Agile services and analysis framework for autonomous and autonomic critical infrastructure View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2021-08-13

AUTHORS

Joe Maurio, Paul Wood, Sebastian Zanlongo, Josh Silbermann, Tamim Sookoor, Alberto Lorenzo, Randy Sleight, James Rogers, Dan Muller, Noah Armiger, Christopher Rouff, Lanier Watkins

ABSTRACT

Many cyber physical systems have little or no cybersecurity mechanisms due to their limited computing capabilities or their history of running on isolated networks. As these systems have become interconnected and connected to corporate networks, they have become more vulnerable to cyberattacks. Providing cyber physical systems with autonomic properties will allow them to become more self-aware and react in near real time to attacks and failures. Testing these systems for their susceptibility to intelligent attacks is also needed to provide assurance of their resilience. This paper describes two approaches to providing assurances to cyber physical systems. The first approach retrofits industrial control systems with autonomic properties that will allow them to automatically detect and recover from cyberattacks and other failures through the use of microservices that reconfigure the systems dynamically during attacks or failures. The second approach uses intelligent agents in a modeling and simulation framework to test the resiliency of autonomous unmanned aerial systems. Agents are orchestrated using a range of algorithms and subjected to stressful environments to measure the efficiency and safety of their operations in a simulate multi-UAS air-traffic control problem. More... »

PAGES

1-12

References to SciGraph publications

  • 2005-03-11. Autonomic computing in INNOVATIONS IN SYSTEMS AND SOFTWARE ENGINEERING
  • 2016. Principles and Practice of Constraint Programming, 22nd International Conference, CP 2016, Toulouse, France, September 5-9, 2016, Proceedings in NONE
  • 2005. Neural Fitted Q Iteration – First Experiences with a Data Efficient Neural Reinforcement Learning Method in MACHINE LEARNING: ECML 2005
  • 2017-05-04. A Malware-Tolerant, Self-Healing Industrial Control System Framework in ICT SYSTEMS SECURITY AND PRIVACY PROTECTION
  • 2005. Autonomic Agents for Survivable Security Systems in EMBEDDED AND UBIQUITOUS COMPUTING – EUC 2005 WORKSHOPS
  • 2007-01-01. Lessons Learned from the Maroochy Water Breach in CRITICAL INFRASTRUCTURE PROTECTION
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11334-021-00411-9

    DOI

    http://dx.doi.org/10.1007/s11334-021-00411-9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1140407286


    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/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "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/2008/0806", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information Systems", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Maurio", 
            "givenName": "Joe", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wood", 
            "givenName": "Paul", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zanlongo", 
            "givenName": "Sebastian", 
            "id": "sg:person.016117237520.52", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016117237520.52"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Silbermann", 
            "givenName": "Josh", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sookoor", 
            "givenName": "Tamim", 
            "id": "sg:person.010026247473.05", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010026247473.05"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lorenzo", 
            "givenName": "Alberto", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sleight", 
            "givenName": "Randy", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Rogers", 
            "givenName": "James", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Muller", 
            "givenName": "Dan", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Armiger", 
            "givenName": "Noah", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Rouff", 
            "givenName": "Christopher", 
            "id": "sg:person.016560052530.14", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016560052530.14"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.474430.0", 
              "name": [
                "Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Watkins", 
            "givenName": "Lanier", 
            "id": "sg:person.010445532352.48", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010445532352.48"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s11334-005-0001-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027715336", 
              "https://doi.org/10.1007/s11334-005-0001-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-0-387-75462-8_6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040189262", 
              "https://doi.org/10.1007/978-0-387-75462-8_6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-58469-0_4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1086842310", 
              "https://doi.org/10.1007/978-3-319-58469-0_4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-44953-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025568103", 
              "https://doi.org/10.1007/978-3-319-44953-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/11564096_32", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052945304", 
              "https://doi.org/10.1007/11564096_32"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/11596042_125", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047793020", 
              "https://doi.org/10.1007/11596042_125"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2021-08-13", 
        "datePublishedReg": "2021-08-13", 
        "description": "Many cyber physical systems have little or no cybersecurity mechanisms due to their limited computing capabilities or their history of running on isolated networks. As these systems have become interconnected and connected to corporate networks, they have become more vulnerable to cyberattacks. Providing cyber physical systems with autonomic properties will allow them to become more self-aware and react in near real time to attacks and failures. Testing these systems for their susceptibility to intelligent attacks is also needed to provide assurance of their resilience. This paper describes two approaches to providing assurances to cyber physical systems. The first approach retrofits industrial control systems with autonomic properties that will allow them to automatically detect and recover from cyberattacks and other failures through the use of microservices that reconfigure the systems dynamically during attacks or failures. The second approach uses intelligent agents in a modeling and simulation framework to test the resiliency of autonomous unmanned aerial systems. Agents are orchestrated using a range of algorithms and subjected to stressful environments to measure the efficiency and safety of their operations in a simulate multi-UAS air-traffic control problem.", 
        "genre": "article", 
        "id": "sg:pub.10.1007/s11334-021-00411-9", 
        "inLanguage": "en", 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1044675", 
            "issn": [
              "1614-5046", 
              "1614-5054"
            ], 
            "name": "Innovations in Systems and Software Engineering", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }
        ], 
        "keywords": [
          "cyber-physical systems", 
          "autonomic properties", 
          "autonomous unmanned aerial systems", 
          "use of microservices", 
          "limited computing capabilities", 
          "physical systems", 
          "air traffic control problem", 
          "industrial control systems", 
          "range of algorithms", 
          "unmanned aerial systems", 
          "intelligent agents", 
          "agile services", 
          "cybersecurity mechanisms", 
          "computing capabilities", 
          "intelligent attacks", 
          "corporate networks", 
          "critical infrastructure", 
          "simulation framework", 
          "aerial systems", 
          "real time", 
          "isolated network", 
          "cyberattacks", 
          "analysis framework", 
          "control system", 
          "attacks", 
          "network", 
          "first approach", 
          "second approach", 
          "control problem", 
          "microservices", 
          "framework", 
          "assurance", 
          "system", 
          "algorithm", 
          "infrastructure", 
          "services", 
          "capability", 
          "resiliency", 
          "environment", 
          "modeling", 
          "operation", 
          "efficiency", 
          "resilience", 
          "time", 
          "use", 
          "agents", 
          "properties", 
          "safety", 
          "failure", 
          "approach", 
          "mechanism", 
          "range", 
          "problem", 
          "stressful environments", 
          "history", 
          "susceptibility", 
          "paper"
        ], 
        "name": "Agile services and analysis framework for autonomous and autonomic critical infrastructure", 
        "pagination": "1-12", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1140407286"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s11334-021-00411-9"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s11334-021-00411-9", 
          "https://app.dimensions.ai/details/publication/pub.1140407286"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-05-20T07:39", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20220519/entities/gbq_results/article/article_897.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1007/s11334-021-00411-9"
      }
    ]
     

    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/s11334-021-00411-9'

    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/s11334-021-00411-9'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11334-021-00411-9'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11334-021-00411-9'


     

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

    206 TRIPLES      22 PREDICATES      87 URIs      72 LITERALS      4 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s11334-021-00411-9 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 anzsrc-for:0806
    4 schema:author N2170adfad8a744ae9ee671d912464718
    5 schema:citation sg:pub.10.1007/11564096_32
    6 sg:pub.10.1007/11596042_125
    7 sg:pub.10.1007/978-0-387-75462-8_6
    8 sg:pub.10.1007/978-3-319-44953-1
    9 sg:pub.10.1007/978-3-319-58469-0_4
    10 sg:pub.10.1007/s11334-005-0001-5
    11 schema:datePublished 2021-08-13
    12 schema:datePublishedReg 2021-08-13
    13 schema:description Many cyber physical systems have little or no cybersecurity mechanisms due to their limited computing capabilities or their history of running on isolated networks. As these systems have become interconnected and connected to corporate networks, they have become more vulnerable to cyberattacks. Providing cyber physical systems with autonomic properties will allow them to become more self-aware and react in near real time to attacks and failures. Testing these systems for their susceptibility to intelligent attacks is also needed to provide assurance of their resilience. This paper describes two approaches to providing assurances to cyber physical systems. The first approach retrofits industrial control systems with autonomic properties that will allow them to automatically detect and recover from cyberattacks and other failures through the use of microservices that reconfigure the systems dynamically during attacks or failures. The second approach uses intelligent agents in a modeling and simulation framework to test the resiliency of autonomous unmanned aerial systems. Agents are orchestrated using a range of algorithms and subjected to stressful environments to measure the efficiency and safety of their operations in a simulate multi-UAS air-traffic control problem.
    14 schema:genre article
    15 schema:inLanguage en
    16 schema:isAccessibleForFree false
    17 schema:isPartOf sg:journal.1044675
    18 schema:keywords aerial systems
    19 agents
    20 agile services
    21 air traffic control problem
    22 algorithm
    23 analysis framework
    24 approach
    25 assurance
    26 attacks
    27 autonomic properties
    28 autonomous unmanned aerial systems
    29 capability
    30 computing capabilities
    31 control problem
    32 control system
    33 corporate networks
    34 critical infrastructure
    35 cyber-physical systems
    36 cyberattacks
    37 cybersecurity mechanisms
    38 efficiency
    39 environment
    40 failure
    41 first approach
    42 framework
    43 history
    44 industrial control systems
    45 infrastructure
    46 intelligent agents
    47 intelligent attacks
    48 isolated network
    49 limited computing capabilities
    50 mechanism
    51 microservices
    52 modeling
    53 network
    54 operation
    55 paper
    56 physical systems
    57 problem
    58 properties
    59 range
    60 range of algorithms
    61 real time
    62 resilience
    63 resiliency
    64 safety
    65 second approach
    66 services
    67 simulation framework
    68 stressful environments
    69 susceptibility
    70 system
    71 time
    72 unmanned aerial systems
    73 use
    74 use of microservices
    75 schema:name Agile services and analysis framework for autonomous and autonomic critical infrastructure
    76 schema:pagination 1-12
    77 schema:productId N075fa1354bc84d029e2476238f22d250
    78 N6005b39651194064a4aa194aa068d108
    79 schema:sameAs https://app.dimensions.ai/details/publication/pub.1140407286
    80 https://doi.org/10.1007/s11334-021-00411-9
    81 schema:sdDatePublished 2022-05-20T07:39
    82 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    83 schema:sdPublisher Na0baca9fb6074d9298931b62b20defab
    84 schema:url https://doi.org/10.1007/s11334-021-00411-9
    85 sgo:license sg:explorer/license/
    86 sgo:sdDataset articles
    87 rdf:type schema:ScholarlyArticle
    88 N075fa1354bc84d029e2476238f22d250 schema:name dimensions_id
    89 schema:value pub.1140407286
    90 rdf:type schema:PropertyValue
    91 N13761921bcda48d19f9cdb2f7261b513 schema:affiliation grid-institutes:grid.474430.0
    92 schema:familyName Armiger
    93 schema:givenName Noah
    94 rdf:type schema:Person
    95 N2170adfad8a744ae9ee671d912464718 rdf:first N291f6c2414b04bf1b431b90b9cf5c7ce
    96 rdf:rest N8f719898f8fb4635b06948ff1f245779
    97 N291f6c2414b04bf1b431b90b9cf5c7ce schema:affiliation grid-institutes:grid.474430.0
    98 schema:familyName Maurio
    99 schema:givenName Joe
    100 rdf:type schema:Person
    101 N3c4ae0e3284f45b8982dc93680a4c605 schema:affiliation grid-institutes:grid.474430.0
    102 schema:familyName Muller
    103 schema:givenName Dan
    104 rdf:type schema:Person
    105 N6005b39651194064a4aa194aa068d108 schema:name doi
    106 schema:value 10.1007/s11334-021-00411-9
    107 rdf:type schema:PropertyValue
    108 N7e192005d6f840ab84b81bb804992f5f rdf:first sg:person.016560052530.14
    109 rdf:rest Ne1baf9552ff749278649d49b35bd6d88
    110 N8f719898f8fb4635b06948ff1f245779 rdf:first Nb73d9b77aa4a437abec3dc8b737c8489
    111 rdf:rest Nea193ed0160a4d3a8506f035357ed23a
    112 Na0baca9fb6074d9298931b62b20defab schema:name Springer Nature - SN SciGraph project
    113 rdf:type schema:Organization
    114 Na5c34f318d5440608acb318be6f6f806 rdf:first Na6dc219741b24dcd990d4522bb8a7223
    115 rdf:rest Nde2c43009d574e3791b49993e8d1c5bb
    116 Na6dc219741b24dcd990d4522bb8a7223 schema:affiliation grid-institutes:grid.474430.0
    117 schema:familyName Silbermann
    118 schema:givenName Josh
    119 rdf:type schema:Person
    120 Nb49bd9ed1b354694bfce6592a6eb7155 rdf:first Nd5e50336f0ec469e807f1e0639d3bd10
    121 rdf:rest Ndacc3f9b65dc45978e87dd30f9a2021c
    122 Nb73d9b77aa4a437abec3dc8b737c8489 schema:affiliation grid-institutes:grid.474430.0
    123 schema:familyName Wood
    124 schema:givenName Paul
    125 rdf:type schema:Person
    126 Ncab3c039d8c043a694a5cab18b9182b4 schema:affiliation grid-institutes:grid.474430.0
    127 schema:familyName Sleight
    128 schema:givenName Randy
    129 rdf:type schema:Person
    130 Ncc24d761f0a14c4dbe8d33faf9f3da5e rdf:first N13761921bcda48d19f9cdb2f7261b513
    131 rdf:rest N7e192005d6f840ab84b81bb804992f5f
    132 Nd5e50336f0ec469e807f1e0639d3bd10 schema:affiliation grid-institutes:grid.474430.0
    133 schema:familyName Lorenzo
    134 schema:givenName Alberto
    135 rdf:type schema:Person
    136 Ndacc3f9b65dc45978e87dd30f9a2021c rdf:first Ncab3c039d8c043a694a5cab18b9182b4
    137 rdf:rest Nedd6836c3ded417abdd37fe826fce921
    138 Nde2c43009d574e3791b49993e8d1c5bb rdf:first sg:person.010026247473.05
    139 rdf:rest Nb49bd9ed1b354694bfce6592a6eb7155
    140 Ne1baf9552ff749278649d49b35bd6d88 rdf:first sg:person.010445532352.48
    141 rdf:rest rdf:nil
    142 Ne2b4c2dc66fb482d8f97726f7ba53b94 schema:affiliation grid-institutes:grid.474430.0
    143 schema:familyName Rogers
    144 schema:givenName James
    145 rdf:type schema:Person
    146 Nea193ed0160a4d3a8506f035357ed23a rdf:first sg:person.016117237520.52
    147 rdf:rest Na5c34f318d5440608acb318be6f6f806
    148 Nedd6836c3ded417abdd37fe826fce921 rdf:first Ne2b4c2dc66fb482d8f97726f7ba53b94
    149 rdf:rest Nf8ba6a714a0b47cf80938cf09056dd74
    150 Nf8ba6a714a0b47cf80938cf09056dd74 rdf:first N3c4ae0e3284f45b8982dc93680a4c605
    151 rdf:rest Ncc24d761f0a14c4dbe8d33faf9f3da5e
    152 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    153 schema:name Information and Computing Sciences
    154 rdf:type schema:DefinedTerm
    155 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    156 schema:name Artificial Intelligence and Image Processing
    157 rdf:type schema:DefinedTerm
    158 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
    159 schema:name Information Systems
    160 rdf:type schema:DefinedTerm
    161 sg:journal.1044675 schema:issn 1614-5046
    162 1614-5054
    163 schema:name Innovations in Systems and Software Engineering
    164 schema:publisher Springer Nature
    165 rdf:type schema:Periodical
    166 sg:person.010026247473.05 schema:affiliation grid-institutes:grid.474430.0
    167 schema:familyName Sookoor
    168 schema:givenName Tamim
    169 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010026247473.05
    170 rdf:type schema:Person
    171 sg:person.010445532352.48 schema:affiliation grid-institutes:grid.474430.0
    172 schema:familyName Watkins
    173 schema:givenName Lanier
    174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010445532352.48
    175 rdf:type schema:Person
    176 sg:person.016117237520.52 schema:affiliation grid-institutes:grid.474430.0
    177 schema:familyName Zanlongo
    178 schema:givenName Sebastian
    179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016117237520.52
    180 rdf:type schema:Person
    181 sg:person.016560052530.14 schema:affiliation grid-institutes:grid.474430.0
    182 schema:familyName Rouff
    183 schema:givenName Christopher
    184 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016560052530.14
    185 rdf:type schema:Person
    186 sg:pub.10.1007/11564096_32 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052945304
    187 https://doi.org/10.1007/11564096_32
    188 rdf:type schema:CreativeWork
    189 sg:pub.10.1007/11596042_125 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047793020
    190 https://doi.org/10.1007/11596042_125
    191 rdf:type schema:CreativeWork
    192 sg:pub.10.1007/978-0-387-75462-8_6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040189262
    193 https://doi.org/10.1007/978-0-387-75462-8_6
    194 rdf:type schema:CreativeWork
    195 sg:pub.10.1007/978-3-319-44953-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025568103
    196 https://doi.org/10.1007/978-3-319-44953-1
    197 rdf:type schema:CreativeWork
    198 sg:pub.10.1007/978-3-319-58469-0_4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086842310
    199 https://doi.org/10.1007/978-3-319-58469-0_4
    200 rdf:type schema:CreativeWork
    201 sg:pub.10.1007/s11334-005-0001-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027715336
    202 https://doi.org/10.1007/s11334-005-0001-5
    203 rdf:type schema:CreativeWork
    204 grid-institutes:grid.474430.0 schema:alternateName Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA
    205 schema:name Johns Hopkins University Applied Physics Laboratory, Laurel MD, USA
    206 rdf:type schema:Organization
     




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


    ...