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Record W2890436618 · doi:10.1002/spy2.43

Special Issue on security and privacy in Internet of Things and cloud computing systems

2018· article· en· W2890436618 on OpenAlex
Isaac Woungang, Sanjay Kumar Dhurandher, Joel J. P. C. Rodrigues, Ahmed Awad

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSecurity and Privacy · 2018
Typearticle
Languageen
FieldComputer Science
TopicIoT and Edge/Fog Computing
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsInternet of ThingsComputer securityInternet privacyCloud computingCloud computing securityComputer science

Abstract

fetched live from OpenAlex

Special Issue on security and privacy in Internet of Things and cloud computing systemsThe strong growth in mobile devices, pervasive networked embedded systems, and wireless sensors provides a flexible and cheap infrastructure for collecting and monitoring real-world data, nearly everywhere.This is complemented by the rapid increase in information and computing power offered by computing clusters, emerging cloud systems, and information services over stationary and dynamic networks.The integration of network computing and mobile systems presents new challenges with respect to the dependability of integrated applications: accepted measures of availability, costs, and quality of service for high-bandwidth, high-quality stationary systems have to be rethought, facing possibly new dependability paradigms for cheap, resource restricted, and unreliable mobile systems with low-bandwidth communication facilities.On the other hand, the proliferation of devices, which are able to directly connect to the Internet, has led to a new computing and communication paradigm known as Internet of Things (IoT).At the same time, new threat vectors have emerged that leverage and magnify traditional hacking methods, enabling large-scale and intelligence-driven attacks against a variety of platforms, including mobile, cloud, IoT, as well as conventional networks.The consequence of such fast-evolving environment is the pressing need for effective and efficient paradigms, approaches, and tools for building, maintaining, and managing secure and dependable systems.This Special Issue addresses security and privacy issues related to the design, analysis, and implementation of IoT and cloud computing infrastructures, systems, architectures, algorithms, and protocols.We have received many manuscripts.Only four of these manuscripts of high quality were selected for this Special Issue.Each selected paper was blindly reviewed by at least three qualified reviewers in the field.Below is a brief summary of each manuscript.The first paper entitled "The Internet of Things and the Smart City: Legal challenges with digital forensics, privacy, and security" by Losavio et al 1 investigates the threats to personal autonomy, personality, and privacy in IoT and smart city and proposes a comprehensive survey of related legal challenges.The technical-legal interaction involved and how they can be informative with respect to privacy and security with the IoT and smart city are examined in-depth, leading to a qualitative comparison of legal regimes of digital forensics and investigations among nations worldwide.The second paper entitled "Secure cloud computing: reference architecture for measuring instrument under legal control" by Oppermann et al 2 introduces a secure cloud reference architecture for measuring instruments, addressing both requirements and roles in the Legal Metrology framework.The general approach of the proposed reference architecture is evaluated to find out whether cloud computing can be integrated into the legal framework.A bottom-up approach is considered, where each layer of the cloud is addressed and thoroughly tested against the essential requirements for Legal Metrology.On top of this, a secure communication protocol for encrypted data is devised to address the demand of integrity of encrypted measurements throughout their lifecycle.Finally, for the purpose of detecting anomalies and classifying the system behavior depending on their severity and impact, a continuous monitoring approach is presented.The third paper entitled "Passphrase protected device-to-device mutual authentication schemes for smart homes" by Raniyal et al 3 proposes two novel passphrase protected device-to-device mutual authentication schemes for smart homes, in which the keys are protected using passphrases and a centralized server provides a proxy-passphrase service to smart home devices.The High-Level Protocol Specification Language is used to model the proposed protocols, and a security analysis is provided using the SPAN/AVISPA tool, demonstrating that the proposed schemes can achieve the goals of secrecy of secret keys and device-to-device mutual authentication.The fourth and last paper entitled "A review and an empirical analysis of privacy policy and notices for consumer Internet of things" by Perez et al 4 proposes a comprehensive review of issues related to privacy policies and notices of six consumer IoT devices and systems available in the U.S. market as of November 2017.An analysis of privacy practices is presented about the practices that manufacturers provide related to data collection, data ownership, data modification, data security, external data sharing, policy change, and policies for specific audiences.To this end, an experimental test bed is designed and used to investigate the traffic generated when two voice-activated intelligent assistant devices, namely the Amazon Echo Dot 2.0 and the

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score0.841

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.253
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it