A Framework for IoT Data Acquisition and Forensics Analysis

Chi, Hongmei; Aderibigbe, Temilola; Granville, Bobby C.

doi:10.1109/bigdata.2018.8622019

Cited by 26 publications

(9 citation statements)

References 5 publications

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“…Thus, IoT security relies upon securing each and every layer shown on Figure 4. Accordingly, the IoT security and forensics tools are in high demand [77]. This applies to all IoT-based domains like healthcare, smart home appliances, industrial machines, supply chain and inventory management, smart grid, surveillance, and smart cities.…”

Section: E Where Do We Need the Iot Forensics The Most?mentioning

confidence: 99%

“…Digital forensic practitioners will need to take advantage of the supervised and unsupervised learning algorithms, as used in Big Data analytics, in order to cope with the huge amount of data [68]. Finally, to fully understand the challenges of future cybercrime forensics, practitioners and researchers should adopt a multidisciplinary approach [77] and shift their focus from post-event assistance to preincident detection strategies and proactive standardization practices.…”

Section: E Tracing the Near-future Digital Forensics Versus Forensics In The Internet Of Everything (Ioe)mentioning

confidence: 99%

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A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues

Stoyanova

Nikoloudakis

Panagiotakis

et al. 2020

IEEE Commun. Surv. Tutorials

619

238

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Today is the era of the Internet of Things (IoT). The recent advances in hardware and information technology have accelerated the deployment of billions of interconnected, smart and adaptive devices in critical infrastructures like health, transportation, environmental control, and home automation. Transferring data over a network without requiring any kind of human-to-computer or human-to-human interaction, brings reliability and convenience to consumers, but also opens a new world of opportunity for intruders, and introduces a whole set of unique and complicated questions to the field of Digital Forensics. Although IoT data could be a rich source of evidence, forensics professionals cope with diverse problems, starting from the huge variety of IoT devices and non-standard formats, to the multitenant cloud infrastructure and the resulting multi-jurisdictional litigations. A further challenge is the end-to-end encryption which represents a trade-off between users' right to privacy and the success of the forensics investigation. Due to its volatile nature, digital evidence has to be acquired and analyzed using validated tools and techniques that ensure the maintenance of the Chain of Custody. Therefore, the purpose of this paper is to identify and discuss the main issues involved in the complex process of IoT-based investigations, particularly all legal, privacy and cloud security challenges. Furthermore, this work provides an overview of the past and current theoretical models in the digital forensics science. Special attention is paid to frameworks that aim to extract data in a privacy-preserving manner or secure the evidence integrity using decentralized blockchain-based solutions. In addition, the present paper addresses the ongoing Forensics-as-a-Service (FaaS) paradigm, as well as some promising cross-cutting data reduction and forensics intelligence techniques. Finally, several other research trends and open issues are presented, with emphasis on the need for proactive Forensics Readiness strategies and generally agreed-upon standards.

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Section: E Where Do We Need the Iot Forensics The Most?mentioning

confidence: 99%

Section: E Tracing the Near-future Digital Forensics Versus Forensics In The Internet Of Everything (Ioe)mentioning

confidence: 99%

A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues

Stoyanova

Nikoloudakis

Panagiotakis

et al. 2020

IEEE Commun. Surv. Tutorials

619

238

View full text Add to dashboard Cite

show abstract

“…In the term of IoT based DF investigation, the question arises of whether to investigate devices or data in the case of cloud or else the devices may be viewed as a metadata aspect of the data or if the reverse is true, the cloud computing architectures (PaaS, SaaS, IaaS) allow data fragmentation and distribution among different countries and continents [109]. As IoTA is one of the applications, IoT may face the same challenge in the identification phase of the investigation.…”

Section: Identificationmentioning

confidence: 99%

IoT based Agriculture (IoTA): Architecture, Cyber Attack, Cyber Crime and Digital Forensics Challenges

Rudrakar¹,

Rughani²

2022

Preprint

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The Internet of Things (IoT) is a thriving technology in almost all fields of human life to make their lives easy. Smart Agriculture is one of the IoT applications on which farmers are widely switching to improve productivity and reduce labor costs. As IoT involves the Internet, data transmission technology creates the possibility of privacy/security breaches concerning users’ data. The cybercrime rate may also increase in IoT-based agriculture (IoTA). Thus there must be ready concerning digital forensics in IoTA. Various review articles are available regarding the emerging cyber attack, cybercrime, and forensics challenges in IoT applications like smart home, smart city, smart healthcare, smart grid, smart retail, smart supply chain management, and smart agriculture, while a few review articles on IoTA security and forensic challenges. This review paper is focused on IoTA solutions and their security and forensics challenges. The systematic literature review method has been used for this study which includes articles published from 2011 - 2021. This article has brought the limelight on IoT architecture and its application in agricluture (IoTA) to emphasize on its introduction, architecture, challenges and issues related emerging cybercrimes and digital forensics. At the end, this review paper discusses various challenges in securing IoTA systems and presents future directions for research.

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“…Several IoT data frameworks have been presented in the literature to deal with specific IoT application domains. Recent examples concern forensics [15], smart homes [16] and smart cities [17]. In a more general approach, Jiang et al [18] proposed a framework dealing with typical IoT challenges (large volume of data, different data types, rapid generating data, complicated requirements, etc.).…”

Section: Related Workmentioning

confidence: 99%

Atmosphere, an Open Source Measurement-Oriented Data Framework for IoT

Berta

Kobeissi

Bellotti

et al. 2021

IEEE Trans. Ind. Inf.

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The ever more extensive data collection from Internet of Thing (IoT) devices stresses the need for efficient application development tools. State-of-the-art IoT cloud services are powerful, but the best solutions are proprietary, and there is a growing demand for interoperability and standardization. We have investigated how to develop a nonvendor-locked framework, which exploits state of the art data management technologies, and targets effective and efficient development in this article. Focusing on the concept of measurement, we abstracted an architecture that could be applied in a variety of domains and contexts. We tested the framework and its workflow in four use cases analyzing data and enabling new services in health, automotive, and instruction. Our experience showed the benefits of the development tool, which is not tied to a commercial platform, nor requires the huge set-up times needed to start a project from scratch. The tool is released opensource, particularly supporting collaborative research.

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A Framework for IoT Data Acquisition and Forensics Analysis

Cited by 26 publications

References 5 publications

A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues

A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues

IoT based Agriculture (IoTA): Architecture, Cyber Attack, Cyber Crime and Digital Forensics Challenges

Atmosphere, an Open Source Measurement-Oriented Data Framework for IoT

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