Development and Design Strategies of Evidence Collection Framework in Cloud Environment

Khan, Yunus; Varma, Shambhu D.

doi:10.1007/978-981-15-2071-6_3

Cited by 8 publications

(6 citation statements)

References 18 publications

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“…Moreover, they discussed the limitations and drawbacks of existing forensic solutions, providing future research directions. Khan and Varma [ 23 ] focused their research on evidence collection and cloud forensic architecture, also implementing a machine learning-based forensic method for the SaaS and PaaS delivery architecture. A fundamental issue often faced by forensic investigators in an investigation is how to carefully and efficaciously collect, preserve, and analyze digital evidence.…”

Section: Related Surveysmentioning

confidence: 99%

“…These frameworks focus on data collection, analysis, architecture, and the enhancement of investigation efficiency within cloud environments, addressing challenges specific to different cloud service models. Such a comprehensive approach aligns with the dynamic nature of cloud-based digital forensics, ensuring experts can effectively navigate diverse challenges while upholding ethical and legal standards [ 23 , 148 ].…”

Section: Strategizing For Emerging Challenges In Cloud Digital Forensicsmentioning

confidence: 99%

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Cloud Digital Forensics: Beyond Tools, Techniques, and Challenges

Malik,

Bhatti,

Park

et al. 2024

Sensors

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Cloud computing technology is rapidly becoming ubiquitous and indispensable. However, its widespread adoption also exposes organizations and individuals to a broad spectrum of potential threats. Despite the multiple advantages the cloud offers, organizations remain cautious about migrating their data and applications to the cloud due to fears of data breaches and security compromises. In light of these concerns, this study has conducted an in-depth examination of a variety of articles to enhance the comprehension of the challenges related to safeguarding and fortifying data within the cloud environment. Furthermore, the research has scrutinized several well-documented data breaches, analyzing the financial consequences they inflicted. Additionally, it scrutinizes the distinctions between conventional digital forensics and the forensic procedures specific to cloud computing. As a result of this investigation, the study has concluded by proposing potential opportunities for further research in this critical domain. By doing so, it contributes to our collective understanding of the complex panorama of cloud data protection and security, while acknowledging the evolving nature of technology and the need for ongoing exploration and innovation in this field. This study also helps in understanding the compound annual growth rate (CAGR) of cloud digital forensics, which is found to be quite high at ≈16.53% from 2023 to 2031. Moreover, its market is expected to reach ≈USD 36.9 billion by the year 2031; presently, it is ≈USD 11.21 billion, which shows that there are great opportunities for investment in this area. This study also strategically addresses emerging challenges in cloud digital forensics, providing a comprehensive approach to navigating and overcoming the complexities associated with the evolving landscape of cloud computing.

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Section: Related Surveysmentioning

confidence: 99%

Section: Strategizing For Emerging Challenges In Cloud Digital Forensicsmentioning

confidence: 99%

Cloud Digital Forensics: Beyond Tools, Techniques, and Challenges

Malik,

Bhatti,

Park

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…The proposed OTKA-AED framework's key generation time is depicted in [Fig. 3.6] and compared to the state-of-the-art approaches, such as the secure data sharing scheme developed by [14], the ranked searchable symmetric encryption scheme developed by [15], and the KP-ABE developed by [16][17][18][19]. The chart shows that, in comparison to current methods, the key generation time is significantly shorter.…”

Section: Encryption Of Attributes Based On Authorization Tagsmentioning

confidence: 99%

Digital Forensics Security for Communications Transmission by Encrypting and Decrypting Characteristics with One-Time Key Authorization

Kim,

Ju,

Hong

2024

APJCRI

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Information can be secretly coded to conceal its actual meaning through the process of encryption. In computers, encrypted data is referred to as ciphertext and unencrypted data is also called plaintext. Data encryption guards against data loss, alteration, and compromise. However, the decryption key needs to be kept private and shielded from unwanted access in order to guarantee that data is kept safe. In this study, the One-Time Key Authorization (OTKA-AED) framework is built to guarantee that message exchange is safe between owners and requesters of cloud data. Additionally, it obtains the OTKA-AED framework that obtains the encryption and decryption method for every session number based on the bilinear mapping transformation and reverse bilinear mapping transformation. In this study, to provide the public key and secret key, the OTKA-AED framework first used the one-time key generation function. This reduced the key generation time and hence, increased cloud security. Finally, permission tag-based encryption and decryption was carried out under the authorization tag, which ensured authorization by effectively reducing communication and storage overhead. The proposed One-Time Key Authorization (OTKA-AED) architecture further ensures message processing within the cloud environment by increasing the security of message communication by encrypting key attributes shared among cloud users.

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“…In addition to this approach, the authors of [48] suggested using a compatible data synchronization model that synchronizes data variables between VM and persistent storage for forensic use. The authors of [49] proposed a model for data collection and forensic Cloud construction, by using feature-based machine learning and prioritization on VMs. The authors proposed a forensic approach for PaaS and SaaS models to design and develop new digital technologies and improve research efficiency and may provide information to law enforcement personnel.…”

Section: An Integrated Conceptual Digital Forensic Frameworkmentioning

confidence: 99%

Cloud and Edge Computing-Based Computer Forensics: Challenges and Open Problems

et al. 2021

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In recent years, there has been a dramatic change in attitude towards computers and the use of computer resources in general. Cloud and Edge computing have emerged as the most widely used technologies, including fog computing and the Internet of Things (IoT). There are several benefits in exploiting Cloud and Edge computing paradigms, such as lower costs and higher efficiency. It provides data computation and storage where data are processed, enables better data control, faster understanding and actions, and continuous operation. However, though these benefits seem to be appealing, their effects on computer forensics are somewhat undesirable. The complexity of the Cloud and Edge environments and their key features present many technical challenges from multiple stakeholders. This paper seeks to establish an in-depth understanding of the impact of Cloud and Edge computing-based environmental factors. Software and hardware tools used in the digital forensic process, forensic methods for handling tampered sound files, hidden files, image files, or images with steganography, etc. The technical/legal challenges and the open design problems (such as distributed maintenance, multitasking and practicality) highlight the various challenges for the digital forensics process.

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Development and Design Strategies of Evidence Collection Framework in Cloud Environment

Cited by 8 publications

References 18 publications

Cloud Digital Forensics: Beyond Tools, Techniques, and Challenges

Cloud Digital Forensics: Beyond Tools, Techniques, and Challenges

Digital Forensics Security for Communications Transmission by Encrypting and Decrypting Characteristics with One-Time Key Authorization

Cloud and Edge Computing-Based Computer Forensics: Challenges and Open Problems

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