Block Chain Based Data Logging and Integrity Management System for Cloud Forensics

Park, Jun Hak; Park, Jun Yong; Huh, Eui Nam

doi:10.5121/csit.2017.71112

Cited by 19 publications

(8 citation statements)

References 8 publications

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“…The "BlockFog Framework," its components, and how they relate to IoT devices and the blockchain are depicted in the figure 2.1. Security and functionality are guaranteed by the "Device Onboarding & Identity Management," [28], "Data Integrity & Logging," [29] and "Smart Contract-Driven Intrusion Detection" modules of the BlockFog framework. Through the framework, IoT devices register, transmit data, and are Diving deeper into BlockFog's architectural design, it's evident that a series of core components work in harmony to fortify IoT fog computing.…”

Section: Methodsmentioning

confidence: 99%

BlockFog: A Blockchain-based Framework for Intrusion Defense in IOT Fog Computing

VG,

Babu,

Pydala

2024

SCPE

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In the rapidly evolving domain of the Internet of Things (IoT) and fog computing, maintaining security, scalability, and efficient operation poses significant challenges. Addressing these issues, this study introduces "BlockFog," a novel blockchain-based framework designed to bolster intrusion defense in IoT fog computing environments. The core objective of BlockFog is to counteract the vulnerabilities inherent in decentralized IoT ecosystems by leveraging blockchain technology for enhanced security and transparency. The framework's innovative design integrates crucial components such as Device Onboarding & Identity Management, Data Integrity & Logging, Smart Contract-Driven Intrusion Detection, Automated Blockchain Responses, Secure Peer-to-Peer Communication, and a Lightweight Consensus Mechanism. These elements work collectively to ensure the security and functionality of IoT devices within the fog computing paradigm. BlockFog stands out for its meticulous approach to handling high transaction volumes with off-chain computations and layer-2 solutions, ensuring data integrity and facilitating seamless audit processes. The framework's resilience is further demonstrated through its robust response to evolving cyber threats, incorporating Over-the-Air (OTA) updates and advanced data protection mechanisms like zero-knowledge proofs. A comparative analysis highlights BlockFog's superior performance against existing models. The results reveal BlockFog's lower latency rates in normal, high traffic, and attack scenarios, its higher throughput efficiency, and its more effective resource utilization in terms of CPU, memory, and bandwidth usage. Moreover, BlockFog exhibits an enhanced ability to detect and respond to malicious activities, including DDoS attacks, with significantly higher accuracy than its counterparts. These findings underscore BlockFog's potential in redefining security and operational paradigms in IoT fog computing, making it a robust, agile, and transparent framework suitable for the current digital landscape.

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Section: Methodsmentioning

confidence: 99%

BlockFog: A Blockchain-based Framework for Intrusion Defense in IOT Fog Computing

VG,

Babu,

Pydala

2024

SCPE

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“…The major problems considered in cloud forensics are storage of evidence and the integrity of evidence. The authors in [37] suggest a blockchain-based data storage and integrity management framework for cloud forensics to solve these problems. Therefore, it compares the efficiency of the proposed network with the other cryptocurrencies based on blockchain.…”

Section: Blockchain Based Solutions For Cloud Forensicsmentioning

confidence: 99%

Cloud Forensics: Challenges and Blockchain Based Solutions

Akter¹,

Akther²,

Uddin³

et al. 2020

IJWMT

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With the advancement in digital forensics, digital forensics has been evolved in Cloud computing. A common process of digital forensics mainly includes five steps: defining problem scenario, collection of the related data, investigation of the crime scenes, analysis of evidences and case documentation. The conduction of digital forensics in cloud results in several challenges, security, and privacy issues. In this paper, several digital forensics approaches in the context of IoT and cloud have been presented. The review focused on zone-based approach for IoT digital forensics where the forensics process is divided into three zones. Digital forensics in cloud provides the facilities of large data storage, computational capabilities and identification of criminal activities required for investigating forensics. We have presented a brief study on several issues and challenges raised in each phase of Cloud forensics process. The solution approaches as well as advancement prospects of cloud forensics have been described in the light of Blockchain technology. These studies will broaden the way to new researchers for better understanding and devising new ideas for combating the challenges.

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“…In addition, the need of evaluating the trustworthiness of collected data clearly emerged in the context of forensics science and has been initially dealt with by defining a systematic and reliable methodology for data collection and analysis [10]. Some solutions based on blockchain have been also proposed to guarantee availability, integrity, and verifiability of collected data (e.g., [5,16,19]). Their goal was to show the feasibility of using blockchain to guarantee integrity and traceability of digital forensics evidence, while not focusing on the quality and accuracy of stored results.…”

Section: Problem Statement and Related Workmentioning

confidence: 99%

From Trustworthy Data to Trustworthy IoT

Ardagna

Asal

Damiani

et al. 2020

ACM Trans. Cyber-Phys. Syst.

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Internet of Things (IoT) is composed of physical devices, communication networks, and services provided by edge systems and over-the-top applications. IoT connects billions of devices that collect data from the physical environment, which are pre-processed at the edge and then forwarded to processing services at the core of the infrastructure, on top of which cloud-based applications are built and provided to mobile end users. IoT comes with important advantages in terms of applications and added value for its users, making their world smarter and simpler. These advantages, however, are mitigated by the difficulty of guaranteeing IoT trustworthiness, which is still in its infancy. IoT trustworthiness is a must especially in critical domains (e.g., health, transportation) where humans become new components of an IoT system and their life is put at risk by system malfunctioning or breaches. In this article, we put forward the idea that trust in IoT can be boosted if and only if its automation and adaptation processes are based on trustworthy data. We therefore depart from a scenario that considers the quality of a single decision as the main goal of an IoT system and consider the trustworthiness of collected data as a fundamental requirement at the basis of a trustworthy IoT environment. We therefore define a methodology for data collection that filters untrusted data out according to trust rules evaluating the status of the devices collecting data and the collected data themselves. Our approach is based on blockchain and smart contracts and collects data whose trustworthiness and integrity are proven over time. The methodology balances trustworthiness and privacy and is experimentally evaluated in real-world and simulated scenarios using Hyperledger fabric blockchain.

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Block Chain Based Data Logging and Integrity Management System for Cloud Forensics

Abstract: ABSTRACT

Cited by 19 publications

References 8 publications

BlockFog: A Blockchain-based Framework for Intrusion Defense in IOT Fog Computing

BlockFog: A Blockchain-based Framework for Intrusion Defense in IOT Fog Computing

Cloud Forensics: Challenges and Blockchain Based Solutions

From Trustworthy Data to Trustworthy IoT

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