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Record W2185531306

ENERGY EFFICIENT SECURITY FOR WIRELESS SENSOR NETWORKS

2013· article· en· W2185531306 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2013
Typearticle
Languageen
FieldComputer Science
TopicSecurity in Wireless Sensor Networks
Canadian institutionsnot available
Fundersnot available
KeywordsWireless sensor networkComputer scienceComputer securityWirelessEnergy (signal processing)TelecommunicationsComputer networkPhysics
DOInot available

Abstract

fetched live from OpenAlex

This thesis presents two main achievements. The first is a novel link-layer encryption protocol for wireless sensor networks. The protocol design aims to reduce energy consumption by reducing security-related communication overhead. This is done by merging security-related data of consecutive packets. The merging is based on simple mathematical operations. It helps to reduce energy consumption by eliminating the requirement to transmit security-related fields in the packet. The protocol is named the Compact Security Protocol and is referred to as C-Sec. In addition to energy savings, the C-Sec protocol also includes a unique security feature of hiding the packet header information. This feature makes it more difficult to trace the flow of wireless communication, and helps to minimize the effect of replay attacks. The C-Sec protocol is rigorously tested and compared with well-known related protocols. Performance evaluations demonstrate that C-Sec protocol outperforms other protocols in terms of energy savings. The protocol is evaluated with respect to other performance metrics including queuing delay and error probability.\n \n \n The C-Sec operation requires fast encryption, which leads to a second major contribution: The SN-Sec, a 32-bit RISC secure wireless sensor platform with hardware cryptographic primitives. The security vulnerabilities in current WSNs platforms are scrutinized and the main approaches to implementing their cryptographic primitives are compared in terms of security, time, and energy efficiency. The SN-Sec secures these vulnerabilities and provides more time and energy efficiency. The choice of cryptographic primitives for SN-Sec is based on their compatibility with the constrained nature of WSNs and their security. The AES implementation has the best data-path and S-Box design in the literature. All SHA family members are implemented and compared to choose the most compatible with WSN constraints. An efficient elliptic-curve processor design is proposed. It has the least mathematical operations compared to elliptic-curve processors proposed for WSNs in the literature. It also exploits parallelism among mathematical operations to compute elliptic-curve point multiplication with minimal amount of clock cycles. SN-Sec is implemented using VHDL. Experimental results using synthesis for Spartan-6 low-power FPGA shows that the proposed design has very reasonable computational time and energy consumption.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.948
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.003
GPT teacher head0.135
Teacher spread0.133 · 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