An intelligent defense and filtration platform for network traffic

Mehrnoosh Monshizadeh; Vikramajeet Khatri; Buse Atli; Raimo Kantola

doi:10.1007/978-3-030-02931-9_9

An intelligent defense and filtration platform for network traffic

Mehrnoosh Monshizadeh^*, Vikramajeet Khatri, Buse Atli, Raimo Kantola

^*Tämän työn vastaava kirjoittaja

Nokia Bell Labs

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

3 Sitaatiot (Scopus)

Abstrakti

Hybrid Anomaly Detection Model (HADM) is a security platform to detect and prevent cyber-attacks on communication networks. The platform uses a combination of linear and learning algorithms combined with protocol analyzer. The linear algorithms filter and extract distinctive attributes and features of the cyber-attacks while the learning algorithms use these attributes and features to identify new types of cyber-attacks. The protocol analyzer in this platform classifies and filters vulnerable protocols to avoid unnecessary computation load. The use of linear algorithms in conjunction with learning algorithms allows the HADM to achieve improved efficiency in terms of accuracy and computation time in order to detect cyber-attacks over existing solutions.

Alkuperäiskieli	Englanti
Otsikko	Wired/Wireless Internet Communications - 16th IFIP WG 6.2 International Conference, WWIC 2018, Proceedings
Toimittajat	Kaushik Roy Chowdhury, Marco Di Felice, Bo Sheng, Ibrahim Matta
Kustantaja	Springer
Luku	2
Sivut	107-118
Sivumäärä	12
ISBN (elektroninen)	978-3-030-02931-9
ISBN (painettu)	978-3-030-02930-2
DOI - pysyväislinkit	https://doi.org/10.1007/978-3-030-02931-9_9
Tila	Julkaistu - 1 tammik. 2018
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisussa
Tapahtuma	International Conference on Wired/Wireless Internet Communications - Boston, Yhdysvallat Kesto: 18 kesäk. 2018 → 20 kesäk. 2018 Konferenssinumero: 16

Julkaisusarja

Nimi	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vuosikerta	10866 LNCS
ISSN (painettu)	0302-9743
ISSN (elektroninen)	1611-3349

Conference

Conference	International Conference on Wired/Wireless Internet Communications
Lyhennettä	WWIC
Maa/Alue	Yhdysvallat
Kaupunki	Boston
Ajanjakso	18/06/2018 → 20/06/2018

Pääsy asiakirjaan

10.1007/978-3-030-02931-9_9

Muut tiedostot ja linkit

Link to publication in Scopus

Siteeraa tätä

Monshizadeh, M., Khatri, V., Atli, B., & Kantola, R. (2018). An intelligent defense and filtration platform for network traffic. teoksessa K. R. Chowdhury, M. Di Felice, B. Sheng, & I. Matta (Toimittajat), Wired/Wireless Internet Communications - 16th IFIP WG 6.2 International Conference, WWIC 2018, Proceedings (Sivut 107-118). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vuosikerta 10866 LNCS). Springer. https://doi.org/10.1007/978-3-030-02931-9_9

Monshizadeh, Mehrnoosh ; Khatri, Vikramajeet ; Atli, Buse et al. / An intelligent defense and filtration platform for network traffic. Wired/Wireless Internet Communications - 16th IFIP WG 6.2 International Conference, WWIC 2018, Proceedings. Toimittaja / Kaushik Roy Chowdhury ; Marco Di Felice ; Bo Sheng ; Ibrahim Matta. Springer, 2018. Sivut 107-118 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "An intelligent defense and filtration platform for network traffic",

abstract = "Hybrid Anomaly Detection Model (HADM) is a security platform to detect and prevent cyber-attacks on communication networks. The platform uses a combination of linear and learning algorithms combined with protocol analyzer. The linear algorithms filter and extract distinctive attributes and features of the cyber-attacks while the learning algorithms use these attributes and features to identify new types of cyber-attacks. The protocol analyzer in this platform classifies and filters vulnerable protocols to avoid unnecessary computation load. The use of linear algorithms in conjunction with learning algorithms allows the HADM to achieve improved efficiency in terms of accuracy and computation time in order to detect cyber-attacks over existing solutions.",

keywords = "Anomaly detection, Cloud computing, Internet of things, Machine learning, Security",

author = "Mehrnoosh Monshizadeh and Vikramajeet Khatri and Buse Atli and Raimo Kantola",

year = "2018",

month = jan,

day = "1",

doi = "10.1007/978-3-030-02931-9_9",

language = "English",

isbn = "978-3-030-02930-2",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "107--118",

editor = "Chowdhury, {Kaushik Roy} and {Di Felice}, Marco and Bo Sheng and Ibrahim Matta",

booktitle = "Wired/Wireless Internet Communications - 16th IFIP WG 6.2 International Conference, WWIC 2018, Proceedings",

address = "Germany",

note = "International Conference on Wired/Wireless Internet Communications, WWIC ; Conference date: 18-06-2018 Through 20-06-2018",

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Monshizadeh, M, Khatri, V, Atli, B & Kantola, R 2018, An intelligent defense and filtration platform for network traffic. julkaisussa KR Chowdhury, M Di Felice, B Sheng & I Matta (toim), Wired/Wireless Internet Communications - 16th IFIP WG 6.2 International Conference, WWIC 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vuosikerta 10866 LNCS, Springer, Sivut 107-118, International Conference on Wired/Wireless Internet Communications, Boston, Massachusetts, Yhdysvallat, 18/06/2018. https://doi.org/10.1007/978-3-030-02931-9_9

An intelligent defense and filtration platform for network traffic. / Monshizadeh, Mehrnoosh; Khatri, Vikramajeet; Atli, Buse et al.
Wired/Wireless Internet Communications - 16th IFIP WG 6.2 International Conference, WWIC 2018, Proceedings. toim. / Kaushik Roy Chowdhury; Marco Di Felice; Bo Sheng; Ibrahim Matta. Springer, 2018. s. 107-118 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vuosikerta 10866 LNCS).

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

TY - GEN

T1 - An intelligent defense and filtration platform for network traffic

AU - Monshizadeh, Mehrnoosh

AU - Khatri, Vikramajeet

AU - Atli, Buse

AU - Kantola, Raimo

N1 - Conference code: 16

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Hybrid Anomaly Detection Model (HADM) is a security platform to detect and prevent cyber-attacks on communication networks. The platform uses a combination of linear and learning algorithms combined with protocol analyzer. The linear algorithms filter and extract distinctive attributes and features of the cyber-attacks while the learning algorithms use these attributes and features to identify new types of cyber-attacks. The protocol analyzer in this platform classifies and filters vulnerable protocols to avoid unnecessary computation load. The use of linear algorithms in conjunction with learning algorithms allows the HADM to achieve improved efficiency in terms of accuracy and computation time in order to detect cyber-attacks over existing solutions.

AB - Hybrid Anomaly Detection Model (HADM) is a security platform to detect and prevent cyber-attacks on communication networks. The platform uses a combination of linear and learning algorithms combined with protocol analyzer. The linear algorithms filter and extract distinctive attributes and features of the cyber-attacks while the learning algorithms use these attributes and features to identify new types of cyber-attacks. The protocol analyzer in this platform classifies and filters vulnerable protocols to avoid unnecessary computation load. The use of linear algorithms in conjunction with learning algorithms allows the HADM to achieve improved efficiency in terms of accuracy and computation time in order to detect cyber-attacks over existing solutions.

KW - Anomaly detection

KW - Cloud computing

KW - Internet of things

KW - Machine learning

KW - Security

UR - http://www.scopus.com/inward/record.url?scp=85059695698&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-02931-9_9

DO - 10.1007/978-3-030-02931-9_9

M3 - Conference article in proceedings

AN - SCOPUS:85059695698

SN - 978-3-030-02930-2

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 107

EP - 118

BT - Wired/Wireless Internet Communications - 16th IFIP WG 6.2 International Conference, WWIC 2018, Proceedings

A2 - Chowdhury, Kaushik Roy

A2 - Di Felice, Marco

A2 - Sheng, Bo

A2 - Matta, Ibrahim

PB - Springer

T2 - International Conference on Wired/Wireless Internet Communications

Y2 - 18 June 2018 through 20 June 2018

ER -

Monshizadeh M, Khatri V, Atli B, Kantola R. An intelligent defense and filtration platform for network traffic. julkaisussa Chowdhury KR, Di Felice M, Sheng B, Matta I, toimittajat, Wired/Wireless Internet Communications - 16th IFIP WG 6.2 International Conference, WWIC 2018, Proceedings. Springer. 2018. s. 107-118. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-02931-9_9

An intelligent defense and filtration platform for network traffic

Abstrakti

Julkaisusarja

Conference

Pääsy asiakirjaan

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Sormenjälki

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