Abstract
Due to businesses’ growing use of IoT services in their day-to-day operations and the increased use of smart devices, digital forensic investigations involving such systems will need increasingly sophisticated digital evidence collection and processing. The majority of IoT systems are composed of disparate software and hardware components, which may pose security and privacy concerns. Recently, blockchain technology was presented as one of the options for achieving IoT security via the use of an immutable ledger, a decentralized architecture, and strong cryptographic primitives. Integrating blockchain platforms with IoT-based applications, on the other hand, poses a number of difficulties owing to the trustworthiness, integrity, and real-time responsiveness of IoT data. However, certain IoT devices may be incompatible with existing blockchain-based IoT forensic methods for additional digital evidence processing owing to their usage of conventional hash. A critical feature of cryptographic hash functions is that even if just one bit of the input is altered, the output acts pseudo-randomly, making it impossible to identify identical files. However, in the field of computer forensics, it is essential to locate comparable files (e.g., various versions of a file); therefore, we need a hash function that preserves similarity. It is getting more difficult to establish how forensic investigators might utilize traces from such devices. To effectively deal with IoT digital forensics applications, this article presents an improved blockchain-based IoT digital forensics architecture that uses the fuzzy hash to construct the Blockchain’s Merkle tree in addition to the conventional hash for authentication. Fuzzy hashing enables the identification of potentially damning documents that might otherwise remain undiscovered using conventional hashing techniques. By comparing blocks/files to all nodes in the blockchain network using fuzzy hash similarity, the digital forensics investigator will be able to verify their authenticity. To support the proof of concept, we simulated the suggested model.
Highlights
Digital forensics is getting increasingly difficult to perform as a result of the exponential growth of computing devices and computer-enabled paradigms, posing new difficulties for remote data processing
Current digital forensic tools, investigative frameworks, and procedures are incapable of addressing the Internet of Things (IoT) environment's heterogeneity and dispersion characteristics
All the studies that discussed the IoT digital forensics [1][3][5][8] confirmed that utilizing blockchain technology provides security against attacks as the IoT forensic investigation framework is built on private blockchain network
Summary
Digital forensics is getting increasingly difficult to perform as a result of the exponential growth of computing devices and computer-enabled paradigms, posing new difficulties for remote data processing. With billions of new and growing devices, the IoT expands the security risks. While the IoT inherits the same monitoring needs as cloud computing, the associated difficulties are exacerbated by the volume, diversity, and velocity of data [1]. Current digital forensic tools, investigative frameworks, and procedures are incapable of addressing the IoT environment's heterogeneity and dispersion characteristics. These features provide significant difficulties for digital forensic investigators and law enforcement agencies. The complexity of the IoT system and the absence of an integrated standard complicate the collection of forensic evidence by security and law enforcement authorities
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