A Review of Digital Forensics Framework for Blockchain in Cryptocurrency Technology

Mas'ud, M. Z.; Hassan, Aslinda; Shah, Wahidah Md; Abdul‐Latip, Shekh Faisal; Ahmad, Rabiah; Ariffin, A.; Yunos, Zahri

doi:10.1109/crc50527.2021.9392563

Cited by 9 publications

(4 citation statements)

References 18 publications

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“…Mas'ud et al 14 Examine how digital forensic investigation procedures have been applied to blockchain and cryptocurrencies.…”

Section: Compared the Different Assessed Toolsmentioning

confidence: 99%

Blockchain and crypto forensics: Investigating crypto frauds

Agarwal,

Rishiwal,

Tanwar

et al. 2023

Int J Network Mgmt

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In the past few years, cryptocurrency has gained widespread acceptance because of its decentralized nature, quick and secure transactions, and potential for investment and speculation. But the increased popularity has also led to increased cryptocurrency fraud, including scams, phishing attacks, Ponzi schemes, and other criminal activities. Although there is little documentation of cryptocurrency fraud, an in‐depth study is essential to recognize various scams in different cryptocurrencies. To fill this gap, a study investigated cryptocurrency‐related fraud in various cryptocurrencies and provided a taxonomy of crypto‐forensics and forensic blockchain. In addition, we have introduced an architecture that integrates artificial intelligence (AI) and blockchain technologies to investigate and protect against instances of cryptocurrency fraud. The suggested design's effectiveness was evaluated using several machine learning (ML) classification algorithms. The conclusion of the evaluation confirmed that the random forest (RF) classifier performed the best, delivering the highest level of accuracy, that is, 97.5%. Once the ML classifiers detect cryptocurrency fraud, the information is securely stored in the InterPlanetary File System (IPFS); the document's hash is also stored in the blockchain using smart contracts. Law enforcement can leverage blockchain technology to secure access to fraudulent cryptographic transactions. The proposed architecture was tested for bandwidth utilization. Despite the potential benefits of blockchain and crypto‐forensics, several issues and challenges remain, including privacy concerns, standardization, and difficulty identifying fraud between crypto‐currencies. Finally, the paper discusses various problems and challenges in blockchain and crypto forensics to investigate cryptocurrency fraud.

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“…Mas'ud et al 14 Examine how digital forensic investigation procedures have been applied to blockchain and cryptocurrencies.…”

Section: Compared the Different Assessed Toolsmentioning

confidence: 99%

Blockchain and crypto forensics: Investigating crypto frauds

Agarwal,

Rishiwal,

Tanwar

et al. 2023

Int J Network Mgmt

View full text Add to dashboard Cite

show abstract

“…The training phase contains the feature extraction process in which the features of malicious and standard data are based on the behavior analysis method; these extracted features help classify the harmful or standard data. Before transmitting data to the requested user, it checks whether it is stored in a public or private cloud [13,14]. If the requested data is in the public cloud, it gets transmitted directly to the user because it does not contain confidential data.…”

Section: Improve Malware Detectionmentioning

confidence: 99%

Security Privacy Process Involvement in Cloud Security for Data Preservation against Data Malicious Activity

K Prabu

2023

IJRITCC

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Cloud data sent from the person is attacked, leading to data hacking. Data classification can be made by malware detection, leading to the data warehouse technique and data storage. The cloud data from a particular internet protocol address cannot be hacked. Only random cloud data is hacked. Even though this leads to some illegal issues. The method of managing the cloud data and maintaining the factor to hack illegal cloud data has been proposed. The method of malware detection and ML-based end-to-end malware detection are used in calculating the time efficiency. The malware detection and defence method has been introduced for managing the data tracking and the system's formation to hack unwanted data. The time efficiency calculation for the data transmitted in the network has been enabled for the cloud data sent and received. The data from each router makes the data store 12% of the unwanted compared to the original messages. The factor for managing the individual aspect to produce the data is 30% of the database. This will contain 20% of the data in formulating the cloud storage system, which makes the data classifications. 4% of redundant data from the database has been enveloped for the data classifications. Meanwhile, the data attack can be evaluated using the malware detector and also manages classification method for evaluation of data and formation of the system to produce data from the appearance of Secure data clouds.

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“…This discipline facilitates the exposure of felonious activities, including money laundering and fraud, championing transparency and accountability in decentralized systems. Through the judicious application of the appropriate tools and techniques, it has been demonstrated that transactions can be retraced and culprits implicated within the blockchain's labyrinth [8,9]. https://doi.org/10.56578/ida020302 However, the task of decrypting cryptocurrencies for digital evidence is not devoid of formidable challenges.…”

Section: Introductionmentioning

confidence: 99%

Cryptocurrency Investigations in Digital Forensics: Contemporary Challenges and Methodological Advances

Raza,

Shaikh,

Tahira

2023

IDA

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Digital forensics, a crucial subset of cybersecurity, encompasses sophisticated tools and methodologies for the interpretation, analysis, and investigation of digital evidence, facilitating the identification and mitigation of cybercrimes and security breaches. With the advent of cryptocurrencies, an array of unique challenges has emerged in the domain of digital forensic investigations. This review elucidates the prevailing state of digital forensic practices vis-à-vis cryptocurrencies, emphasizing the obstacles and limitations inherent in probing decentralized and intricate technologies. Notable deficiencies in extant investigative practices were observed. Solutions proffered encompass the formulation of novel software applications tailored for cryptocurrency analyses, the integration of machine learning and artificial intelligence capabilities, and the employment of advanced analytics to discern patterns and irregularities within blockchain transactions. Furthermore, a pioneering methodology, merging traditional digital forensic strategies with blockchain-specific techniques, is posited for efficacious cryptocurrency inquiries. The analysis underscores the imperative for a renewed paradigm in digital forensic examinations to surmount the challenges integral to cryptocurrency probes. By forging novel methodologies and standardizing investigative procedures, support for legal enforcement endeavors can be enhanced, facilitating the efficacious detection and prosecution of cryptocurrency-associated misdemeanors.

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A Review of Digital Forensics Framework for Blockchain in Cryptocurrency Technology

Cited by 9 publications

References 18 publications

Blockchain and crypto forensics: Investigating crypto frauds

Blockchain and crypto forensics: Investigating crypto frauds

Security Privacy Process Involvement in Cloud Security for Data Preservation against Data Malicious Activity

Cryptocurrency Investigations in Digital Forensics: Contemporary Challenges and Methodological Advances

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