Towards Deep-Learning-Driven Intrusion Detection for the Internet of Things
Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end us...
Gespeichert in:
| Veröffentlicht in: | Sensors (Basel, Switzerland) Jg. 19; H. 9; S. 1977 |
|---|---|
| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Switzerland
MDPI AG
27.04.2019
MDPI |
| Schlagworte: | |
| ISSN: | 1424-8220, 1424-8220 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively. |
|---|---|
| AbstractList | Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively. Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively.Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively. |
| Author | Chawla, Shiven Thamilarasu, Geethapriya |
| AuthorAffiliation | School of STEM, University of Washington Bothell, Bothell, WA 98011, USA; chawls@uw.edu |
| AuthorAffiliation_xml | – name: School of STEM, University of Washington Bothell, Bothell, WA 98011, USA; chawls@uw.edu |
| Author_xml | – sequence: 1 givenname: Geethapriya surname: Thamilarasu fullname: Thamilarasu, Geethapriya – sequence: 2 givenname: Shiven orcidid: 0000-0002-0583-6494 surname: Chawla fullname: Chawla, Shiven |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31035611$$D View this record in MEDLINE/PubMed |
| BookMark | eNplkslu2zAQhokiQbbm0BcoBPTSHtRwF3kpUCRdjBroxT0TFDWyacikS0op-val6iTIcuKA88-Hf5ZzdBRiAITeEPyRMY2vMtFYE900r9AZ4ZTXilJ89Cg-Rec5bzGmjDF1gk4ZwUxIQs7Qj1X8Y1OXqxuAfb0Em4IP6_om-VsI1SKMaco-hpIewY1z1MdUjRuYc5ACjFXsq9WmFOXX6Li3Q4bLu_cC_fr6ZXX9vV7-_La4_rysnWBirLlgLcW9cBykdMQ53QjugLJW9qRrtdCdUm2HaQe9pdQprLgTnHVtsY9bzS7Q4sDtot2affI7m_6aaL35_xHT2tg0ejeAwQqLMhvstO45BWmbVuHCt1Ix3TNbWJ8OrP3U7qBzUDq2wxPo00zwG7OOt0YKVnzPZt7fAVL8PUEezc5nB8NgA8QpG0pJw6VWqinSd8-k2zilUEZlKMNEEi4bUVRvHzt6sHK_syK4Oghcijkn6I3zo513Uwz6wRBs5qswD1dRKj48q7iHvtT-A91atTo |
| CitedBy_id | crossref_primary_10_3390_jsan11030032 crossref_primary_10_1007_s10922_021_09589_6 crossref_primary_10_1007_s10669_022_09859_x crossref_primary_10_3390_sym14091916 crossref_primary_10_26599_TST_2023_9010033 crossref_primary_10_1016_j_jisa_2019_102419 crossref_primary_10_1109_ACCESS_2021_3094024 crossref_primary_10_3390_s21196346 crossref_primary_10_3390_s22218280 crossref_primary_10_1109_TCE_2024_3350231 crossref_primary_10_32604_cmc_2023_042726 crossref_primary_10_1016_j_jpdc_2023_05_001 crossref_primary_10_3390_app9132763 crossref_primary_10_1109_ACCESS_2021_3056149 crossref_primary_10_3390_s22207896 crossref_primary_10_1016_j_adhoc_2023_103120 crossref_primary_10_1093_comjnl_bxab136 crossref_primary_10_1007_s11227_022_04753_4 crossref_primary_10_3390_electronics10111241 crossref_primary_10_1155_2022_2693948 crossref_primary_10_3390_s22155621 crossref_primary_10_3390_electronics9030530 crossref_primary_10_1007_s11235_022_00927_w crossref_primary_10_3390_s21041113 crossref_primary_10_1109_ACCESS_2021_3074887 crossref_primary_10_1109_JIOT_2021_3051414 crossref_primary_10_3390_en14196384 crossref_primary_10_32604_cmc_2021_016938 crossref_primary_10_3390_info12040154 crossref_primary_10_1007_s10922_021_09621_9 crossref_primary_10_1186_s13638_024_02348_6 crossref_primary_10_1155_2023_7690322 crossref_primary_10_3390_jsan12020021 crossref_primary_10_1002_cpe_6152 crossref_primary_10_1080_19393555_2023_2218852 crossref_primary_10_1109_ACCESS_2022_3215532 crossref_primary_10_1007_s41315_022_00234_2 crossref_primary_10_1109_ACCESS_2023_3325929 crossref_primary_10_1016_j_measen_2022_100613 crossref_primary_10_3390_app11073022 crossref_primary_10_1109_TITS_2021_3110725 crossref_primary_10_1007_s11227_020_03513_6 crossref_primary_10_1080_19393555_2025_2496327 crossref_primary_10_1007_s42979_024_03364_5 crossref_primary_10_1109_TITS_2022_3188671 crossref_primary_10_3389_fcomp_2023_997159 crossref_primary_10_1002_dac_5500 crossref_primary_10_1007_s10207_024_00935_8 crossref_primary_10_1016_j_iswa_2022_200152 crossref_primary_10_1111_exsy_13726 crossref_primary_10_1007_s10462_023_10437_z crossref_primary_10_1016_j_compeleceng_2024_109725 crossref_primary_10_1016_j_comnet_2022_108826 crossref_primary_10_1109_ACCESS_2021_3049249 crossref_primary_10_1109_ACCESS_2023_3349287 crossref_primary_10_1007_s12065_024_00949_0 crossref_primary_10_1109_ACCESS_2021_3097247 crossref_primary_10_1007_s10586_024_04495_3 crossref_primary_10_1016_j_iot_2024_101377 crossref_primary_10_3390_s20020461 crossref_primary_10_35940_ijrte_A8226_14010525 crossref_primary_10_1049_ntw2_12128 crossref_primary_10_1016_j_comnet_2020_107784 crossref_primary_10_3390_s22093400 crossref_primary_10_1016_j_comcom_2022_07_007 crossref_primary_10_1016_j_procs_2024_11_089 crossref_primary_10_1016_j_compeleceng_2023_108626 crossref_primary_10_3390_app11188383 crossref_primary_10_1002_cpe_7380 crossref_primary_10_1016_j_adhoc_2023_103331 crossref_primary_10_1109_ACCESS_2022_3195053 crossref_primary_10_3390_s22218085 crossref_primary_10_31185_wjcms_363 crossref_primary_10_3390_w16142038 crossref_primary_10_1109_ACCESS_2022_3151248 crossref_primary_10_3390_pr13030753 crossref_primary_10_1109_JIOT_2021_3106898 crossref_primary_10_3390_electronics12234806 crossref_primary_10_3390_s21092987 crossref_primary_10_1109_ACCESS_2022_3225074 crossref_primary_10_1155_2022_9304689 crossref_primary_10_1109_ACCESS_2022_3220622 crossref_primary_10_1109_ACCESS_2023_3241588 crossref_primary_10_1016_j_eswa_2023_121751 crossref_primary_10_3390_s25113341 crossref_primary_10_1109_ACCESS_2020_3029191 crossref_primary_10_1186_s40537_023_00805_5 crossref_primary_10_1016_j_simpat_2019_102041 crossref_primary_10_1109_ACCESS_2020_3037359 crossref_primary_10_1109_ACCESS_2025_3550392 crossref_primary_10_3390_s20205800 crossref_primary_10_1109_JIOT_2020_3031162 crossref_primary_10_1186_s13677_023_00527_2 crossref_primary_10_1186_s13677_022_00338_x crossref_primary_10_1007_s11042_024_19919_w crossref_primary_10_1155_2020_6689134 crossref_primary_10_1109_ACCESS_2024_3375395 crossref_primary_10_1155_2022_8030510 crossref_primary_10_32604_cmc_2023_041667 crossref_primary_10_3390_s21196432 crossref_primary_10_3390_s21041034 crossref_primary_10_3390_s24020713 crossref_primary_10_1109_ACCESS_2022_3153716 crossref_primary_10_3390_electronics11091502 crossref_primary_10_3233_WEB_230109A crossref_primary_10_1007_s10664_023_10302_1 crossref_primary_10_32604_cmc_2023_032220 crossref_primary_10_1007_s00521_022_07084_w crossref_primary_10_3390_technologies12100203 crossref_primary_10_1016_j_measen_2024_101263 crossref_primary_10_3390_electronics11020198 crossref_primary_10_3390_math12121799 crossref_primary_10_3390_s22114167 crossref_primary_10_7717_peerj_cs_721 crossref_primary_10_1016_j_iot_2023_100750 crossref_primary_10_1145_3585520 crossref_primary_10_1016_j_jnca_2021_103111 crossref_primary_10_32604_cmc_2023_032591 crossref_primary_10_1007_s10586_022_03607_1 crossref_primary_10_1109_JIOT_2022_3167005 crossref_primary_10_1109_ACCESS_2020_3012411 crossref_primary_10_1007_s10586_022_03645_9 crossref_primary_10_3390_s23125568 crossref_primary_10_3390_info11050279 crossref_primary_10_3390_ijerph17020408 crossref_primary_10_1109_TCCN_2024_3355433 crossref_primary_10_1016_j_cose_2022_103014 crossref_primary_10_1016_j_cose_2023_103315 crossref_primary_10_1109_ACCESS_2024_3393548 crossref_primary_10_3390_app10030794 crossref_primary_10_3390_smartcities8010013 crossref_primary_10_1016_j_engappai_2023_107132 crossref_primary_10_1002_ett_4169 |
| Cites_doi | 10.1109/ICCCN.2016.7568495 10.1007/s11277-011-0385-5 10.1109/CIS.2013.145 10.1016/j.adhoc.2013.04.014 10.1145/2508859.2512494 10.1109/CNS.2014.6997468 10.1002/dac.2356 10.1109/WiMOB.2013.6673419 10.1007/978-81-322-2752-6_49 10.3390/info7020025 10.1016/j.comcom.2016.12.001 10.1145/3212687.3212872 10.1016/j.future.2013.01.010 10.13052/jcsm2245-1439.414 10.1016/j.adhoc.2012.02.016 10.1080/17434440.2018.1483235 10.1016/j.dcan.2017.04.003 10.1109/WiSPNET.2016.7566473 10.1109/ICNC.2011.6022060 10.1109/JIOT.2018.2847733 10.1109/FIT.2012.53 10.1109/ICCAD.2014.7001385 10.1186/s13638-018-1128-z 10.1016/j.comnet.2012.12.018 10.1109/ISI.2017.8004904 |
| ContentType | Journal Article |
| Copyright | 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2019 by the authors. 2019 |
| Copyright_xml | – notice: 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: 2019 by the authors. 2019 |
| DBID | AAYXX CITATION NPM 3V. 7X7 7XB 88E 8FI 8FJ 8FK ABUWG AFKRA AZQEC BENPR CCPQU DWQXO FYUFA GHDGH K9. M0S M1P PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQQKQ PQUKI PRINS 7X8 5PM DOA |
| DOI | 10.3390/s19091977 |
| DatabaseName | CrossRef PubMed ProQuest Central (Corporate) ProQuest - Health & Medical Complete保健、医学与药学数据库 ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials - QC ProQuest Central ProQuest One Community College ProQuest Central Proquest Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Health & Medical Complete (Alumni) Health & Medical Collection (Alumni) Medical Database ProQuest Central Premium ProQuest One Academic (New) ProQuest Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef PubMed Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Central China ProQuest Central ProQuest Health & Medical Research Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Health & Medical Research Collection ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest One Academic Eastern Edition ProQuest Hospital Collection Health Research Premium Collection (Alumni) ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | PubMed MEDLINE - Academic Publicly Available Content Database CrossRef |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: PIMPY name: Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1424-8220 |
| ExternalDocumentID | oai_doaj_org_article_08059090c99f42e6a7b809d8a6839f3a PMC6539759 31035611 10_3390_s19091977 |
| Genre | Journal Article |
| GeographicLocations | United States--US China India |
| GeographicLocations_xml | – name: China – name: United States--US – name: India |
| GroupedDBID | --- 123 2WC 53G 5VS 7X7 88E 8FE 8FG 8FI 8FJ AADQD AAHBH AAYXX ABDBF ABUWG ACUHS ADBBV ADMLS AENEX AFFHD AFKRA AFZYC ALMA_UNASSIGNED_HOLDINGS BENPR BPHCQ BVXVI CCPQU CITATION CS3 D1I DU5 E3Z EBD ESX F5P FYUFA GROUPED_DOAJ GX1 HH5 HMCUK HYE KQ8 L6V M1P M48 MODMG M~E OK1 OVT P2P P62 PHGZM PHGZT PIMPY PJZUB PPXIY PQQKQ PROAC PSQYO RNS RPM TUS UKHRP XSB ~8M ALIPV NPM 3V. 7XB 8FK AZQEC DWQXO K9. PKEHL PQEST PQUKI PRINS 7X8 5PM |
| ID | FETCH-LOGICAL-c535t-453b20f5c4e66c1cc9754ce23b6f1db959d88bd02defa22c8084c543db2330b93 |
| IEDL.DBID | DOA |
| ISICitedReferencesCount | 164 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000469766800021&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1424-8220 |
| IngestDate | Fri Oct 03 12:53:37 EDT 2025 Tue Nov 04 01:52:42 EST 2025 Sun Nov 09 11:56:55 EST 2025 Tue Oct 07 06:48:22 EDT 2025 Thu Apr 03 07:08:19 EDT 2025 Sat Nov 29 07:18:02 EST 2025 Tue Nov 18 21:42:20 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 9 |
| Keywords | Intrusion-Detection System (IDS) deep learning Internet of Things (IoT) security machine learning |
| Language | English |
| License | Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c535t-453b20f5c4e66c1cc9754ce23b6f1db959d88bd02defa22c8084c543db2330b93 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ORCID | 0000-0002-0583-6494 |
| OpenAccessLink | https://doaj.org/article/08059090c99f42e6a7b809d8a6839f3a |
| PMID | 31035611 |
| PQID | 2301614675 |
| PQPubID | 2032333 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_08059090c99f42e6a7b809d8a6839f3a pubmedcentral_primary_oai_pubmedcentral_nih_gov_6539759 proquest_miscellaneous_2217469887 proquest_journals_2301614675 pubmed_primary_31035611 crossref_citationtrail_10_3390_s19091977 crossref_primary_10_3390_s19091977 |
| PublicationCentury | 2000 |
| PublicationDate | 20190427 |
| PublicationDateYYYYMMDD | 2019-04-27 |
| PublicationDate_xml | – month: 4 year: 2019 text: 20190427 day: 27 |
| PublicationDecade | 2010 |
| PublicationPlace | Switzerland |
| PublicationPlace_xml | – name: Switzerland – name: Basel |
| PublicationTitle | Sensors (Basel, Switzerland) |
| PublicationTitleAlternate | Sensors (Basel) |
| PublicationYear | 2019 |
| Publisher | MDPI AG MDPI |
| Publisher_xml | – name: MDPI AG – name: MDPI |
| References | ref_13 ref_12 ref_34 ref_33 ref_10 ref_32 Sfar (ref_19) 2018; 4 ref_30 ref_17 ref_16 ref_15 Le (ref_14) 2012; 25 Liu (ref_31) 2018; 2018 Gubbi (ref_1) 2013; 29 ref_25 ref_24 ref_23 ref_22 ref_21 Fu (ref_27) 2017; 2017 ref_20 Raza (ref_28) 2013; 11 ref_3 Miorandi (ref_2) 2012; 10 ref_29 Pycroft (ref_11) 2018; 15 Bostani (ref_26) 2017; 98 ref_9 Heer (ref_18) 2011; 61 ref_8 ref_5 Abomhara (ref_6) 2015; 4 ref_7 Roman (ref_4) 2013; 57 |
| References_xml | – ident: ref_7 – ident: ref_30 doi: 10.1109/ICCCN.2016.7568495 – ident: ref_9 – volume: 61 start-page: 527 year: 2011 ident: ref_18 article-title: Security Challenges in the IP-based Internet of Things publication-title: Wirel. Person. Commun. doi: 10.1007/s11277-011-0385-5 – ident: ref_5 – ident: ref_32 – ident: ref_3 – ident: ref_21 doi: 10.1109/CIS.2013.145 – ident: ref_34 – volume: 11 start-page: 2661 year: 2013 ident: ref_28 article-title: SVELTE: Real-time Intrusion Detection in the Internet of Things publication-title: Ad Hoc Netw. doi: 10.1016/j.adhoc.2013.04.014 – ident: ref_12 doi: 10.1145/2508859.2512494 – ident: ref_13 doi: 10.1109/CNS.2014.6997468 – volume: 25 start-page: 1189 year: 2012 ident: ref_14 article-title: 6LoWPAN: A study on QoS security threats and countermeasures using intrusion detection system approach publication-title: Int. J. Commun. Syst. doi: 10.1002/dac.2356 – ident: ref_22 doi: 10.1109/WiMOB.2013.6673419 – ident: ref_23 doi: 10.1007/978-81-322-2752-6_49 – ident: ref_24 doi: 10.3390/info7020025 – volume: 98 start-page: 52 year: 2017 ident: ref_26 article-title: Hybrid of anomaly-based and specification-based IDS for Internet of Things using unsupervised OPF based on MapReduce approach publication-title: Comput. Commun. doi: 10.1016/j.comcom.2016.12.001 – ident: ref_15 doi: 10.1145/3212687.3212872 – volume: 29 start-page: 1645 year: 2013 ident: ref_1 article-title: Internet of Things (IoT): A vision, architectural elements, and future directions publication-title: Future Gener. Comput. Syst. doi: 10.1016/j.future.2013.01.010 – volume: 4 start-page: 65 year: 2015 ident: ref_6 article-title: Cyber Security and the Internet of Things: Vulnerabilities, Threats, Intruders and Attacks publication-title: J. Cyber Secur. Mobil. doi: 10.13052/jcsm2245-1439.414 – volume: 10 start-page: 1497 year: 2012 ident: ref_2 article-title: Internet of Things: Vision, applications and research challenges publication-title: Ad Hoc Netw. doi: 10.1016/j.adhoc.2012.02.016 – ident: ref_33 – volume: 15 start-page: 403 year: 2018 ident: ref_11 article-title: Security of implantable medical devices with wireless connections: The dangers of cyber-attacks publication-title: Expert Rev. Med. Devices doi: 10.1080/17434440.2018.1483235 – volume: 4 start-page: 118 year: 2018 ident: ref_19 article-title: A roadmap for security challenges in the Internet of Things publication-title: Digit. Commun. Netw. doi: 10.1016/j.dcan.2017.04.003 – ident: ref_10 – ident: ref_25 doi: 10.1109/WiSPNET.2016.7566473 – volume: 2017 start-page: 1750637 year: 2017 ident: ref_27 article-title: An Automata Based Intrusion Detection Method for Internet of Things publication-title: Mobile Inf. Syst. – ident: ref_29 doi: 10.1109/ICNC.2011.6022060 – ident: ref_20 doi: 10.1109/JIOT.2018.2847733 – ident: ref_16 doi: 10.1109/FIT.2012.53 – ident: ref_17 doi: 10.1109/ICCAD.2014.7001385 – volume: 2018 start-page: 113 year: 2018 ident: ref_31 article-title: An intrusion detection method for internet of things based on suppressed fuzzy clustering publication-title: EURASIP J. Wirel. Commun. Netw. doi: 10.1186/s13638-018-1128-z – volume: 57 start-page: 2266 year: 2013 ident: ref_4 article-title: On the features and challenges of security and privacy in distributed Internet of Things publication-title: Comput. Netw. doi: 10.1016/j.comnet.2012.12.018 – ident: ref_8 doi: 10.1109/ISI.2017.8004904 |
| SSID | ssj0023338 |
| Score | 2.6498609 |
| Snippet | Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly... |
| SourceID | doaj pubmedcentral proquest pubmed crossref |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source |
| StartPage | 1977 |
| SubjectTerms | Algorithms Deep learning International conferences Internet of Things Internet of Things (IoT) Intrusion detection systems Intrusion-Detection System (IDS) machine learning Malware Privacy security Security systems Wireless networks |
| SummonAdditionalLinks | – databaseName: ProQuest Central dbid: BENPR link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwEB7BlgM9UJ4lUJBBHLhYTWI7tk-IvgRCWlWoSL1FfqWthJJls_D7GSfe0K2qXlBu8Rwcz8Pf2JNvAD40yhTGOEZ94BVFoyiolbmglgVlhVWBaz80m5DzuTo_16fpwK1PZZXrmDgEat-5eEa-j1AZwQm6tfi0-EVj16h4u5paaNyHrchUxmewdXA8P_0-pVwMM7CRT4hhcr_f4_anC4Q8G7vQQNZ_G8K8WSh5bec52fnfOT-GRwlzks-jkTyBe6F9CtvXmAifwbezoXy2J0chLGgiXb2gR8sYDMnXNv6agRrE4dVQu9USBLsEwSMZjxTDinQNGZuAPocfJ8dnh19o6rNAnWBiRblgtswb4XioKlc4p6XgLpTMVk3hrRbaK2V9XvrQmLJ0KlfcCc68xfXNrWYvYNZ2bXgJxBipvCgd4qbYcb2xHh_HrIk5OJc-g4_rda9dIiGPvTB-1piMRBXVk4oyeD-JLkbmjduEDqLyJoFIlj286JYXdfK9GkGxQPncad3wMlRGWpXjN5kK0WHDTAZ7a_XVyYP7-p_uMng3DaPvxQsV04buN8rEfK7SGKcz2B0tZZpJ7N-G2LTIQG7Y0MZUN0faq8uB3zuyBUuhX909rdfwEMHbcLNVyj2YoSGEN_DA_Vld9cu3yRH-AnhOFGo priority: 102 providerName: ProQuest |
| Title | Towards Deep-Learning-Driven Intrusion Detection for the Internet of Things |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/31035611 https://www.proquest.com/docview/2301614675 https://www.proquest.com/docview/2217469887 https://pubmed.ncbi.nlm.nih.gov/PMC6539759 https://doaj.org/article/08059090c99f42e6a7b809d8a6839f3a |
| Volume | 19 |
| WOSCitedRecordID | wos000469766800021&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 1424-8220 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0023338 issn: 1424-8220 databaseCode: DOA dateStart: 20010101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 1424-8220 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0023338 issn: 1424-8220 databaseCode: M~E dateStart: 20010101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVPQU databaseName: ProQuest - Health & Medical Complete保健、医学与药学数据库 customDbUrl: eissn: 1424-8220 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0023338 issn: 1424-8220 databaseCode: 7X7 dateStart: 20010101 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1424-8220 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0023338 issn: 1424-8220 databaseCode: BENPR dateStart: 20010101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database customDbUrl: eissn: 1424-8220 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0023338 issn: 1424-8220 databaseCode: PIMPY dateStart: 20010101 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1La9wwEB7SpIfmUPqO23RRSg-9iNiWZEnHptnQELIsJYXtyejlNBC8IbvJMb-9I9lrdkugl2LQQZqDPDOSvrHG3wB8bpQpjHGM-sArik5RUCtzQS0LygqrAtc-FZuQk4mazfR0rdRXzAnr6IE7xR0iohE617nTuuFlqIy0KtdemQqP9oYlaIQyq2CqD7UYRl4djxDDoP5wgceeLhDqbJw-iaT_MWT5d4Lk2olz8gKe91CRfO2m-BK2QvsKdtcIBF_D2UXKel2Q4xBuaM-VekmPb-MeRk7b-EcFKh6HlynlqiWIUQliPtJ9CQxLMm9IV7vzDfw8GV98-0778gjUCSaWlAtmy7wRjoeqcoVzWgruQsls1RTeaoFaUtbnpQ-NKUuncsWd4MxbVE9uNXsL2-28DXtAjJHKi9Ih3ImF0hvr8XHMmhg6c-kz-LJSW-167vBYwuK6xhgiargeNJzBp0H0piPMeEzoKOp-EIgc16kDLV_3lq__ZfkM9leWq_uFt6gxokIMi7u_yOBgGMYlE-9BTBvmdygTw7BK4_aawbvO0MNMYtk1hJRFBnLDBTamujnSXv1OtNyR5FcK_f5_vNsHeIbILF1blXIfttFdwkd46u6XV4vbETyRM5laNYKdo_Fk-mOU_B_b84cx9k1Pz6e__gA33gqF |
| linkProvider | Directory of Open Access Journals |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3LbtQwFL2qpkjAgvcjUCAgkNhYTew4sRcIAUPV0bSjWQxSWQW_0laqkmEygPgpvpHrvOigil0XaHbxXdiT4-tzbeccgJeFULFShhHrkpQgKGKis4gTzZzQXAuXSNuYTWSzmTg6kvMt-NV_C-OvVfY5sUnUtjJ-j3wXqTKSE5zW_O3yK_GuUf50tbfQaGExdT9_YMlWv5mM8f2-onTv4-LDPulcBYjhjK9JwpmmUcFN4tLUxMbIjCfGUabTIrZacmmF0Dai1hWKUiMikRieMKsp1v7aiy9hyt9OcFxiBNvzyeH881DiMaz4Wv0ixmS0W-NyK2OkWBurXmMOcBGj_fti5rmVbu_m__Yf3YIbHacO37WT4DZsufIOXD-ntHgXpovmenAdjp1bkk5U9piMVz7Zh5PSf3qCCMXmdXM3rQyRzIdIjsN2y9Stw6oIW5PTe_DpUkZzH0ZlVbqHECqVCcupQV7oHeULbfFnmFZ-jyHJbACv-_ecm05k3Xt9nOVYbHlI5AMkAngxhC5bZZGLgt57sAwBXgy8eVCtjvMut-RI-jnGR0bKIqEuVZkWEY5Jpch-C6YC2OnhkncZqs7_YCWA50Mz5hZ_YKRKV33DGF-vphLXoQAetMgceuL96ZB7xwFkG5jd6OpmS3l60uiXezXkjMtH_-7WM7i6vzg8yA8ms-ljuIZEtTnFo9kOjBAU7glcMd_Xp_XqaTcJQ_hy2Zj-DfQlcbc |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9NAEB5VLUJw4P0wFFgQSFys2Puwdw8IASEiCkQ5FKmc3H25VEJOiAOIv8avY9YvGlRx6wH55p3D2v525pvd8TcAT0upU60ti53nWYygSGOTJyI2zEsjjPRcuabZRD6fy8NDtdiBX_2_MKGssveJjaN2Sxv2yEdIlZGc4LIWo7Iri1iMJy9XX-PQQSqctPbtNFqIzPzPH5i-1S-mY_zWzyidvD148y7uOgzEVjCxiblghialsNxnmU2tVbng1lNmsjJ1RgnlpDQuoc6XmlIrE8mt4MwZylhighATuv89pOQc19jeYvph8WlI9xhmf62WEWMqGdUYelWKdGsrAjaNAs5it38XaZ6KepOr__P7ugZXOq5NXrWL4zrs-OoGXD6lwHgTZgdN2XBNxt6v4k5s9jger0MQINMq_JKCyMXhTVOzVhEk-QRJM2m3Uv2GLEvSNj-9BR_P5Wluw261rPxdIFrn0glqkS-GTvOlcXhZZnTYe-C5i-B5_80L24mvhx4gXwpMwgI8igEeETwZTFet4shZRq8DcAaDIBLe3Fiuj4vO5xSYDAi0T6xSJac-07mRCT6TzpAVl0xHsN9Dp-g8V138wU0Ej4dh9DnhIElXfvkNbUIemymMTxHcaVE6zCT0rUNOnkaQb-F3a6rbI9XJ50bXPKgk50Ld-_e0HsFFBHLxfjqf3YdLyF-bwz2a78MuYsI_gAv2--akXj_s1iOBo_OG9G_41Hp3 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Towards+Deep-Learning-Driven+Intrusion+Detection+for+the+Internet+of+Things&rft.jtitle=Sensors+%28Basel%2C+Switzerland%29&rft.au=Geethapriya+Thamilarasu&rft.au=Shiven+Chawla&rft.date=2019-04-27&rft.pub=MDPI+AG&rft.eissn=1424-8220&rft.volume=19&rft.issue=9&rft.spage=1977&rft_id=info:doi/10.3390%2Fs19091977&rft.externalDBID=DOA&rft.externalDocID=oai_doaj_org_article_08059090c99f42e6a7b809d8a6839f3a |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1424-8220&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1424-8220&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1424-8220&client=summon |