initial trust value based on a binary outcome set, and the third model quantifies the initial trust level based on a multiple-component outcome set from the challenge-response process. Subsequently, we propose the challenge-response information design where the challenge-response process is investigated and designed to determine the information space of the challenger’s view on its environment so that the challenge can invite relevant responses from the target environment. Based on the design of the challenge-response mechanism, the system can capture meaningful trust knowledge about the devices from challenge-response operations at their admission phase. We finally design and implement the initial trust-aware BLE protocol which incorporates the proposed initial trust establishment architecture into the existing BLE protocol. The simulation results show the efficiency, feasibility, and dependability of using initial trust-aware BLE protocol for building a trustworthy personal space IoT systems. The novelty of this research lies in assessing the devices’ initial trust level within a limited time window, before their admission to the personal space IoT system, without requiring prior experience or recommendations. The major contribution of this thesis is that it helps the IoT business solution providers to build secure and trustworthy IoT systems by admitting dependable devices, monitoring the trust of admitted devices, detecting maligned devices, and building long-term trust among. As a result, it mitigates the user’s concerns about the trustworthiness of IoT systems and encourages broader adoption of IoT applications

Securing the Internet of Things Communication Using Named Data Networking Approaches

The rapid advancement in sensors and their use in devices has led to the drastic increase of Internet-of-Things (IoT) device applications and usage. A fundamental requirement of an IoT-enabled ecosystem is the device’s ability to communicate with other devices, humans etc. IoT devices are usually highly resource constrained and come with varying capabilities and features. Hence, a host-based communication approach defined by the TCP/IP architecture relying on securing the communication channel between the hosts displays drawbacks especially when working in a highly chaotic environment (common with IoT applications). The discrepancies between requirements of the application and the network supporting the communication demands for a fundamental change in securing the communication in IoT applications. This research along with identifying the fundamental security problems in IoT device lifecycle in the context of secure communication also explores the use of a data-centric approach advocated by a modern architecture called Named Data Networking (NDN). The use of NDN modifies the basis of communication and security by defining data-centric security where the data chunks are secured directly and retrieved using specialized requests in a pull-based approach. This work also identifies the advantages of using semantically-rich names as the basis for IoT communication in the current client-driven environment and reinforces it with best-practices from the existing host-based approaches for such networks. We present in this thesis a number of solutions built to automate and securely onboard IoT devices; encryption, decryption and access control solutions based on semantically rich names and attribute-based schemes. We also provide the design details of solutions to sup- port trustworthy and conditionally private communication among highly resource constrained devices through specialized signing techniques and automated certificate generation and distribution with minimal use of the network resources. We also explore the design solutions for rapid trust establishment and vertically securing communication in applications including smart-grid operations and vehicular communication along with automated and lightweight certificate generation and management techniques. Through all these design details and exploration, we identify the applicability of the data-centric security techniques presented by NDN in securing IoT communication and address the shortcoming of the existing approaches in this area

A Comprehensive Analysis of Password Authentication for Enhancing Security in Internet of Things (Iot)

Recently, there has been a significant increase in customer demands and the variety of services provided due to the increasing use of mobile devices and the development of new networking technologies such as the Internet of Things (IoTs) and Big data networking. The proliferation of future smart cities, smart transport systems, and other Internet of Things (IoT) application areas presents a significant vulnerability to a multitude of security risks that can have detrimental impacts on the economy, the environment, and society. This vast range of functions raises several security concerns, such as data protection, virtualization vulnerabilities, segregation risks, network connectivity issues, and monitoring challenges. The objective of identity and access management is to ensure that the right individuals have access to the right resources. Implementing user identification and identity verification establishes a robust security measure that effectively separates potential attackers from accessing sensitive data. This study use a Systematic Literature Review (SLR) methodology to conduct a comprehensive review of security concerns and various computing approaches to mitigate them. Despite the existence of various approaches to address the specific challenges related to application design, security, and privacy, there is still a need for a comprehensive research study. This study should focus on the challenges and requirements of targeted applications, which currently have limited security enhancement solutions

UNCOVERING EVIDENCE OF ATTACKER BEHAVIOR ON THE NETWORK

This comprehensive research presents and investigates a diverse assessment of interruption discovery strategies and their job in contemporary online protection. Interruption Recognition Frameworks are taken apart as vital parts in defending computerized foundations, utilizing different techniques, for example, signature-based, peculiarity based, and heuristic-based identification. While signature-based strategies demonstrate strong against known dangers, the review highlights the urgent job of irregularity-based and heuristic-based approaches in countering novel and complex assaults. Different types attract, their characteristics and behaviors has explored in this paper. The mix of AI and Man-made consciousness (computer based intelligence) in recognizing odd exercises arises as an extraordinary power, empowering versatile reactions to developing digital dangers. The exploration fundamentally breaks down the difficulties looked by existing location strategies, including versatility concerns, high bogus positive rates, and the encryption-related obstacles in rush hour gridlock examination. The outcomes and investigation segment approves the viability of proposed models, including group learning strategies and creative techniques, for example, the Solid Methodology in light of Blockchain and Peculiarity based location (SABA). A Convolutional Brain Organization (CNN) model for interruption location in IoT conditions and a cross breed approach joining positioning based channel strategies and NSGA-II exhibit eminent exactnesses. The review\u27s suggestions for network security are significant, prompting proposals for a TTP-driven approach, mix of conduct peculiarities, persistent security mindfulness preparing, standard red group works out, versatile episode reaction plans, and intermittent security reviews. By and large, the examination contributes a nuanced comprehension of assailant\u27s ways of behaving, down to earth procedures for online protection flexibility, and makes way for future investigation into dynamic danger scenes and the human component in network safety

Pioneering food safety:Blockchain's integration in supply chain surveillance

Ensuring food safety in a world facing escalating demand and complex supply chains is a pressing challenge. Despite increasing awareness, obstacles such as information distribution, financial limitations, and insufficient infrastructure impede food safety efforts. Blockchain technology presents a promising solution by improving transparency and traceability in supply chains, which are essential for tackling food safety issues. This study explores the integration of blockchain into food safety frameworks, emphasising its compatibility and potential to transform food production and distribution. Drawing on literature, it identifies key challenges to blockchain adoption, including regulatory frameworks and interoperability issues, and proposes strategies such as government intervention and standardisation to overcome them. Ultimately, blockchain holds immense promise in revolutionizing food safety practices, ensuring safe and nutritious food for all

A Critical Investigation into Identifying Key Focus Areas for the Implementation of Blockchain Technology in the Mining Industry

Thesis (PhD)--University of Pretoria, 2023.The value of digital information is ever-increasing as more companies utilize digital technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT) to gain deeper insight into their business operations and drive productivity gains. It is therefore important to safeguard and ensure the integrity of digital information exchange. Blockchain technology (BCT) was identified as potentially providing the mining industry with a trusted system for securely exchanging digital value. However, there is little evidence or understanding of how/where BCT can be implemented and what benefits the industry could obtain. This research study provides a fundamental understanding of what the technology is in order to identify the associated capabilities and potential application benefits for the mining industry. From a technology push perspective, blockchain capabilities are used to evaluate how the technology’s value drivers map to the mining industries core value chain processes. This was done to identify potential focus areas within the mining enterprise for further research and development of blockchain applications.ARMMining EngineeringMEngUnrestricte

Machine learning and blockchain technologies for cybersecurity in connected vehicles

Future connected and autonomous vehicles (CAVs) must be secured againstcyberattacks for their everyday functions on the road so that safety of passengersand vehicles can be ensured. This article presents a holistic review of cybersecurityattacks on sensors and threats regardingmulti-modal sensor fusion. A compre-hensive review of cyberattacks on intra-vehicle and inter-vehicle communicationsis presented afterward. Besides the analysis of conventional cybersecurity threatsand countermeasures for CAV systems,a detailed review of modern machinelearning, federated learning, and blockchain approach is also conducted to safe-guard CAVs. Machine learning and data mining-aided intrusion detection systemsand other countermeasures dealing with these challenges are elaborated at theend of the related section. In the last section, research challenges and future direc-tions are identified

Data Trading and Monetization: Challenges and Open Research Directions

Traditional data monetization approaches face challenges related to data protection and logistics. In response, digital data marketplaces have emerged as intermediaries simplifying data transactions. Despite the growing establishment and acceptance of digital data marketplaces, significant challenges hinder efficient data trading. As a result, few companies can derive tangible value from their data, leading to missed opportunities in understanding customers, pricing decisions, and fraud prevention. In this paper, we explore both technical and organizational challenges affecting data monetization. Moreover, we identify areas in need of further research, aiming to expand the boundaries of current knowledge by emphasizing where research is currently limited or lacking.Comment: Paper accepted by the International Conference on Future Networks and Distributed Systems (ICFNDS 2023

Cognitive Machine Individualism in a Symbiotic Cybersecurity Policy Framework for the Preservation of Internet of Things Integrity: A Quantitative Study

This quantitative study examined the complex nature of modern cyber threats to propose the establishment of cyber as an interdisciplinary field of public policy initiated through the creation of a symbiotic cybersecurity policy framework. For the public good (and maintaining ideological balance), there must be recognition that public policies are at a transition point where the digital public square is a tangible reality that is more than a collection of technological widgets. The academic contribution of this research project is the fusion of humanistic principles with Internet of Things (IoT) technologies that alters our perception of the machine from an instrument of human engineering into a thinking peer to elevate cyber from technical esoterism into an interdisciplinary field of public policy. The contribution to the US national cybersecurity policy body of knowledge is a unified policy framework (manifested in the symbiotic cybersecurity policy triad) that could transform cybersecurity policies from network-based to entity-based. A correlation archival data design was used with the frequency of malicious software attacks as the dependent variable and diversity of intrusion techniques as the independent variable for RQ1. For RQ2, the frequency of detection events was the dependent variable and diversity of intrusion techniques was the independent variable. Self-determination Theory is the theoretical framework as the cognitive machine can recognize, self-endorse, and maintain its own identity based on a sense of self-motivation that is progressively shaped by the machine’s ability to learn. The transformation of cyber policies from technical esoterism into an interdisciplinary field of public policy starts with the recognition that the cognitive machine is an independent consumer of, advisor into, and influenced by public policy theories, philosophical constructs, and societal initiatives