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Record W1957358593 · doi:10.1109/jproc.2016.2558521

A Survey on Wireless Security: Technical Challenges, Recent Advances, and Future Trends

2016· article· en· W1957358593 on OpenAlexaff

Bibliographic record

VenueProceedings of the IEEE · 2016
Typearticle
Languageen
FieldComputer Science
TopicSecurity in Wireless Sensor Networks
Canadian institutionsWestern University
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsGovernment of Jiangsu ProvinceNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsEavesdroppingWireless networkWirelessWireless securityWireless Transport Layer SecurityNode (physics)Key (lock)Open researchNetwork security

Abstract

fetched live from OpenAlex

Due to the broadcast nature of radio propagation, the wireless air interface is open and accessible to both authorized and illegitimate users. This completely differs from a wired network, where communicating devices are physically connected through cables and a node without direct association is unable to access the network for illicit activities. The open communications environment makes wireless transmissions more vulnerable than wired communications to malicious attacks, including both the passive eavesdropping for data interception and the active jamming for disrupting legitimate transmissions. Therefore, this paper is motivated to examine the security vulnerabilities and threats imposed by the inherent open nature of wireless communications and to devise efficient defense mechanisms for improving the wireless network security. We first summarize the security requirements of wireless networks, including their authenticity, confidentiality, integrity, and availability issues. Next, a comprehensive overview of security attacks encountered in wireless networks is presented in view of the network protocol architecture, where the potential security threats are discussed at each protocol layer. We also provide a survey of the existing security protocols and algorithms that are adopted in the existing wireless network standards, such as the Bluetooth, Wi-Fi, WiMAX, and the long-term evolution (LTE) systems. Then, we discuss the state of the art in physical-layer security, which is an emerging technique of securing the open communications environment against eavesdropping attacks at the physical layer. Several physical-layer security techniques are reviewed and compared, including information-theoretic security, artificial-noise-aided security, security-oriented beamforming, diversity-assisted security, and physical-layer key generation approaches. Since a jammer emitting radio signals can readily interfere with the legitimate wireless users, we also introduce the family of various jamming attacks and their countermeasures, including the constant jammer, intermittent jammer, reactive jammer, adaptive jammer, and intelligent jammer. Additionally, we discuss the integration of physical-layer security into existing authentication and cryptography mechanisms for further securing wireless networks. Finally, some technical challenges which remain unresolved at the time of writing are summarized and the future trends in wireless security are discussed.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0020.008
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.003

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 head0.020
GPT teacher head0.245
Teacher spread0.225 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1,225
Published2016
Admission routes1
Has abstractyes

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