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Record W2761002106 · doi:10.1002/nem.2010

Special issue on security for emerging open networking technologies

2017· article· en· W2761002106 on OpenAlexaff
Carol Fung, Mohamed Faten Zhani, Weverton Cordeiro, Jérôme François

Bibliographic record

VenueInternational Journal of Network Management · 2017
Typearticle
Languageen
FieldComputer Science
TopicNetwork Security and Intrusion Detection
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsComputer scienceComputer securityData science

Abstract

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Emerging paradigms such as SDN, NFV, and programmable networks are reshaping the way networks are designed, deployed, and managed. The benefits are manifold, including an unprecedented flexibility for network operations and management, and a favourable environment for delivering innovative network applications and services. This paradigm shift brings however a multitude of security challenges that have to be addressed in order to provide secure, trustworthy, and privacy-preserving data communication and network services. The main goal of this special issue on Security for Emerging Open Networking Technologies is bringing together state-of-the-art research on the various security aspects related to next-generation networking paradigms. The submitted papers have been carefully peer-reviewed for technical quality, originality, impact, and relevance. Based on the reviews, 8 high-quality papers were selected for publication. All papers focus on how to properly address the security challenges mentioned earlier, in areas such as SDN, IoT, and Information-centric networking. The first paper “Trust Management in Cognitive Radio Networks: A Survey,” by Bennaceur et al, provides a comprehensive review about existing Trust and Reputation Management (TRM) techniques for cognitive radio networks. The authors expose existing classifications of TRM techniques, followed by a classification scheme that takes into account different TRM properties and approaches. In their paper “Design, Implementation and Performance Evaluation of Identity-based Cryptography in ONOS,” Lam et al designed, implemented, and evaluated an Identity-Based Cryptography (IBC) protocol to secure the East/West-bound intra-cluster communication of Open Networking Operating System (ONOS) for Distributed Software-Defined Networks. The purpose of the IBC system is to solve the issues existed in the ONOS system such as the complicated key management of TLS. The third paper “Secure and Efficient Verification for Data Aggregation in Front-End Internet of Things,” by Boudia et al, proposes Safe IoT. It is a scheme that provides an end-to-end privacy protection for Internet of thing (IoT)–based wireless sensor networks (WSNs). The scheme allows early detection of attacks through a hop-by-hop verification, thus reducing the need to rely entirely on sink node for verification. The solution is implemented on MicaZ and TelosB motes, based on an enhanced version of TinyECC. The fourth paper “NomadiKey: User Authentication for Smart Devices based on Nomadic Keys” is brought by Souza et al and introduces NomadiKey, a user-to-device authentication mechanism based on nomadic keyboard keys. NomadiKey increases security level by placing keys at different screen coordinates each time it is activated. The authors also design an extension to NomadiKey that employs out-of-band channels to thwart shoulder-surfing adversaries and compared it with other user authentication mechanisms. In their paper “A Procedure for Fast and Efficient Probing of Heterogeneous IoT Networks,” Metongnon and Sadre focus on network scans that are aiming at identifying vulnerable nodes in heterogeneous IoT environments. They propose a novel approach to increase the efficiency of network scans in heterogeneous networks by leveraging active round-trip time measurements. Using such measurements, their approach is able to adapt the scan strategy to the network characteristics in order to reduce probe losses and thereby improve the speed and efficiency of the scan. The paper “Booter List Generation: The Basis for Investigating DDoS-for-hire Websites,” by Santanna et al, investigates the expansion of Distributed Denial of Service (DDoS) launched from websites known as Booters or Stressers that are offering DDoS on the Internet as a paid service (DDoS-as-a-Service). They hence present a rigorous methodology to identify Booters existing in the Internet using URL crawling and classification techniques. The generated list of Booters is useful to identify and track attackers and suspicious websites. In their paper “Rendezvous-based access control for Information-Centric Architectures,” Fotiou and Bander address the problem of managing accesses to contents in Information Centric Networks (ICNs). Indeed, original designs of ICN architectures promote open distribution of contents by leveraging automatic in-network caching. A rendezvous mechanism is proposed and relies on Identity-Based Encryption in order to re-encrypt data to make content only available to authorized users. The authors particularly adapts this approach to the Publish-Subscribe Internet ICN architecture. Finally, Dridi et al investigated the impact of Denial-of-Service (DoS) attacks on Software-Defined Networks (SDN) in their paper “A Holistic Approach to Mitigating DoS Attacks in SDN Networks.” The authors show that such attacks could easily overload the SDN controller and flood switch forwarding tables, resulting in a critical degradation of the network performance. They propose SDN-Guard, a novel approach to mitigate DoS attack in SDN networks by leveraging an intrusion detection system to identify the attacks and dynamically managing the malicious traffic and the forwarding rules. The authors also investigate techniques to reduce the traffic that should be analysed by the intrusion system, such as packet sampling and optimal IDS placement in the SDN network. The Guest Editors of this International Journal of Network Management (IJNM) Special Issue would like to thank all authors for the high quality submissions received. We also thank the reviewers for the considerable time and invaluable effort to provide high-quality reviews and constructive comments, which enabled authors to significantly improve their papers and helped us to select the best manuscripts. We also extend our thanks to the IJNM Editorial Board, in particular James Hong and Filip De Turck, for giving us this opportunity to contribute as guest editors to the ongoing development and success of IJNM. Finally, we thank the Wiley Editorial Team, in special Rechelle Nabas and Cathryn Jordan, for the support and help throughout the editorial process.

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)0.003
metaresearch head score (Gemma)0.008
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.081
Threshold uncertainty score0.269

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0070.007
Open science0.0020.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0810.032

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 head0.025
GPT teacher head0.316
Teacher spread0.291 · 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
GenreEditorial

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".

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Citations1
Published2017
Admission routes1
Has abstractyes

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