1,268 research outputs found
A Cost-efficient IoT Forensics Framework with Blockchain
IoT devices have been adopted widely in the last decade which enabled
collection of various data from different environments. The collected data is
crucial in certain applications where IoT devices generate data for critical
infrastructure or systems whose failure may result in catastrophic results.
Specifically, for such critical applications, data storage poses challenges
since the data may be compromised during the storage and the integrity might be
violated without being noticed. In such cases, integrity and data provenance
are required in order to be able to detect the source of any incident and prove
it in legal cases if there is a dispute with the involved parties. To address
these issues, blockchain provides excellent opportunities since it can protect
the integrity of the data thanks to its distributed structure. However, it
comes with certain costs as storing huge amount of data in a public blockchain
will come with significant transaction fees. In this paper, we propose a highly
cost effective and reliable digital forensics framework by exploiting multiple
inexpensive blockchain networks as a temporary storage before the data is
committed to Ethereum. To reduce Ethereum costs,we utilize Merkle trees which
hierarchically stores hashes of the collected event data from IoT devices. We
evaluated the approach on popular blockchains such as EOS, Stellar, and
Ethereum by presenting a cost and security analysis. The results indicate that
we can achieve significant cost savings without compromising the integrity of
the data
Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future
Given the exponential expansion of the internet, the possibilities of
security attacks and cybercrimes have increased accordingly. However, poorly
implemented security mechanisms in the Internet of Things (IoT) devices make
them susceptible to cyberattacks, which can directly affect users. IoT
forensics is thus needed for investigating and mitigating such attacks. While
many works have examined IoT applications and challenges, only a few have
focused on both the forensic and security issues in IoT. Therefore, this paper
reviews forensic and security issues associated with IoT in different fields.
Future prospects and challenges in IoT research and development are also
highlighted. As demonstrated in the literature, most IoT devices are vulnerable
to attacks due to a lack of standardized security measures. Unauthorized users
could get access, compromise data, and even benefit from control of critical
infrastructure. To fulfil the security-conscious needs of consumers, IoT can be
used to develop a smart home system by designing a FLIP-based system that is
highly scalable and adaptable. Utilizing a blockchain-based authentication
mechanism with a multi-chain structure can provide additional security
protection between different trust domains. Deep learning can be utilized to
develop a network forensics framework with a high-performing system for
detecting and tracking cyberattack incidents. Moreover, researchers should
consider limiting the amount of data created and delivered when using big data
to develop IoT-based smart systems. The findings of this review will stimulate
academics to seek potential solutions for the identified issues, thereby
advancing the IoT field.Comment: 77 pages, 5 figures, 5 table
Securing Our Future Homes: Smart Home Security Issues and Solutions
The Internet of Things, commonly known as IoT, is a new technology transforming businesses, individuals’ daily lives and the operation of entire countries. With more and more devices becoming equipped with IoT technology, smart homes are becoming increasingly popular. The components that make up a smart home are at risk for different types of attacks; therefore, security engineers are developing solutions to current problems and are predicting future types of attacks. This paper will analyze IoT smart home components, explain current security risks, and suggest possible solutions. According to “What is a Smart Home” (n.d.), a smart home is a home that always operates in consideration of security, energy, efficiency and convenience, whether anyone is home or not
Blockchain based digital forensics investigation framework in the internet of things and social systems
The decentralised nature of blockchain technologies can well match the needs of integrity and provenances of evidences collecting in digital forensics across jurisdictional borders. In this work, a novel blockchain based digital forensics investigation framework in the Internet of Things (IoT) and social systems environment is proposed, which can provide proof of existence and privacy preservation for evidence items examination. To implement such features, we present a block enabled forensics framework for IoT, namely IoT forensic chain (IoTFC), which can offer forensic investigation with good authenticity, immutability, traceability, resilience, and distributed trust between evidential entitles as well as examiners. The IoTFC can deliver a gurantee of traceability and track provenance of evidence items. Details of evidence identification, preservation, analysis, and presentation will be recorded in chains of block. The IoTFC can increase trust of both evidence items and examiners by providing transparency of the audit train. The use case demonstrated the effectiveness of proposed method
ForensiBlock: A Provenance-Driven Blockchain Framework for Data Forensics and Auditability
Maintaining accurate provenance records is paramount in digital forensics, as
they underpin evidence credibility and integrity, addressing essential aspects
like accountability and reproducibility. Blockchains have several properties
that can address these requirements. Previous systems utilized public
blockchains, i.e., treated blockchain as a black box, and benefiting from the
immutability property. However, the blockchain was accessible to everyone,
giving rise to security concerns and moreover, efficient extraction of
provenance faces challenges due to the enormous scale and complexity of digital
data. This necessitates a tailored blockchain design for digital forensics. Our
solution, Forensiblock has a novel design that automates investigation steps,
ensures secure data access, traces data origins, preserves records, and
expedites provenance extraction. Forensiblock incorporates Role-Based Access
Control with Staged Authorization (RBAC-SA) and a distributed Merkle root for
case tracking. These features support authorized resource access with an
efficient retrieval of provenance records. Particularly, comparing two methods
for extracting provenance records off chain storage retrieval with Merkle root
verification and a brute-force search the offchain method is significantly
better, especially as the blockchain size and number of cases increase. We also
found that our distributed Merkle root creation slightly increases smart
contract processing time but significantly improves history access. Overall, we
show that Forensiblock offers secure, efficient, and reliable handling of
digital forensic dataComment: This work has been submitted to the IEEE for possible publication.
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Security and Privacy for Green IoT-based Agriculture: Review, Blockchain solutions, and Challenges
open access articleThis paper presents research challenges on security and privacy issues in the field of green IoT-based agriculture. We start by describing a four-tier green IoT-based agriculture architecture and summarizing the existing surveys that deal with smart agriculture. Then, we provide a classification of threat models against green IoT-based agriculture into five categories, including, attacks against privacy, authentication, confidentiality, availability, and integrity properties. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward secure and privacy-preserving technologies for IoT applications and how they will be adapted for green IoT-based agriculture. In addition, we analyze the privacy-oriented blockchain-based solutions as well as consensus algorithms for IoT applications and how they will be adapted for green IoT-based agriculture. Based on the current survey, we highlight open research challenges and discuss possible future research directions in the security and privacy of green IoT-based agriculture
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