IoT Forensics: An Overview of the Current Issues and Challenges

Janarthanan, Tharmini; Bagheri, Maryam; Zargari, Shahrzad

doi:10.1007/978-3-030-60425-7_10

Cited by 24 publications

(6 citation statements)

References 42 publications

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“…In 2021, Janarthanan et al [ 149 ] reviewed the solutions and frameworks related to IoT forensics that were presented in recent studies. They analysed various digital forensics frameworks specific to the IoT, based on the forensic process stages, and evaluated their strengths and limitations.…”

Section: Cyber Forensics In Smart Citiesmentioning

confidence: 99%

“…Year Approach/Experiment IoT Zia et al [136] 2017 An application-specific digital forensics investigative model for the IoT Rizal et al [137] 2018 An evaluated network forensics method to detect flooding attacks Hou et al [138] 2019 A survey of IoT forensics in the technical, temporal, and spatial dimensions Jayakrishnan and Vasanthi [139] 2019 An attack simulation to identify advanced encryption standard (AES) keys Qatawneh et al [140] 2019 A digital forensics investigation model (DFIM) for the IoT Yaqoob et al [141] 2019 An IoT taxonomy based on different forensics processes Stoyanova et al [142] 2020 Cloud security challenges and data acquisition using blockchain Patil et al [143] 2020 A comparative analysis of IoT cyber forensics research Jayakrishnan and Vasanthi [144] 2020 A process model for forensics using an IoT HoneyNetCloud Atlam et al [145] 2020 IoT forensics techniques and the need for AI in IoT forensics Patel and Malek [146] 2020 Existing IoT forensics frameworks and their challenges Yang et al [147] 2020 Biometric-based authentication and forensics for the IoT Bandil and Al-Masri [148] 2020 Real-time events associated with IoT data streams Janarthanan et al [149] 2021 Challenges in smart home investigations and forensics Surange and Khatri [150] 2021 A survey of developments in IoT forensics and the identification of research gaps Kim et al [151] 2022 A data acquisition framework for smart devices Ganesh et al [152] 2022 AI use cases of forensics in blockchain, the IoT, and cloud computing…”

Section: Category Authorsmentioning

confidence: 99%

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Cybersecurity and Cyber Forensics for Smart Cities: A Comprehensive Literature Review and Survey

Kim

Alshenaifi

Ramachandran

et al. 2023

Sensors

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Smart technologies, such as the Internet of Things (IoT), cloud computing, and artificial intelligence (AI), are being adopted in cities and transforming them into smart cities. In smart cities, various network technologies, such as the Internet and IoT, are combined to exchange real-time information, making the everyday lives of their residents more convenient. However, there is a lack of systematic research on cybersecurity and cyber forensics in smart cities. This paper presents a comprehensive review and survey of cybersecurity and cyber forensics for smart cities. We analysed 154 papers that were published from 2015 to 2022 and proposed a new framework based on a decade of related research papers. We identified four major areas and eleven sub-areas for smart cities. We found that smart homes and the IoT were the most active research areas within the cybersecurity field. Additionally, we found that research on cyber forensics for smart cities was relatively limited compared to that on cybersecurity. Since 2020, there have been many studies on the IoT (which is a technological component of smart cities) that have utilized machine learning and deep learning. Due to the transmission of large-scale data through IoT devices in smart cities, ML and DL are expected to continue playing critical roles in smart city research.

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Section: Cyber Forensics In Smart Citiesmentioning

confidence: 99%

Section: Category Authorsmentioning

confidence: 99%

Cybersecurity and Cyber Forensics for Smart Cities: A Comprehensive Literature Review and Survey

Kim

Alshenaifi

Ramachandran

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…IoT forensics processes comprise three levels of forensics namely, device-level forensics, network-level forensics, and cloud-level forensics [26]. Due to the distributed nature and heterogeneity of IoT infrastructures as well as limitations of digital forensics tools, IoT forensics at the network and cloud levels have not been completely used in digital forensics and efforts to design standard frameworks, models, or methods for IoT forensics are still in their infancy [27]- [29]. However, there have been attempts to extract and analyze data from devices such as Google Home and Google Assistant apps [30].…”

Section: ) Internet Of Things (Iot) Forensicsmentioning

confidence: 99%

Cryptographic Techniques for Data Privacy in Digital Forensics

Ogunseyi,

Adedayo

2023

IEEE Access

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The acquisition and analysis of data in digital forensics raise different data privacy challenges. Many existing works on digital forensic readiness discuss what information should be stored and how to collect relevant data to facilitate investigations. However, the cost of this readiness often directly impacts the privacy of innocent third parties and suspects if the collected information is irrelevant. Approaches that have been suggested for privacy-preserving digital forensics focus on the use of policy, non-cryptography-based, and cryptography-based solutions. Cryptographic techniques have been proposed to address issues of data privacy during data analysis. As the utilization of some of these cryptographic techniques continues to increase, it is important to evaluate their applicability and challenges in relation to digital forensics processes. This study provides digital forensics investigators and researchers with a roadmap to understanding the data privacy challenges in digital forensics and examines the various privacy techniques that can be utilized to tackle these challenges. Specifically, we review the cryptographic techniques applied for privacy protection in digital forensics and categorize them within the context of whether they support trusted third parties, multiple investigators, and multi-keyword searches. We highlight some of the drawbacks of utilizing cryptography-based methods in privacy-preserving digital forensics and suggest potential solutions to the identified shortcomings. In addition, we propose a conceptual privacypreserving digital forensics (PPDF) model that is based on the use of cryptographic techniques and analyze the model within the context of the above-mentioned factors. An evaluation of the model is provided through a consideration of identified factors that may affect an investigation. Lastly, we provide an analysis of how existing principles for preserving privacy in digital forensics are addressed in our PPDF model. Our evaluation shows that the model aligns with many of the existing privacy principles recommended for privacy protection in digital forensics.

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“…The resulting dataset would almost certainly be larger and more dynamic. Although IoT forensic disciplines are evolving there is currently little research looking into this specific filed particularly with open IoT-related vulnerabilities [45][46][47][48][49].…”

Section: Issues In Iot Forensicsmentioning

confidence: 99%

Current Issues and Challenges with Scientific Validation of Digital Evidence

Raza¹,

Anwar²,

Khan³

2022

RCES

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Computer forensics is an important part of any cybercrime investigation because it allows law enforcement to collect and examine data that can be used to prove a cybercrime. Despite the occasionally justified use of proof, it is frequently met with skepticism and ambiguity in the courts. There is currently a moratorium on the use of untested forensic method in courtroom court cases, it is still difficult to consistently prove the proof obtained through this method. Because of the nature of electronic records and the privacy restrictions that surround them, it is no longer possible to rely solely on the information gathered through this process. The purpose of this article is to discuss current challenges and issues in the field of computer forensics that are impeding scientific validation of digital forensics.

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IoT Forensics: An Overview of the Current Issues and Challenges

Cited by 24 publications

References 42 publications

Cybersecurity and Cyber Forensics for Smart Cities: A Comprehensive Literature Review and Survey

Cybersecurity and Cyber Forensics for Smart Cities: A Comprehensive Literature Review and Survey

Cryptographic Techniques for Data Privacy in Digital Forensics

Current Issues and Challenges with Scientific Validation of Digital Evidence

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