Evolving Evidence Gathering Process: Cloud Forensics

Srivastava, Prachi; Choudhary, Arjun

doi:10.1007/978-981-15-8377-3_20

Cited by 4 publications

(1 citation statement)

References 9 publications

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“…is paper secures logging by encrypting cloud logs using encryption techniques and identifying assaults on the cloud framework from DDoS (distributed denial of service) [25].…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Blockchain and Software-Defined Networking-Based Evidence Collection Architecture for Cloud Environment

Khan

Verma

2021

Scientific Programming

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Cloud forensics is an extension of contemporary forensic science that guards against cybercriminals. However, consolidated data assortment and storage compromise the legitimacy of digital indication. This essay proposes an evolving modern algorithm automated forensic platform based on the blockchain idea. This proposes forensic structure design, evidence gathering, and storage on a blockchain that are peer to peer. Secure Block Verification Mechanism (SBVM) will protect unauthorised users. Secret keys are optimally produced using the cuckoo search optimization method. All data are saved and encrypted at the cloud authentication server for secrecy. Confidentiality-Based Algebraically Homomorphism, a new encryption method, is given to cryptosystem learning. Every data is assigned a block in the SDN controller, and the history is kept as metadata about data. Each block has a Secure Hash Algorithm version 3 of 512-bit hash-based tree. Our approach uses graph theory-based graph neural networks in Smart Contracts to track users’ data (GNNSC). Finally, a blockchain-based evidence graph allows for evidence analysis. The experiments were run in a cloud environment with Python and network simulator-3.30 (for software-defined network). We achieved good results in terms of evidence response time, cloud evidence insertion time, cloud evidence verification time, computational overhead, hash calculation time, key generation times, and entire overall change rate of indication using our newly deliberated forensic construction using blockchain (FAuB).

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“…is paper secures logging by encrypting cloud logs using encryption techniques and identifying assaults on the cloud framework from DDoS (distributed denial of service) [25].…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Blockchain and Software-Defined Networking-Based Evidence Collection Architecture for Cloud Environment

Khan

Verma

2021

Scientific Programming

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Considerations on Evaluation of Practical Cloud Data Protection

Rui

Yan

et al. 2022

Communications in Computer and Information Science

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With the continuous growth of enterprises’ digital transformation, business-driven cloud computing has seen tremendous growth. The security community has proposed a large body of technical mechanisms, operational processes, and practical solutions to achieve cloud security. In addition, diverse jurisdictions also present regulatory requirements on data protection to mitigate possible risks, for instance, unauthorized access, data leakage, sensitive information and privacy disclosure. In view of this, several practical standards, frameworks, and best practices in the industry are proposed to evaluate and improve the protection level of cloud data. However, few evaluation models can conduct a comprehensive quantitative evaluation for cloud data protection that includes security, privacy, and even ethical considerations. In this paper, we first make a comprehensive review of cloud data security and privacy issues, especially also including ethical concerns that we consider as a type of specific risks caused by human factors, which refers to acting honorably, honestly, justly, and legally, due diligence, and due care. Then, we propose a novel evaluation model for cloud data protection that can quantitatively assess the protection level. Finally, based on the parallel evaluation between manual assessment by experts and our evaluation model, results show that our evaluation model is consistent with the manual evaluation conclusion.

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A Detailed Study of Advancements in Digital Forensics

Gogia,

Rughani

2024

Lecture Notes in Electrical Engineering

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Evolving Evidence Gathering Process: Cloud Forensics

Cited by 4 publications

References 9 publications

An Intelligent Blockchain and Software-Defined Networking-Based Evidence Collection Architecture for Cloud Environment

An Intelligent Blockchain and Software-Defined Networking-Based Evidence Collection Architecture for Cloud Environment

Considerations on Evaluation of Practical Cloud Data Protection

A Detailed Study of Advancements in Digital Forensics

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