Detecting and Confining Sybil Attack in Wireless Sensor Networks Based on Reputation Systems Coupled with Self-organizing Maps View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2010

AUTHORS

Zorana Banković , David Fraga , José M. Moya , Juan Carlos Vallejo , Álvaro Araujo , Pedro Malagón , Juan-Mariano de Goyeneche , Daniel Villanueva , Elena Romero , Javier Blesa

ABSTRACT

The Sybil attack is one of the most aggressive and evasive attacks in sensor networks that can affect on many aspects of network functioning. Thus, its efficient detection is of highest importance. In order to resolve this issue, in this work we propose to couple reputation systems with agents based on self-organizing map algorithm trained for detecting outliers in data. The response of the system consists in assigning low reputation values to the compromised node rendering them isolated from the rest of the network. The main improvement of this work consists in the way of calculating reputation, which is more flexible and discriminative in distinguishing attacks from normal behavior. Self-organizing map algorithm deploys feature space based on sequences of sensor outputs. Our solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability and low consumption. The testing results demonstrate its high ability in detecting and confining Sybil attack. More... »

PAGES

311-318

Book

TITLE

Artificial Intelligence Applications and Innovations

ISBN

978-3-642-16238-1
978-3-642-16239-8

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-16239-8_41

DOI

http://dx.doi.org/10.1007/978-3-642-16239-8_41

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1040290520


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Technical University of Madrid", 
          "id": "https://www.grid.ac/institutes/grid.5690.a", 
          "name": [
            "ETSI Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Av. Complutense 30, 28040, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bankovi\u0107", 
        "givenName": "Zorana", 
        "id": "sg:person.013534273534.80", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013534273534.80"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Technical University of Madrid", 
          "id": "https://www.grid.ac/institutes/grid.5690.a", 
          "name": [
            "ETSI Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Av. Complutense 30, 28040, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fraga", 
        "givenName": "David", 
        "id": "sg:person.01263647634.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01263647634.13"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Technical University of Madrid", 
          "id": "https://www.grid.ac/institutes/grid.5690.a", 
          "name": [
            "ETSI Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Av. Complutense 30, 28040, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Moya", 
        "givenName": "Jos\u00e9 M.", 
        "id": "sg:person.07662217004.56", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07662217004.56"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Technical University of Madrid", 
          "id": "https://www.grid.ac/institutes/grid.5690.a", 
          "name": [
            "ETSI Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Av. Complutense 30, 28040, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Vallejo", 
        "givenName": "Juan Carlos", 
        "id": "sg:person.0606356734.19", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0606356734.19"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Technical University of Madrid", 
          "id": "https://www.grid.ac/institutes/grid.5690.a", 
          "name": [
            "ETSI Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Av. Complutense 30, 28040, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Araujo", 
        "givenName": "\u00c1lvaro", 
        "id": "sg:person.010120552111.77", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010120552111.77"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Technical University of Madrid", 
          "id": "https://www.grid.ac/institutes/grid.5690.a", 
          "name": [
            "ETSI Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Av. Complutense 30, 28040, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Malag\u00f3n", 
        "givenName": "Pedro", 
        "id": "sg:person.012400766577.71", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012400766577.71"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Technical University of Madrid", 
          "id": "https://www.grid.ac/institutes/grid.5690.a", 
          "name": [
            "ETSI Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Av. Complutense 30, 28040, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "de Goyeneche", 
        "givenName": "Juan-Mariano", 
        "id": "sg:person.01132363131.83", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01132363131.83"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Technical University of Madrid", 
          "id": "https://www.grid.ac/institutes/grid.5690.a", 
          "name": [
            "ETSI Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Av. Complutense 30, 28040, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Villanueva", 
        "givenName": "Daniel", 
        "id": "sg:person.013663472462.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013663472462.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Technical University of Madrid", 
          "id": "https://www.grid.ac/institutes/grid.5690.a", 
          "name": [
            "ETSI Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Av. Complutense 30, 28040, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Romero", 
        "givenName": "Elena", 
        "id": "sg:person.014247455257.71", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014247455257.71"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Technical University of Madrid", 
          "id": "https://www.grid.ac/institutes/grid.5690.a", 
          "name": [
            "ETSI Telecomunicaci\u00f3n, Universidad Polit\u00e9cnica de Madrid, Av. Complutense 30, 28040, Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Blesa", 
        "givenName": "Javier", 
        "id": "sg:person.013377402130.57", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013377402130.57"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/s0925-2312(97)00068-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005216996"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/s91109380", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007608279"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/984622.984660", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037615875"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2010", 
    "datePublishedReg": "2010-01-01", 
    "description": "The Sybil attack is one of the most aggressive and evasive attacks in sensor networks that can affect on many aspects of network functioning. Thus, its efficient detection is of highest importance. In order to resolve this issue, in this work we propose to couple reputation systems with agents based on self-organizing map algorithm trained for detecting outliers in data. The response of the system consists in assigning low reputation values to the compromised node rendering them isolated from the rest of the network. The main improvement of this work consists in the way of calculating reputation, which is more flexible and discriminative in distinguishing attacks from normal behavior. Self-organizing map algorithm deploys feature space based on sequences of sensor outputs. Our solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability and low consumption. The testing results demonstrate its high ability in detecting and confining Sybil attack.", 
    "editor": [
      {
        "familyName": "Papadopoulos", 
        "givenName": "Harris", 
        "type": "Person"
      }, 
      {
        "familyName": "Andreou", 
        "givenName": "Andreas S.", 
        "type": "Person"
      }, 
      {
        "familyName": "Bramer", 
        "givenName": "Max", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-642-16239-8_41", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": {
      "isbn": [
        "978-3-642-16238-1", 
        "978-3-642-16239-8"
      ], 
      "name": "Artificial Intelligence Applications and Innovations", 
      "type": "Book"
    }, 
    "name": "Detecting and Confining Sybil Attack in Wireless Sensor Networks Based on Reputation Systems Coupled with Self-organizing Maps", 
    "pagination": "311-318", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1040290520"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-16239-8_41"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "bfed527052b93cad9710afb93b2b7c2e7d944812ddbd1651ac55cd5ebf3aff35"
        ]
      }
    ], 
    "publisher": {
      "location": "Berlin, Heidelberg", 
      "name": "Springer Berlin Heidelberg", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-16239-8_41", 
      "https://app.dimensions.ai/details/publication/pub.1040290520"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-16T08:26", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000363_0000000363/records_70058_00000001.jsonl", 
    "type": "Chapter", 
    "url": "https://link.springer.com/10.1007%2F978-3-642-16239-8_41"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-16239-8_41'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-16239-8_41'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-16239-8_41'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-16239-8_41'


 

This table displays all metadata directly associated to this object as RDF triples.

147 TRIPLES      23 PREDICATES      30 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-642-16239-8_41 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author Nde38719442614f51aa79cbe70e220ea5
4 schema:citation https://doi.org/10.1016/s0925-2312(97)00068-4
5 https://doi.org/10.1145/984622.984660
6 https://doi.org/10.3390/s91109380
7 schema:datePublished 2010
8 schema:datePublishedReg 2010-01-01
9 schema:description The Sybil attack is one of the most aggressive and evasive attacks in sensor networks that can affect on many aspects of network functioning. Thus, its efficient detection is of highest importance. In order to resolve this issue, in this work we propose to couple reputation systems with agents based on self-organizing map algorithm trained for detecting outliers in data. The response of the system consists in assigning low reputation values to the compromised node rendering them isolated from the rest of the network. The main improvement of this work consists in the way of calculating reputation, which is more flexible and discriminative in distinguishing attacks from normal behavior. Self-organizing map algorithm deploys feature space based on sequences of sensor outputs. Our solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability and low consumption. The testing results demonstrate its high ability in detecting and confining Sybil attack.
10 schema:editor Ne566e9015ad2498f9ade08e0ee63399c
11 schema:genre chapter
12 schema:inLanguage en
13 schema:isAccessibleForFree true
14 schema:isPartOf N8f347cd54a6846ee83fbea8998b2ce33
15 schema:name Detecting and Confining Sybil Attack in Wireless Sensor Networks Based on Reputation Systems Coupled with Self-organizing Maps
16 schema:pagination 311-318
17 schema:productId N1e2e49c6a9664655b5c3a17ae7e03727
18 N6bf9ce368b5c4745904f42cb5622c14e
19 Ne427e976081e4d86b4e7586cd9551b1b
20 schema:publisher N6bde249d383245dbad291154d726e190
21 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040290520
22 https://doi.org/10.1007/978-3-642-16239-8_41
23 schema:sdDatePublished 2019-04-16T08:26
24 schema:sdLicense https://scigraph.springernature.com/explorer/license/
25 schema:sdPublisher N61875c03cad8482992bc19b30f67e2dc
26 schema:url https://link.springer.com/10.1007%2F978-3-642-16239-8_41
27 sgo:license sg:explorer/license/
28 sgo:sdDataset chapters
29 rdf:type schema:Chapter
30 N1807799595b44fdcacf4469c4b666a02 schema:familyName Papadopoulos
31 schema:givenName Harris
32 rdf:type schema:Person
33 N1a090dcb04f54ce2beebd59168282c4c rdf:first sg:person.014247455257.71
34 rdf:rest Nee28d7a853694895b046c86fde3caa0c
35 N1e2e49c6a9664655b5c3a17ae7e03727 schema:name readcube_id
36 schema:value bfed527052b93cad9710afb93b2b7c2e7d944812ddbd1651ac55cd5ebf3aff35
37 rdf:type schema:PropertyValue
38 N281f03c8b8e8473fbc40dfc8e1096189 rdf:first sg:person.07662217004.56
39 rdf:rest N3c2e13cb5b2041a5a184bdfee9e60763
40 N31381f20352b43798bf15c1d2b3fe162 rdf:first N6f2cca972d09402bad56b8f9bee84941
41 rdf:rest N703ab73c0c7742cab87a15b6f1597d00
42 N38c42098b4314c87bead432cca6bd4f3 rdf:first sg:person.01263647634.13
43 rdf:rest N281f03c8b8e8473fbc40dfc8e1096189
44 N3c2e13cb5b2041a5a184bdfee9e60763 rdf:first sg:person.0606356734.19
45 rdf:rest N80526ff3032548f988f45117f2d9015d
46 N5e78ece9d4f84758967d5afa43b0d0a5 rdf:first sg:person.012400766577.71
47 rdf:rest N7021fc5546e7469ea0de5b4af1c08c2f
48 N61875c03cad8482992bc19b30f67e2dc schema:name Springer Nature - SN SciGraph project
49 rdf:type schema:Organization
50 N6bde249d383245dbad291154d726e190 schema:location Berlin, Heidelberg
51 schema:name Springer Berlin Heidelberg
52 rdf:type schema:Organisation
53 N6bf9ce368b5c4745904f42cb5622c14e schema:name dimensions_id
54 schema:value pub.1040290520
55 rdf:type schema:PropertyValue
56 N6f2cca972d09402bad56b8f9bee84941 schema:familyName Andreou
57 schema:givenName Andreas S.
58 rdf:type schema:Person
59 N7021fc5546e7469ea0de5b4af1c08c2f rdf:first sg:person.01132363131.83
60 rdf:rest Ne523f69a7fcb418b8ce236b600d2a265
61 N703ab73c0c7742cab87a15b6f1597d00 rdf:first Nada869b5be0a4f139dba1d6ad5c95dee
62 rdf:rest rdf:nil
63 N80526ff3032548f988f45117f2d9015d rdf:first sg:person.010120552111.77
64 rdf:rest N5e78ece9d4f84758967d5afa43b0d0a5
65 N8f347cd54a6846ee83fbea8998b2ce33 schema:isbn 978-3-642-16238-1
66 978-3-642-16239-8
67 schema:name Artificial Intelligence Applications and Innovations
68 rdf:type schema:Book
69 Nada869b5be0a4f139dba1d6ad5c95dee schema:familyName Bramer
70 schema:givenName Max
71 rdf:type schema:Person
72 Nde38719442614f51aa79cbe70e220ea5 rdf:first sg:person.013534273534.80
73 rdf:rest N38c42098b4314c87bead432cca6bd4f3
74 Ne427e976081e4d86b4e7586cd9551b1b schema:name doi
75 schema:value 10.1007/978-3-642-16239-8_41
76 rdf:type schema:PropertyValue
77 Ne523f69a7fcb418b8ce236b600d2a265 rdf:first sg:person.013663472462.48
78 rdf:rest N1a090dcb04f54ce2beebd59168282c4c
79 Ne566e9015ad2498f9ade08e0ee63399c rdf:first N1807799595b44fdcacf4469c4b666a02
80 rdf:rest N31381f20352b43798bf15c1d2b3fe162
81 Nee28d7a853694895b046c86fde3caa0c rdf:first sg:person.013377402130.57
82 rdf:rest rdf:nil
83 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
84 schema:name Information and Computing Sciences
85 rdf:type schema:DefinedTerm
86 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
87 schema:name Artificial Intelligence and Image Processing
88 rdf:type schema:DefinedTerm
89 sg:person.010120552111.77 schema:affiliation https://www.grid.ac/institutes/grid.5690.a
90 schema:familyName Araujo
91 schema:givenName Álvaro
92 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010120552111.77
93 rdf:type schema:Person
94 sg:person.01132363131.83 schema:affiliation https://www.grid.ac/institutes/grid.5690.a
95 schema:familyName de Goyeneche
96 schema:givenName Juan-Mariano
97 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01132363131.83
98 rdf:type schema:Person
99 sg:person.012400766577.71 schema:affiliation https://www.grid.ac/institutes/grid.5690.a
100 schema:familyName Malagón
101 schema:givenName Pedro
102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012400766577.71
103 rdf:type schema:Person
104 sg:person.01263647634.13 schema:affiliation https://www.grid.ac/institutes/grid.5690.a
105 schema:familyName Fraga
106 schema:givenName David
107 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01263647634.13
108 rdf:type schema:Person
109 sg:person.013377402130.57 schema:affiliation https://www.grid.ac/institutes/grid.5690.a
110 schema:familyName Blesa
111 schema:givenName Javier
112 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013377402130.57
113 rdf:type schema:Person
114 sg:person.013534273534.80 schema:affiliation https://www.grid.ac/institutes/grid.5690.a
115 schema:familyName Banković
116 schema:givenName Zorana
117 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013534273534.80
118 rdf:type schema:Person
119 sg:person.013663472462.48 schema:affiliation https://www.grid.ac/institutes/grid.5690.a
120 schema:familyName Villanueva
121 schema:givenName Daniel
122 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013663472462.48
123 rdf:type schema:Person
124 sg:person.014247455257.71 schema:affiliation https://www.grid.ac/institutes/grid.5690.a
125 schema:familyName Romero
126 schema:givenName Elena
127 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014247455257.71
128 rdf:type schema:Person
129 sg:person.0606356734.19 schema:affiliation https://www.grid.ac/institutes/grid.5690.a
130 schema:familyName Vallejo
131 schema:givenName Juan Carlos
132 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0606356734.19
133 rdf:type schema:Person
134 sg:person.07662217004.56 schema:affiliation https://www.grid.ac/institutes/grid.5690.a
135 schema:familyName Moya
136 schema:givenName José M.
137 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07662217004.56
138 rdf:type schema:Person
139 https://doi.org/10.1016/s0925-2312(97)00068-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005216996
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1145/984622.984660 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037615875
142 rdf:type schema:CreativeWork
143 https://doi.org/10.3390/s91109380 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007608279
144 rdf:type schema:CreativeWork
145 https://www.grid.ac/institutes/grid.5690.a schema:alternateName Technical University of Madrid
146 schema:name ETSI Telecomunicación, Universidad Politécnica de Madrid, Av. Complutense 30, 28040, Madrid, Spain
147 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...