MétaCan
Menu
Back to cohort
Record W2910648169 · doi:10.1109/oceans.2018.8604858

Securing a Janus-Based Flooding Routing Protocol for Underwater Acoustic Networks

2018· article· en· W2910648169 on OpenAlexaff
Hossein Ghannadrezaii, Jean‐François Bousquet

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputer networkComputer scienceRouting protocolWireless Routing ProtocolZone Routing ProtocolOptimized Link State Routing ProtocolEnhanced Interior Gateway Routing ProtocolDistributed computingHazy Sighted Link State Routing ProtocolNetwork packet

Abstract

fetched live from OpenAlex

In this paper, a secure-capable multi-user network protocol proposed which uses the Janus standard in a hybrid cellular/ad hoc topology. In a cellular topology, a self-organized ad hoc mode employing a flooding routing protocol is utilized as a backup when the local gateway-sink node is unreachable. Employing an optimized flooding routing protocol to relay packets in an underwater network increases the packet delivery ratio, and decreases latency. This protocol is applied to a 40node network in an area of 100 square kilometers. For the scenario defined, each packet is forwarded 71 times for it to be received by the destination. This is 29% less than for the common flooding routing protocol, which means notable energy savings in the network. However, adopting a collaborative distributed architecture with multi-hop relaying nodes enhances security threats over the network. This is particularly true when external relay nodes collaborate in the routing mechanism. We investigate vulnerabilities of the Janus-based flooding routing protocol in a self-organized ad hoc topology. We suggest the Elliptic-curve Diffie Hellman (ECDH) key agreement and applying a light weight data encryption on the application layer to protect the communications between the source and destination nodes against eavesdropping and data tampering. As will be demonstrated, applying a security suite on the protocol will impose considerable overhead on the network, since it requires additional handshaking for key exchange, as well as the transmission of large-sized encrypted packets.

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 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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score0.552

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 science0.0000.000
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 head0.035
GPT teacher head0.281
Teacher spread0.246 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations6
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicUnderwater Vehicles and Communication SystemsFrench-language works237,207