Digital Forensic Tools for Cloud Computing Environment

Bhagat, Swapnil P.; Meshram, B. B.

doi:10.1007/978-981-16-4177-0_7

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…For example, some events logging into the cloud with an account need to be followed with an action using the same credentials. In the case of data encryption, DFI can use Forensics Tool Kit (FTK) [33] to decrypt an encrypted piece of evidence. The investigator also needs to associate every piece of evidence with its legality procedures under SLA, local authority contract, or international law.…”

Section: Evaluation Phasementioning

confidence: 99%

MsFaaS: Microservices Forensics as a Service

Shehata¹,

Aslan²

2023

Preprint

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The rapid increase in using cloud services leads to the rise of unlimited cyber threats. Due to the distributed architect nature, services like Software as a Service (SaaS) are hard to be monitored. Consequently, in digital crimes, the investigator faces several forensics challenges. Mainly, in collecting data and presenting acceptable electronic evidence at the court. While most researchers went towards the external investigator’s responsibility, fewer researchers went to the Cloud Service Provider’s (CSP) responsibility. In literature, no complete framework that resolves all challenges and succeeds in presenting trusted evidence to the court has been suggested. In the present paper, we propose a framework named Microservices Forensics as a Service (MsFaaS) that suggests solutions to resolve open challenges. Since the CSP holds the crime scene and there is a global legal responsibility against digital crimes, MsFaaS relies on enforcing international law and putting the responsibility on both CSP and local authorities where the victim/attacker and CSP operate. We collect several data types and use event reconstruction methodology to build a comprehensive crime scene in both live and postmortem scenarios. In addition, MsFaaS provides a validation service against man-in-the-middle attacks microservices. It also triggers a response action to virtual machines incidents and external attacks; finally, the framework is helpful for auditing and recording the external and internal traffic inside the cloud environment. As a result, the service provided by the framework offers an evidence report that is certified by the local authority which can be accepted in a digital crime trial.

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Section: Evaluation Phasementioning

confidence: 99%

MsFaaS: Microservices Forensics as a Service

Shehata¹,

Aslan²

2023

Preprint

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“…With the current cyber-crime scenarios in which physical and digital boundaries have essentially been diluted, resulting in a tremendous increase in cyber-attacks in recent years, the complexity, heterogeneous environments, and influential nature of IoT and cloud computing are driving the adoption of innovative and upcoming frameworks and models to deter and deal with. [9] B. Digital Evidence Principles For any digital evidence to be admissible in court of law, there are certain mandatory attributes that the evidence must have.…”

Section: Context and Backgroundmentioning

confidence: 99%

Advanced Intuitive Model for Digital Forensics Collection Methods in the Context of Cloud Computing and IoT

Kotasthane¹,

Khare²,

Sunil³

et al. 2022

IJRASET

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With the wide scale adoption of cloud computing paradigms and Internet of Things implementations, the arena of service delivery has changed significantly for the world of technology-oriented services. While these new modes of service delivery have provided innovations that were not fathomable earlier, they not only create new non-traditional pathways for evidence generation, nevertheless, they have also been seen to carry a potential of creating and exposing a whole new set of security vulnerabilities that malicious actors can exploit. Traditional forensic investigation process falls short in many ways including the way it aims to identify and link crucial pieces of evidence in these scenarios due to a myriad of internal and external factors. Challenges and inadequacies have been identified in the community in relation to these specific sets of advancing technologies that hinder the efficient identification, extraction and processing of evidence generated in crimes involving them. In this paper we wish to surmise the current forensic collection methods, how they pose challenges when put together with the latest cloud and IoT technologies and then attempt to propose an advanced, more intuitive, and theoretically validated digital forensic collection process guided by zero trust principle and enforced with artificial intelligence and machine learning methodologies with the aim to fill the gaps and provide a more reliable, robust and intuitive model to perform digital evidence collection in the given context.

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“…This includes the difficulties of data access, data originating from various locations, the traceability and transparency of evidence, and huge-volume data analysis. During the past few years, a large number of researchers have focused on forensic analysis based on cloud computing [ 13 , 14 , 15 ], evidence modeling [ 16 , 17 , 18 ], and assisting the community of law enforcement. Blockchain technology is a distributed ledger system that collects and saves the proper records in the decentralized format of a peer-to-peer network.…”

Section: Introductionmentioning

confidence: 99%

NLP-Based Digital Forensic Analysis for Online Social Network Based on System Security

Shahbazi

Byun

2022

IJERPH

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Social media evidence is the new topic in digital forensics. If social media information is correctly explored, there will be significant support for investigating various offenses. Exploring social media information to give the government potential proof of a crime is not an easy task. Digital forensic investigation is based on natural language processing (NLP) techniques and the blockchain framework proposed in this process. The main reason for using NLP in this process is for data collection analysis, representations of every phase, vectorization phase, feature selection, and classifier evaluation. Applying a blockchain technique in this system secures the data information to avoid hacking and any network attack. The system’s potential is demonstrated by using a real-world dataset.

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Digital Forensic Tools for Cloud Computing Environment

Cited by 4 publications

References 9 publications

MsFaaS: Microservices Forensics as a Service

MsFaaS: Microservices Forensics as a Service

Advanced Intuitive Model for Digital Forensics Collection Methods in the Context of Cloud Computing and IoT

NLP-Based Digital Forensic Analysis for Online Social Network Based on System Security

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