Lawful evidence management by law enforcement agencies during the Digital Forensics (DF) investigation is of supreme importance since it convicts suspects of crimes. Therefore, a secure and efficient evidence management system should have certain features such as tamper-resistant, traceability, auditability, privacy preservation, and fine-grained access control. Unfortunately, the state-of-the-art DF is facing new challenges due to the recent technological advancements in various areas, such as the Internet of Things (IoT), Cyber-Physical Systems (CPS), communication technologies, and cloud computing, which are heavily being used in our daily lives. These technologies are also the primary sources for evidence extraction in most crimes. Hence, forensic experts need novel tools and methodologies to keep pace with these new technologies. The inherent properties of blockchain, such as transparency, immutability, secure anonymity, and auditability, make it a suitable solution to address DF’s new challenges. To this end, we provide a compact survey on state-of-the-art blockchain-based DF investigation techniques along with their advantages and disadvantages. We will discuss all critical issues and challenges involved in forensic investigations and evidence management systems, focusing on security and privacy challenges. Moreover, blockchain-based solutions that target specific service areas such as IoT and cloud computing forensics will be discussed in detail due to their usage in many application domains. Finally, we will present the challenges that existing blockchain-based forensics solutions face, along with possible ways of addressing them.

Internet-of-Thing (IoT) faces various security attacks. Different solutions exist to mitigate the intrusion problems. However, the existing solutions lack behind in dealing with heterogeneity of attack sources and features. The future anticipated demand of devices' connections also urge the need of new solutions addressing the concerns of time consumption and complexity. In this article, we show a novel solution for the intrusion detection in IoT framework. We configure the intrusion detection in the edge computing layer so that the effect of the attack is not propagated to the clouds. Our solution uses cerebellar model articulation controller with kernel map. This combination is very new in the direction of intrusion detection; hence, it emphasizes the novelty of our proposed intrusion detection solution. We name our solution as Cerebellar Model Articulation Controller based Intrusion Detection System (CMACIDS). Additionally, we use spline fitting to the kernel mapping for the model fit; this adds on another novel contribution to CMACIDS. The results obtained with our detection system are compared with the state-of-the-art solutions in terms of complexity, false alarms, and precision of detection. The analysis of the comparative study proves the efficiency of the solution and makes CMACIDS suitable for IoT paradigm.

Digital forensic in Internet-of-Thing (IoT) paradigm is critical due to its heterogeneity and lack of transparency of evidence processing. Moreover, cross-border legalization makes a hindrance in such process pertaining to the cloud forensic issues. This urges a forensic framework for IoT which provides distributed computing, decentralization, and transparency of forensic investigation of digital evidences in cross-border perspectives. To this end, we propose a framework for IoT forensics that addresses the above mentioned issues. The proposed solution called Internet-of-Forensics (IoF) considers a blockchain tailored IoT framework for digital forensics. It provides a transparent view of the investigation process that involves all the stakeholders (e.g., heterogeneous devices, and cloud service providers) in a single framework. It uses blockchain-based case chain to deal with the investigation process including chain-of-custody and evidence chain. Consensus is used for consortium to solve the problems of cross-border legalization. This is also beneficial for a transparent and ease of forensic reference. The programmable lattice-based cryptographic primitives produce reduced complexities. It shows benefits for power-aware devices and puts an add-on to the novelty of the presented idea. IoF is generic; hence, it can be used by autonomous security operation centers, cyber-forensic investigators and manually initiated evidences under chain-of-custody for man-made crimes. Security services are assured as required by the framework. IoF is experimented and compared with the other state-of-the-art frameworks. The outcomes and analysis prove the efficiency of IoF concerning complexity, time consumption, memory and CPU utilization, gas consumption, and energy analysis.