Abstract

Collecting and preserving the smart environment logs connected to cloud storage is challenging due to the black-box nature and the multi-tenant cloud models which can pervade log secrecy and privacy. The existing work for log secrecy and confidentiality depends on cloud-assisted models, but these models are prone to multi-stakeholder collusion problems. This study proposes ’PLAF,’ a holistic and automated architecture for proactive forensics in the Internet of Things (IoT) that considers the security and privacy-aware distributed edge node log preservation by tackling the multi-stakeholder issue in a fog enabled cloud. We have developed a test-bed to implement the specification, as mentioned earlier, by incorporating many state-of-the-art technologies in one place. We used Holochain to preserve log integrity, provenance, log verifiability, trust admissibility, and ownership non-repudiation. We introduced the privacy preservation automation of log probing via non-malicious command and control botnets in the container environment. For continuous and robust integration of IoT microservices, we used docker containerization technology. For secure storage and session establishment for logs validation, Paillier Homomorphic Encryption, and SSL with Curve25519 is used respectively. We performed the security and performance analysis of the proposed PLAF architecture and showed that, in stress conditions, the automatic log harvesting running in containers gives a 95% confidence interval. Moreover, we show that log preservation via Holochain can be performed on ARM-Based architectures such as Raspberry Pi in a very less amount of time when compared with RSA and blockchain.

Highlights

  • Cloud computing has provided numerous features such as on-demand services, resilience to security attacks, and ubiquity to many fields in enterprise networks [1,2,3]

  • We propose an architecture for continuous log collection and preservation for Internet of Things (IoT) devices in a fog enabled cloud environment for proactive forensic aware logging

  • Threat Agent: Multi-stake holders are all the corresponding entities that are assumed as threat agents which are, Cloud Service Provider (CSP), investigator, an attacker, or malicious user neighboring with the cloud storage in a cloud environment

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Summary

Introduction

Cloud computing has provided numerous features such as on-demand services, resilience to security attacks, and ubiquity to many fields in enterprise networks [1,2,3]. To avoid delay in edge cloud network communication, fog assisted IoT network is used to assign the tasks This is done through computation offloading which lessen the load of the core network [24,25]. The proposed architecture introduced the holistic log preservation scheme which ensures the security and privacy of logs generated by IoT devices by considering the features of the fog-cloud. We propose an architecture for continuous log collection and preservation for IoT devices in a fog enabled cloud environment for proactive forensic aware logging. PLAF architecture performs the forensic aware logging and considers automated, secure, and privacy concerned distributed edge node log collection in fog-cloud by tackling the multi-stakeholder collusion problem. PLAF architecture, Section 7 concludes the paper and outlines plans for future work

Related Work
Limitations
Threat Model and Security Requirement Modelling
Modelling Attack Possibilities
Modeling Security Requirements
Proposed Architecture PLAF
Objective
Holochain
Creating Log Chains as Proof of Past Logs
Performance Evaluation and Security Analysis
Implementation
Performance Analysis
Use Case
Fog Level Privacy Automation Processing and Testing
Stress Testing of Bots and Containers
Log Preservation Processing Analysis
Secure Log Storage Processing Analyses
Performance Validation of PPL Processing
Computing Resource Allocation Trade-Offs
Security Analysis
Log Integrity Verification
Log Chain Validation
Result
Findings
Discussion
Conclusions and Future Directions

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