Resilient and Trustworthy Dynamic Data-driven Application Systems (DDDAS) Services for Crisis Management Environments
Future crisis management systems needresilient and trustworthy infrastructures to quickly develop reliable applications and processes, andensure end-to-end security, trust, and privacy. Due to the multiplicity and diversity of involved actors, volumes of data, and heterogeneity of shared information...
Uloženo v:
| Vydáno v: | Procedia computer science Ročník 51; s. 2623 - 2637 |
|---|---|
| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
2015
Elsevier |
| Témata: | |
| ISSN: | 1877-0509, 1877-0509 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | Future crisis management systems needresilient and trustworthy infrastructures to quickly develop reliable applications and processes, andensure end-to-end security, trust, and privacy. Due to the multiplicity and diversity of involved actors, volumes of data, and heterogeneity of shared information;crisis management systems tend to be highly vulnerable and subjectto unforeseen incidents. As a result, the dependability of crisis management systems can be at risk. This paper presents a cloud-based resilient and trustworthy infrastructure (known as rDaaS) to quickly develop securecrisis management systems. The rDaaSintegrates the Dynamic Data-DrivenApplication Systems (DDDAS) paradigm into a service-oriented architectureover cloud technology andprovidesa set of resilient DDDAS-As-A Service (rDaaS)components to build secure and trusted adaptable crisis processes. The rDaaSalso ensures resilience and security by obfuscating the execution environment andapplying Behavior Software Encryption and Moving Technique Defense. A simulation environment for a nuclear plant crisis managementcase study is illustrated to build resilient and trusted crisis response processes. |
|---|---|
| AbstractList | In this paper, the multi-criteria decision making in which criteria are assumed to be dependent with each other is investigated. Choquet integral is employed to aggregate the criteria evaluations of alternatives to reflect the interactions of the criteria. Objective and subjective information are integrated to derive the interactions of the criteria. The objective information of alternatives is expressed by decision matrix, whereas the subjective information is expressed by utilities or interval preference relations. Models are given to minimize the objective and subjective information. The proposed method can be considered as an extension of the existing methods, and can obtain smaller deviations and better overall evaluations of alternatives. Future crisis management systems needresilient and trustworthy infrastructures to quickly develop reliable applications and processes, andensure end-to-end security, trust, and privacy. Due to the multiplicity and diversity of involved actors, volumes of data, and heterogeneity of shared information;crisis management systems tend to be highly vulnerable and subjectto unforeseen incidents. As a result, the dependability of crisis management systems can be at risk. This paper presents a cloud-based resilient and trustworthy infrastructure (known as rDaaS) to quickly develop securecrisis management systems. The rDaaSintegrates the Dynamic Data-DrivenApplication Systems (DDDAS) paradigm into a service-oriented architectureover cloud technology andprovidesa set of resilient DDDAS-As-A Service (rDaaS)components to build secure and trusted adaptable crisis processes. The rDaaSalso ensures resilience and security by obfuscating the execution environment andapplying Behavior Software Encryption and Moving Technique Defense. A simulation environment for a nuclear plant crisis managementcase study is illustrated to build resilient and trusted crisis response processes. |
| Author | Badr, Youakim AL-Nashif, Youssif Blasch, Erik Hariri, Salim |
| Author_xml | – sequence: 1 givenname: Youakim surname: Badr fullname: Badr, Youakim organization: Université de Lyon, CNRS LIRIS, UMR5205, INSA-Lyon, France – sequence: 2 givenname: Salim surname: Hariri fullname: Hariri, Salim organization: Center for Cloud and Autonomic Computing The University of Arizona, Tucson, Arizona – sequence: 3 givenname: Youssif surname: AL-Nashif fullname: AL-Nashif, Youssif organization: Old Dominion University, Norfolk, Virginia – sequence: 4 givenname: Erik surname: Blasch fullname: Blasch, Erik organization: Air Force Research Laboratory, Information Directorate, Rome, NY |
| BackLink | https://hal.science/hal-01212583$$DView record in HAL |
| BookMark | eNqFkU1v2zAMhoWhA9Z1_QW76Nge7Ip2HMuHHYK4X0CGAUt3FhiJbhU4UiCpLvLvazfDUOyw8UKCeB8eHn5mJ847YuwriBwEzK-2-T54HfNCQJWLKi9r8YGdgqzrTFSiOXk3f2LnMW7FWKWUDdSn7PknRdtbcomjM_whPMf04kN6OvD24HBnNW8xYWaCHcjxxX7fW43JesfXh5hoF_lF27aL9SVfUxispsg7H_gy2Ggj_44OH2k3nb92gw3eTXP8wj522Ec6_93P2K-b64flXbb6cXu_XKwyXcoiZRrm2Blqim4mhdBQaQDaQCOkEWbTwabB2bzThazlTEKDdQXzGSE0ZsyBwfKMXR7vPmGv9sHuMByUR6vuFis17QQUUFSyHGDMlsesDj7GQN0fAISaRKutehOtJtFKVGoUPVLNX5S26c1PCmj7_7DfjiyNCgZLQUU9fkKTsYF0Usbbf_Kv3MGd4Q |
| CitedBy_id | crossref_primary_10_1109_TNS_2022_3162216 crossref_primary_10_3390_ijgi5040042 crossref_primary_10_1109_TNSM_2021_3071774 crossref_primary_10_1016_j_cose_2024_103792 crossref_primary_10_1177_0037549719856100 |
| Cites_doi | 10.1145/375663.375668 10.1109/ICCSN.2011.6014783 10.1016/j.procs.2014.05.117 10.1109/CCNC.2011.5766528 10.1109/MAES.2012.6366088 10.1145/948143.948147 10.1016/j.procs.2013.05.369 10.5120/7292-0578 10.1145/2480741.2480757 10.1109/TSE.1985.231893 10.1145/775047.775103 10.1145/347090.347160 10.1109/MILCOM.2011.6127486 10.1016/j.jnca.2010.07.006 10.1117/12.2050255 10.1109/ARES.2008.171 10.1109/TSE.1987.232894 10.1109/ICIF.2006.301670 10.1109/MSP.2009.87 10.1002/qre.392 10.1145/342009.335388 10.1109/ICDCSW.2012.42 10.1007/978-3-642-40543-3_71 10.1016/j.infsof.2008.02.006 10.1109/12.24266 10.1109/MAES.2014.130115 10.1117/12.2016326 10.1016/j.ins.2007.03.025 10.1109/PDP.2011.45 10.6028/NIST.SP.800-94 10.1109/SECPRI.1988.8098 10.1117/12.2054690 10.1109/DSNW.2012.6264686 10.1145/2480362.2480505 10.1007/978-1-4615-0953-0_4 10.1016/S0065-2458(08)60008-X 10.1145/586110.586146 10.1109/AICCSA.2011.6126606 10.1109/NAECON.2014.7045790 10.1109/ICAC.2008.25 10.1109/ICCIS.2013.515 10.1007/s10846-013-9964-x 10.1145/335191.335437 10.1109/ICIF.2006.301581 10.1109/SERVICES.2011.45 10.1117/12.2050782 10.1109/ICCAC.2014.35 10.3233/JCS-2002-101-205 10.1007/s11227-012-0831-5 10.1007/978-1-4614-0977-9_2 10.1504/IJCC.2013.055266 10.1109/NAECON.2011.6183090 10.1016/S1389-1286(99)00112-7 10.1007/978-1-4614-3296-8_4 10.1117/12.720090 |
| ContentType | Journal Article |
| Copyright | 2015 Distributed under a Creative Commons Attribution 4.0 International License |
| Copyright_xml | – notice: 2015 – notice: Distributed under a Creative Commons Attribution 4.0 International License |
| DBID | 6I. AAFTH AAYXX CITATION 1XC |
| DOI | 10.1016/j.procs.2015.05.370 |
| DatabaseName | ScienceDirect Open Access Titles Elsevier:ScienceDirect:Open Access CrossRef Hyper Article en Ligne (HAL) |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1877-0509 |
| EndPage | 2637 |
| ExternalDocumentID | oai:HAL:hal-01212583v1 10_1016_j_procs_2015_05_370 S1877050915011783 |
| GroupedDBID | --K 0R~ 0SF 1B1 457 5VS 6I. 71M AACTN AAEDT AAEDW AAFTH AAIKJ AALRI AAQFI AAXUO ABMAC ACGFS ADBBV ADEZE AEXQZ AFTJW AGHFR AITUG ALMA_UNASSIGNED_HOLDINGS AMRAJ E3Z EBS EJD EP3 FDB FNPLU HZ~ IXB KQ8 M41 M~E NCXOZ O-L O9- OK1 P2P RIG ROL SES SSZ 9DU AAYWO AAYXX ABWVN ACRPL ACVFH ADCNI ADNMO ADVLN AEUPX AFPUW AIGII AKBMS AKRWK AKYEP CITATION ~HD 1XC |
| ID | FETCH-LOGICAL-c382t-c16afde92f4800c15c11eb1908d0dbf1b9a46fc28784819a75164ea19d11e1da3 |
| ISICitedReferencesCount | 17 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000373939100268&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1877-0509 |
| IngestDate | Tue Oct 14 20:24:32 EDT 2025 Tue Nov 18 22:11:29 EST 2025 Sat Nov 29 07:53:13 EST 2025 Wed May 17 01:33:35 EDT 2023 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | service-oriented computing cloud computing resilience trust and security rDaaS subjective information Choquet integral Multi-criteria decision making objective information |
| Language | English |
| License | http://creativecommons.org/licenses/by-nc-nd/4.0 Distributed under a Creative Commons Attribution 4.0 International License: http://creativecommons.org/licenses/by/4.0 |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c382t-c16afde92f4800c15c11eb1908d0dbf1b9a46fc28784819a75164ea19d11e1da3 |
| ORCID | 0000-0002-8976-7894 |
| OpenAccessLink | https://dx.doi.org/10.1016/j.procs.2015.05.370 |
| PageCount | 15 |
| ParticipantIDs | hal_primary_oai_HAL_hal_01212583v1 crossref_primary_10_1016_j_procs_2015_05_370 crossref_citationtrail_10_1016_j_procs_2015_05_370 elsevier_sciencedirect_doi_10_1016_j_procs_2015_05_370 |
| PublicationCentury | 2000 |
| PublicationDate | 2015 2015-00-00 |
| PublicationDateYYYYMMDD | 2015-01-01 |
| PublicationDate_xml | – year: 2015 text: 2015 |
| PublicationDecade | 2010 |
| PublicationTitle | Procedia computer science |
| PublicationYear | 2015 |
| Publisher | Elsevier B.V Elsevier |
| Publisher_xml | – name: Elsevier B.V – name: Elsevier |
| References | M. Abbasy and B. Shanmugam, “Enabling Data Hiding for Resource Sharing in Cloud Computing Environments Based on DNA Sequences,” in K. Scarfone and Peter Mell, Guide to Intrusion Detection and Prevention Systems (IDPS). Computer Security Resource Center (National Institute of Standards and Technology) (800-94), 2007, Retrieved 1 January 2010. D. L. Pipkin. E. Blasch, “Context aided Sensor and Human-based Information Fusion” Information Fusion in a Cloud Computing Era: A Systems-Level Perspective A. Tyrrell, “Recovery Blocks and Algorithm Based Fault tolerance,” in 16 September 2009. [Accessed January 2013].]. Available: http://www.cyber.st.dhs.gov/docs/National_Cyber_Leap_Year_Summit_2009_Co-Chairs_Report.pdf. P. C. G. Costa, K.B. Laskey D. Evans, A. Nguyen-Tuong and J. Knight, “Effectiveness of Moving Target Defenses,” in pp. 18-21, 1988. pp. 427-438, 2000. V. Paxson, “Bro: a system for detecting network intruders in real-time,” CRC Press, Taylor & Francis Group, 2015. C. C. Aggarwal and P. S. Yu, “Outlier detection for high dimensional data,” E. Blasch, R. Breton, and P. Valin, “Using the C-OODA Model for CIMIC Analysis,” H. Zeng, “Research on Developing an Attack and Defense Lab Environment for Cross Site Scripting Education in Higher Vocational Colleges,” M. Rosenblum and T. Garfinkel, “When virtual is harder than real: security challenges in virtual machine based computing environments,” in H. Alipour, Y. Al-Nashif, S. Hariri, “DNS Anomaly Behavior Analysis against Cyber Attacks”, submitted to 10(1-2):105-136, 2002. Springer Publishing, 2013. C. Tunc, F. Fargo, Y. Al-Nashif, S. Hariri, J. Hughes, Autonomic Resilient Cloud Management (ARCM) E. Blasch, A. Steinberg, S. Das, J. Llinas, C.-Y. Chong, O. Kessler, E. Waltz, and F. White, “Revisiting the JDL model for information Exploitation,” E. Blasch, K.B. Laskey, A-L. Joussselme, V. Dragos, P.C. G. Costa, and J. Dezert, “URREF Reliability versus Credibility in Information Fusion (STANAG 2511),” Context aided Video-to-Text Information Fusion B. Liu, E. Blasch, Y. Chen, A.J. Aved Computer Science Laboratory, SRI International, 1995. E. Blasch, A. Jøsang, J. Dezert, P.C. G. Costa, K.B. Laskey, A-L. Jousselme, “URREF Self-Confidence in Information Fusion Trust,” 2010. M. S., Siddiqui, DVerma, “Cross site request forgery: A common web application weakness,” M. Roesch, “Snort - Lightweight Intrusion Detection for Networks,” G. Dsouza, G. Rodríguez, Y.B. Al-Nashif, S. Hariri, “Building resilient cloud services using DDDAS and moving target defence,” 1999. (Amsterdam, Netherlands: 1999), 31(23-24):2435-2463, 1999. 13(2):222-232, 1987. . K. Yamanishi, J. Takeuchi, G.J. Williams, and P. Milne, “On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms,” 177(18):3799-3821, 2007. J. Feng, Y. Chen, D. Summerville, W. Ku, Z. Su, “Enhancing cloud storage security against roll-back attacks with a new fair multi-party non-repudiation protocol,” in vol. 38, no. 5, pp. pp. 626-636, 1989. E. Blasch, Y Al-Nashif, and S. Hariri, “Static versus Dynamic Data Information Fusion analysis using DDDAS for Cyber Trust,” High Level Information Fusion (HLIF) Survey of Models, Issues, and Grand Challenges Kluwer Academics, 78-100, 2002. G. Chen, D. Shen, C. Kwan, J. Cruz Vols. SE-11, no. 12, 1985. 2(2/3): 171-190, 2013. A platform for event-driven agility of processes: A delivery context use-case. Towards Unbiased Evaluation of Uncertainty Reasoning: The URREF Ontology R. P. Viswanathan, Y. Al-Nashif, S. Hariri, “Application Attack Detection System (AADS): An Anomaly Based Behavior Analysis Approach,” 1996. vol. 9, 2011. L. Ge, W. Yu, D. Shen, G. Chen, K. Pham, et al., “Toward Effectiveness and Agility of Network Security Situational Awareness using Moving Target Defense (MTD),” Proc. SPIE, Vol. 9085, 2014. A-M. Barthe-Delanoë Vol. 29, No. 10, pp. 16-24, 2014. 50 (12), 1281-1294, 2008. W. Toy, “Fault-Tolerant Computing,” in Artech House, Norwood, MA, 2012. W. Li, Y. Badr, F. Biennier, “Service Farming: An Ad-hoc and QoS-aware Web Service Composition Approach,” Dans SAC 2013, Coimbra, Portugal, pp. 750-756, 2013. R. Bhadauria and S. Sanyal, “Survey on Security Issues in Cloud Computing and Associated Mitigation Techniques,” Technical Report, SRI International Menlo Park, California, 1994. G. Vallee, C. Engelmann, A. Tikotekar, T. Naughton, K. Charoenpornwattana, C. Leangsuksun and S. Scott, “A Framework for Proactive Fault Tolerance,” 2003. vol. 34, pp. 1-11, 2011. S. Staniford, J.A. Hoagland, and J. M. McAlerney, “Practical automated detection of stealthy portscans,” E. Blasch, “Trust Metrics in Information Fusion,” Proc. SPIE, Vol. 9091, 2014. D. Jeffrey, G. Sanjay, “MapReduce: Simplified Data Processing on Large Clusters,” In Vol. 29, No. 10, pp. 16-24, Oct. 2014. pp. 320-324, 2000. Vol. 74, pp. 421-436, 2014. K. Sequeira and M. Zaki, “Admit: anomaly-based data mining for intrusions,” Proceedings of ACM SIGKDD international conference on Knowledge discovery and data mining (KDD), pp. 386-395, 2002. R. Sekar, A. Gupta, J. Frullo, T. Shanbhag, A. Tiwari, H. Yang, and S. Zhou, “Specification-based anomaly detection: a new approach for detecting network intrusions.”, In M. M. Breunig, H. Kriegel, R.T. Ng, and J. Sander, “LOF: identifying density-based local outliers,” C. Cadar, P. Akritidis, M. Costa, J.-P. Martin, M. Castro, “Data Randomization,” E. Eskin, A. Arnold, M. Prerau, L. Portnoy, and S. Stolfo, “A geometric framework for unsupervised anomaly detection: Detecting intrusions in unlabeled data,” In “PaX Homepage,” 2000. [Online]. Available: http://pax.grsecurity.net/. [Accessed October 2012]. pp. 1-32, 2012. pp. 93-104, 2000. E. Cheng, L. Ma, A. Blaisse, et al., “Efficient Feature Extraction fromWide Area Motion Imagery by MapReduce in Hadoop,” Proc. SPIE, Vol. 9089, 2014. 2004. D. Chen, G. Chen, J. Cruz, L Haynes, et al., “A Markov Game Theoretic Data Fusion Approach for Cyber Situational Awareness,” Proc. of SPIE, Vol. 6571, 2007. H. Alipour, Y. Al-Nashif, S. Hariri, “IEEE 802.11 Anomaly Behavior Analysis”, submitted to Vol. 27, No. 9, Sept. 2012. Minds - Minnesota intrusion detection system V. S. Subashini, “A survey on security issues in service delivery models of cloud computing,” C. Modi, D. Patel, B. Borisaniya, A. Patel and M. Rajarajan, “A survey on security issues and solutions at different layers of Cloud computing,” (CAC ‘14), 2014. Procedia Computer Science, 2014. E Blasch, J Dezert, B Pannetier, “Overview of Dempster-Shafer and belief function tracking methods,”Proc. SPIE, Vol. 8745, 2013. 131-140, 2008. T.F. Lunt and R. Jagannathan, “A prototype real-time intrusion-detection expert system”, In Proceedings of the 2001. 2013. R. M. Dijkman, M. Dumas, and C. Ouyang. “Semantics and analysis of business process models in BPMN,” 45, 3, Article 40 (July 2013), 34 pages. D. Luo and J. Wang, “CC-VIT: Virtualization Intrusion Tolerance Based on Cloud Computing,” in 2nd Vol. 18, pp. 1999-2007, 2013. L. Ertöz, E. Eilertson, A. Lazarevic, P. Tan, V. Kumar, J. Srivastava Academic Press, pp. 201-279, 1987. Towards MapReduce Based Machine Learning Techniques for Processing Massive Network Threat Monitoring Data A. N. Steinberg, C.L. Bowman, G. Haith D. E. Denning, “An intrusion-detection model,” pages 265-274, New York, NY, USA,;1; 2002. S. Narain, “Moving Target Defense With Configuration Space Randomization,” [Accessed 30 Jan. 2013]. Available: https://www.ncsi.com/nsatc11/presentations/thursday/emerging_technologies/narain.pdf. G. Pék, L. Buttýan, and B. Bencsáth. A survey of security issues in hardware virtualization. E. Blasch, G. Seetharaman, and K. Reinhardt, “Dynamic Data Driven Applications System concept for Information Fusion,” E. Blasch, J. Nagy, A. Aved, W.M. Pottenger, M. Schneider, R. Hammoud, E.K. Jones, A. Basharat Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 2000. D. Goodin, “Webhost Hack Wipes Out Data for 100,000 Sites,” 8 June 2009. [Online]. Available: http://www.theregister.co.uk/2009/06/08/webhost_attack/. [Accessed 15 January 2013]. E. M. Knorr and R. T. Ng, “Algorithms for mining distance-based outliers in large datasets”, In Proc. 24th vol. 47, no. 18, pp. 47-66, 2012. M. Dunlop, S. Groat, W. Urbanski, R. Marchany and J. Tront, “MT6D:a moving target IPv6 defense,” in Game Theoretic Approach to Threat Prediction and Situation Awareness 2014. Adaptive Context Assessment and Context Management Intrusion Detection: Randomized Instruction Set Emulation to Disrupt Binary Code Injection Attacks P. Verissimo, A. Bessani and M. Pasin, ‘The TClouds Architecture: Open and Resilient Cloud-of-clouds Computing E. P. Blasch, D.A. Lambert, P. Valin July 2006. 2011. MIT Press, 2004. P.A. Porras and P.G. Neumann, “Emerald: Event monitoring enabling responses to anomalous live disturbances,” In L. Kaufman, “Data security in the world of cloud computing,” H. S. Javitz and A. Valdes Berkeley, 2005. vol. 7, no. 4, pp. 61-64, 2009. T. Shon and J. Moon, “A hybrid machine learning approach to network anomaly detection,” K. Kim and H. Welch, “Distributed Execution of Recovery Blocks:An Approach for Uniform Treatment of Hardware and Software Faults in Real-Time Applications,” K. Kim, “ROAFTS: A Middleware Architecture for Real-time Object-oriented Adaptive Fault Tolerance Support,” in IEEE CS 1998 High-Assurance Systems Engineering (HASE) Symp., Washington, D.C., 1998. Springer, 2011, pp. 29-39. A. Keromytis, G.R. S. Sethumadhavan, S. Stolfo, Y. Junfeng, A. Benameur, M. Dacier, M. Elder, D. Kienzle and A. Stavrou, “The MEERKATS Cloud Security Architecture,” in N. Ye and Q. Chen, “An anomaly detection technique based on a chi-square statistic for detecting intrusions into in-formation systems,” Quality and Reliability Engineering International, 17, 105-112, 2001. E. Barrantes, D. Ackley, S. Forrest N. Ye, “A markov chain model of temporal behavior for anomaly detection,” In M. Schmidt, L. Baumgartner, P. Graubner, D. Bock and B. Freisleben, “Malware Detection and Kernel Rootkit Prevention in Cloud Computing Environments,” in S. Ramaswamy, R. Rastogi, and K. Shim. “Efficie 10.1016/j.procs.2015.05.370_bib0105 10.1016/j.procs.2015.05.370_bib0425 10.1016/j.procs.2015.05.370_bib0305 10.1016/j.procs.2015.05.370_bib0190 10.1016/j.procs.2015.05.370_bib0070 10.1016/j.procs.2015.05.370_bib0390 10.1016/j.procs.2015.05.370_bib0270 10.1016/j.procs.2015.05.370_bib0150 10.1016/j.procs.2015.05.370_bib0030 10.1016/j.procs.2015.05.370_bib0195 10.1016/j.procs.2015.05.370_bib0075 10.1016/j.procs.2015.05.370_bib0350 10.1016/j.procs.2015.05.370_bib0230 10.1016/j.procs.2015.05.370_bib0395 10.1016/j.procs.2015.05.370_bib0110 10.1016/j.procs.2015.05.370_bib0275 10.1016/j.procs.2015.05.370_bib0155 10.1016/j.procs.2015.05.370_bib0430 10.1016/j.procs.2015.05.370_bib0035 10.1016/j.procs.2015.05.370_bib0310 10.1016/j.procs.2015.05.370_bib0355 10.1016/j.procs.2015.05.370_bib0235 10.1016/j.procs.2015.05.370_bib0115 10.1016/j.procs.2015.05.370_bib0435 10.1016/j.procs.2015.05.370_bib0315 10.1016/j.procs.2015.05.370_bib0080 10.1016/j.procs.2015.05.370_bib0280 10.1016/j.procs.2015.05.370_bib0160 10.1016/j.procs.2015.05.370_bib0040 10.1016/j.procs.2015.05.370_bib0085 10.1016/j.procs.2015.05.370_bib0360 10.1016/j.procs.2015.05.370_bib0240 10.1016/j.procs.2015.05.370_bib0120 10.1016/j.procs.2015.05.370_bib0285 10.1016/j.procs.2015.05.370_bib0165 10.1016/j.procs.2015.05.370_bib0045 10.1016/j.procs.2015.05.370_bib0320 10.1016/j.procs.2015.05.370_bib0200 10.1016/j.procs.2015.05.370_bib0365 10.1016/j.procs.2015.05.370_bib0245 10.1016/j.procs.2015.05.370_bib0125 10.1016/j.procs.2015.05.370_bib0400 10.1016/j.procs.2015.05.370_bib0005 10.1016/j.procs.2015.05.370_bib0325 10.1016/j.procs.2015.05.370_bib0205 10.1016/j.procs.2015.05.370_bib0405 10.1016/j.procs.2015.05.370_bib0090 10.1016/j.procs.2015.05.370_bib0290 10.1016/j.procs.2015.05.370_bib0170 10.1016/j.procs.2015.05.370_bib0050 10.1016/j.procs.2015.05.370_bib0095 10.1016/j.procs.2015.05.370_bib0370 10.1016/j.procs.2015.05.370_bib0250 10.1016/j.procs.2015.05.370_bib0130 10.1016/j.procs.2015.05.370_bib0295 10.1016/j.procs.2015.05.370_bib0010 10.1016/j.procs.2015.05.370_bib0175 10.1016/j.procs.2015.05.370_bib0055 10.1016/j.procs.2015.05.370_bib0330 10.1016/j.procs.2015.05.370_bib0210 10.1016/j.procs.2015.05.370_bib0375 10.1016/j.procs.2015.05.370_bib0255 10.1016/j.procs.2015.05.370_bib0135 10.1016/j.procs.2015.05.370_bib0410 10.1016/j.procs.2015.05.370_bib0015 10.1016/j.procs.2015.05.370_bib0335 10.1016/j.procs.2015.05.370_bib0215 10.1016/j.procs.2015.05.370_bib0415 10.1016/j.procs.2015.05.370_bib0180 10.1016/j.procs.2015.05.370_bib0060 10.1016/j.procs.2015.05.370_bib0380 10.1016/j.procs.2015.05.370_bib0260 10.1016/j.procs.2015.05.370_bib0140 10.1016/j.procs.2015.05.370_bib0020 10.1016/j.procs.2015.05.370_bib0185 10.1016/j.procs.2015.05.370_bib0065 10.1016/j.procs.2015.05.370_bib0340 10.1016/j.procs.2015.05.370_bib0220 10.1016/j.procs.2015.05.370_bib0385 10.1016/j.procs.2015.05.370_bib0100 10.1016/j.procs.2015.05.370_bib0265 10.1016/j.procs.2015.05.370_bib0145 10.1016/j.procs.2015.05.370_bib0420 10.1016/j.procs.2015.05.370_bib0025 10.1016/j.procs.2015.05.370_bib0300 10.1016/j.procs.2015.05.370_bib0345 10.1016/j.procs.2015.05.370_bib0225 |
| References_xml | – reference: : 131-140, 2008. – reference: ., “Intrusion Detection: Randomized Instruction Set Emulation to Disrupt Binary Code Injection Attacks,” – reference: R. Sekar, A. Gupta, J. Frullo, T. Shanbhag, A. Tiwari, H. Yang, and S. Zhou, “Specification-based anomaly detection: a new approach for detecting network intrusions.”, In – reference: . MIT Press, 2004. – reference: M. Schmidt, L. Baumgartner, P. Graubner, D. Bock and B. Freisleben, “Malware Detection and Kernel Rootkit Prevention in Cloud Computing Environments,” in – reference: , Vol. 18, pp. 1999-2007, 2013. – reference: E. Blasch, R. Breton, and P. Valin, “Using the C-OODA Model for CIMIC Analysis,” – reference: M. M. Breunig, H. Kriegel, R.T. Ng, and J. Sander, “LOF: identifying density-based local outliers,” – reference: G. Pék, L. Buttýan, and B. Bencsáth. A survey of security issues in hardware virtualization. – reference: . Kluwer Academics, 78-100, 2002. – reference: E. P. Blasch, D.A. Lambert, P. Valin, – reference: L. Ge, H. Zhang, G. Xu, W. Yu, – reference: . “A platform for event-driven agility of processes: A delivery context use-case.” – reference: ., “High Level Information Fusion (HLIF) Survey of Models, Issues, and Grand Challenges,” – reference: “Security as a Service,” Cloud Security Alliance, [Online]. Available: https://cloudsecurityalliance.org/research/secaas/. [Accessed January 2013]. – reference: , Vol. 74, pp. 421-436, 2014. – reference: , vol. 38, no. 5, pp. pp. 626-636, 1989. – reference: A. Tyrrell, “Recovery Blocks and Algorithm Based Fault tolerance,” in – reference: , 2001. – reference: , Academic Press, pp. 201-279, 1987. – reference: R. P. Viswanathan, Y. Al-Nashif, S. Hariri, “Application Attack Detection System (AADS): An Anomaly Based Behavior Analysis Approach,” – reference: , pp. 18-21, 1988. – reference: , 2012. – reference: R. Zhuang, S. Zhang, S.A. DeLoach, X. Ou and A. Singhal, “Simulation-based approaches to studying effectiveness of moving-target network defense,” in – reference: E Blasch, J Dezert, B Pannetier, “Overview of Dempster-Shafer and belief function tracking methods,”Proc. SPIE, Vol. 8745, 2013. – reference: “PaX Homepage,” 2000. [Online]. Available: http://pax.grsecurity.net/. [Accessed October 2012]. – reference: L. Ertöz, E. Eilertson, A. Lazarevic, P. Tan, V. Kumar, J. Srivastava, – reference: . pp. 93-104, 2000. – reference: ., “Context aided Video-to-Text Information Fusion,” – reference: ., “Adaptive Context Assessment and Context Management,” – reference: J. Feng, Y. Chen, D. Summerville, W. Ku, Z. Su, “Enhancing cloud storage security against roll-back attacks with a new fair multi-party non-repudiation protocol,” in – reference: P. Verissimo, A. Bessani and M. Pasin, ‘The TClouds Architecture: Open and Resilient Cloud-of-clouds Computing,” – reference: , Springer Publishing, 2013. – reference: K. Kim, “ROAFTS: A Middleware Architecture for Real-time Object-oriented Adaptive Fault Tolerance Support,” in IEEE CS 1998 High-Assurance Systems Engineering (HASE) Symp., Washington, D.C., 1998. – reference: 1999. – reference: Y. B. Al-Nashif, A. Kumar, S. Hariri, Y. Luo, F. Szidarovszky, and G. Qu: “Multi-Level Intrusion Detection System (ML-IDS),” – reference: S. Ramaswamy, R. Rastogi, and K. Shim. “Efficient algorithms for mining outliers from large datasets,” – reference: W. Toy, “Fault-Tolerant Computing,” in – reference: H. Alipour, Y. Al-Nashif, S. Hariri, “IEEE 802.11 Anomaly Behavior Analysis”, submitted to – reference: P. C. G. Costa, K.B. Laskey, – reference: (Amsterdam, Netherlands: 1999), 31(23-24):2435-2463, 1999. – reference: G. Vallee, C. Engelmann, A. Tikotekar, T. Naughton, K. Charoenpornwattana, C. Leangsuksun and S. Scott, “A Framework for Proactive Fault Tolerance,” – reference: , 2011. – reference: , 2003. – reference: C. C. Aggarwal and P. S. Yu, “Outlier detection for high dimensional data,” – reference: E. Blasch, “Context aided Sensor and Human-based Information Fusion” – reference: E. Blasch, A. Jøsang, J. Dezert, P.C. G. Costa, K.B. Laskey, A-L. Jousselme, “URREF Self-Confidence in Information Fusion Trust,” – reference: V. Paxson, “Bro: a system for detecting network intruders in real-time,” – reference: ., “Minds - Minnesota intrusion detection system,” – reference: B. Liu, E. Blasch, Y. Chen, A.J. Aved, – reference: M. Rosenblum and T. Garfinkel, “When virtual is harder than real: security challenges in virtual machine based computing environments,” in – reference: , July 2006. – reference: ., “Game Theoretic Approach to Threat Prediction and Situation Awareness,” – reference: 2(2/3): 171-190, 2013. – reference: ., “Towards Unbiased Evaluation of Uncertainty Reasoning: The URREF Ontology,” – reference: , (CAC ‘14), 2014. – reference: M. Abbasy and B. Shanmugam, “Enabling Data Hiding for Resource Sharing in Cloud Computing Environments Based on DNA Sequences,” in – reference: E. Blasch, K.B. Laskey, A-L. Joussselme, V. Dragos, P.C. G. Costa, and J. Dezert, “URREF Reliability versus Credibility in Information Fusion (STANAG 2511),” – reference: V. S. Subashini, “A survey on security issues in service delivery models of cloud computing,” – reference: , 177(18):3799-3821, 2007. – reference: , vol. 34, pp. 1-11, 2011. – reference: A. Keromytis, G.R. S. Sethumadhavan, S. Stolfo, Y. Junfeng, A. Benameur, M. Dacier, M. Elder, D. Kienzle and A. Stavrou, “The MEERKATS Cloud Security Architecture,” in – reference: L. Kaufman, “Data security in the world of cloud computing,” – reference: M. Roesch, “Snort - Lightweight Intrusion Detection for Networks,” – reference: . Springer Berlin Heidelberg, 2013. 681-690. – reference: E. Blasch, Y. Chen, G. Chen, D. Shen, and R. Kohler, “Information Fusion in a Cloud-Enabled Environment,” in Keesook Han, Baek-Young Choi, Sejun Song (Eds.), – reference: H. Alipour, Y. Al-Nashif, S. Hariri, “DNS Anomaly Behavior Analysis against Cyber Attacks”, submitted to – reference: , Vol. 27, No. 9, Sept. 2012. – reference: D. Anderson, T.F. Lunt, H. Javitz, A. Tamaru, and A. Valdes, “Detecting unusual program behavior using the statistical component of the next-generation intrusion detection expert system nides”, Technical Report – reference: , 50 (12), 1281-1294, 2008. – reference: 16 September 2009. [Accessed January 2013].]. Available: http://www.cyber.st.dhs.gov/docs/National_Cyber_Leap_Year_Summit_2009_Co-Chairs_Report.pdf. – reference: , pp. 353-365, 1997. – reference: D. L. Pipkin. – reference: D. E. Denning, “An intrusion-detection model,” – reference: , 13(2):222-232, 1987. – reference: G. Chen, D. Shen, C. Kwan, J. Cruz, – reference: K. Kim and H. Welch, “Distributed Execution of Recovery Blocks:An Approach for Uniform Treatment of Hardware and Software Faults in Real-Time Applications,” – reference: (ICCSN), pp.538-543, 2011. – reference: E. Cheng, L. Ma, A. Blaisse, et al., “Efficient Feature Extraction fromWide Area Motion Imagery by MapReduce in Hadoop,” Proc. SPIE, Vol. 9089, 2014. – reference: , pp. 427-438, 2000. – reference: P.A. Porras and P.G. Neumann, “Emerald: Event monitoring enabling responses to anomalous live disturbances,” In – reference: T.F. Lunt and R. Jagannathan, “A prototype real-time intrusion-detection expert system”, In Proceedings of the – reference: , 2008. – reference: . 45, 3, Article 40 (July 2013), 34 pages. – reference: E. Eskin, A. Arnold, M. Prerau, L. Portnoy, and S. Stolfo, “A geometric framework for unsupervised anomaly detection: Detecting intrusions in unlabeled data,” In – reference: C. Tunc, F. Fargo, Y. Al-Nashif, S. Hariri, J. Hughes, Autonomic Resilient Cloud Management (ARCM), – reference: , Technical Report, SRI International Menlo Park, California, 1994. – reference: , vol. 7, no. 4, pp. 61-64, 2009. – reference: , pp. 320-324, 2000. – reference: , “Towards MapReduce Based Machine Learning Techniques for Processing Massive Network Threat Monitoring Data,” – reference: D. Goodin, “Webhost Hack Wipes Out Data for 100,000 Sites,” 8 June 2009. [Online]. Available: http://www.theregister.co.uk/2009/06/08/webhost_attack/. [Accessed 15 January 2013]. – reference: M. Dunlop, S. Groat, W. Urbanski, R. Marchany and J. Tront, “MT6D:a moving target IPv6 defense,” in – reference: E. Blasch, J. Nagy, A. Aved, W.M. Pottenger, M. Schneider, R. Hammoud, E.K. Jones, A. Basharat, – reference: W. Li, Y. Badr, F. Biennier, “Service Farming: An Ad-hoc and QoS-aware Web Service Composition Approach,” Dans SAC 2013, Coimbra, Portugal, pp. 750-756, 2013. – reference: E. M. Knorr and R. T. Ng, “Algorithms for mining distance-based outliers in large datasets”, In Proc. 24th – reference: , 2010. – reference: , Springer, 2011, pp. 29-39. – reference: , vol. 47, no. 18, pp. 47-66, 2012. – reference: C. Modi, D. Patel, B. Borisaniya, A. Patel and M. Rajarajan, “A survey on security issues and solutions at different layers of Cloud computing,” – reference: E. Blasch, “Level 5 (User Refinement) issues supporting Information Fusion Management” – reference: R. Bhadauria and S. Sanyal, “Survey on Security Issues in Cloud Computing and Associated Mitigation Techniques,” – reference: E. Blasch, “Trust Metrics in Information Fusion,” Proc. SPIE, Vol. 9091, 2014. – reference: , 2013. – reference: , Berkeley, 2005. – reference: , Artech House, Norwood, MA, 2012. – reference: , Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 2000. – reference: D. Luo and J. Wang, “CC-VIT: Virtualization Intrusion Tolerance Based on Cloud Computing,” in 2nd – reference: D. Chen, G. Chen, J. Cruz, L Haynes, et al., “A Markov Game Theoretic Data Fusion Approach for Cyber Situational Awareness,” Proc. of SPIE, Vol. 6571, 2007. – reference: , Vol. 29, No. 10, pp. 16-24, 2014. – reference: N. Ye and Q. Chen, “An anomaly detection technique based on a chi-square statistic for detecting intrusions into in-formation systems,” Quality and Reliability Engineering International, 17, 105-112, 2001. – reference: E. Blasch, A. Steinberg, S. Das, J. Llinas, C.-Y. Chong, O. Kessler, E. Waltz, and F. White, “Revisiting the JDL model for information Exploitation,” – reference: K. Yamanishi, J. Takeuchi, G.J. Williams, and P. Milne, “On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms,” – reference: H. Zeng, “Research on Developing an Attack and Defense Lab Environment for Cross Site Scripting Education in Higher Vocational Colleges,” – reference: K. Scarfone and Peter Mell, Guide to Intrusion Detection and Prevention Systems (IDPS). Computer Security Resource Center (National Institute of Standards and Technology) (800-94), 2007, Retrieved 1 January 2010. – reference: S. Latif-Shabgahi, “An Integrated Voting Algorithm for Fault Tolerant Systems”, in – reference: ., “Information Fusion in a Cloud Computing Era: A Systems-Level Perspective,” – reference: , Vol. 2, No. 1, 1-14, June 2007. – reference: T. Shon and J. Moon, “A hybrid machine learning approach to network anomaly detection,” – reference: ), vol. 9, 2011. – reference: C. Cadar, P. Akritidis, M. Costa, J.-P. Martin, M. Castro, “Data Randomization,” – reference: , 2014. – reference: , 10(1-2):105-136, 2002. – reference: D. Jeffrey, G. Sanjay, “MapReduce: Simplified Data Processing on Large Clusters,” In – reference: A. N. Steinberg, C.L. Bowman, G. Haith, – reference: S. Narain, “Moving Target Defense With Configuration Space Randomization,” [Accessed 30 Jan. 2013]. Available: https://www.ncsi.com/nsatc11/presentations/thursday/emerging_technologies/narain.pdf. – reference: B. Liu, Y. Chen, A. Hadiks, – reference: K. Sequeira and M. Zaki, “Admit: anomaly-based data mining for intrusions,” Proceedings of ACM SIGKDD international conference on Knowledge discovery and data mining (KDD), pp. 386-395, 2002. – reference: H. S. Javitz and A. Valdes, – reference: S. Staniford, J.A. Hoagland, and J. M. McAlerney, “Practical automated detection of stealthy portscans,” – reference: L. Ge, W. Yu, D. Shen, G. Chen, K. Pham, et al., “Toward Effectiveness and Agility of Network Security Situational Awareness using Moving Target Defense (MTD),” Proc. SPIE, Vol. 9085, 2014. – reference: G. Dsouza, G. Rodríguez, Y.B. Al-Nashif, S. Hariri, “Building resilient cloud services using DDDAS and moving target defence,” – reference: E. P. Blasch, E. Bosse, and D. A. Lambert, – reference: E. Blasch, G. Seetharaman, and K. Reinhardt, “Dynamic Data Driven Applications System concept for Information Fusion,” – reference: . 2004. – reference: L. Peng, D. Lipinski, K. Mohseni, “Dynamic Data Driven Application System for plume estimation using UAVs,” – reference: , VLDB, pages 392-403, 24-27 1998. – reference: , CRC Press, Taylor & Francis Group, 2015. – reference: ., 1996. – reference: E. Blasch, Y Al-Nashif, and S. Hariri, “Static versus Dynamic Data Information Fusion analysis using DDDAS for Cyber Trust,” – reference: . – reference: A. Avizienis, “The N-Version Approach to fault Tolerant Software,” – reference: , Computer Science Laboratory, SRI International, 1995. – reference: , pages 265-274, New York, NY, USA,;1; 2002. – reference: M. S., Siddiqui, DVerma, “Cross site request forgery: A common web application weakness,” – reference: D. Evans, A. Nguyen-Tuong and J. Knight, “Effectiveness of Moving Target Defenses,” in – reference: E. Barrantes, D. Ackley, S. Forrest, – reference: R. M. Dijkman, M. Dumas, and C. Ouyang. “Semantics and analysis of business process models in BPMN,” – reference: A-M. Barthe-Delanoë, – reference: , pp. 1-32, 2012. – reference: , Procedia Computer Science, 2014. – reference: , Vol. 29, No. 10, pp. 16-24, Oct. 2014. – reference: N. Ye, “A markov chain model of temporal behavior for anomaly detection,” In – reference: , Vols. SE-11, no. 12, 1985. – ident: 10.1016/j.procs.2015.05.370_bib0105 doi: 10.1145/375663.375668 – ident: 10.1016/j.procs.2015.05.370_bib0180 doi: 10.1109/ICCSN.2011.6014783 – ident: 10.1016/j.procs.2015.05.370_bib0005 – ident: 10.1016/j.procs.2015.05.370_bib0030 – ident: 10.1016/j.procs.2015.05.370_bib0385 doi: 10.1016/j.procs.2014.05.117 – ident: 10.1016/j.procs.2015.05.370_bib0195 doi: 10.1109/CCNC.2011.5766528 – ident: 10.1016/j.procs.2015.05.370_bib0400 doi: 10.1109/MAES.2012.6366088 – ident: 10.1016/j.procs.2015.05.370_bib0285 doi: 10.1145/948143.948147 – ident: 10.1016/j.procs.2015.05.370_bib0210 doi: 10.1016/j.procs.2013.05.369 – ident: 10.1016/j.procs.2015.05.370_bib0165 doi: 10.5120/7292-0578 – ident: 10.1016/j.procs.2015.05.370_bib0185 doi: 10.1145/2480741.2480757 – ident: 10.1016/j.procs.2015.05.370_bib0265 doi: 10.1109/TSE.1985.231893 – ident: 10.1016/j.procs.2015.05.370_bib0080 doi: 10.1145/775047.775103 – ident: 10.1016/j.procs.2015.05.370_bib0090 doi: 10.1145/347090.347160 – ident: 10.1016/j.procs.2015.05.370_bib0230 doi: 10.1109/MILCOM.2011.6127486 – ident: 10.1016/j.procs.2015.05.370_bib0425 – ident: 10.1016/j.procs.2015.05.370_bib0050 – ident: 10.1016/j.procs.2015.05.370_bib0160 doi: 10.1016/j.jnca.2010.07.006 – ident: 10.1016/j.procs.2015.05.370_bib0435 – ident: 10.1016/j.procs.2015.05.370_bib0085 – ident: 10.1016/j.procs.2015.05.370_bib0360 – ident: 10.1016/j.procs.2015.05.370_bib0430 doi: 10.1117/12.2050255 – ident: 10.1016/j.procs.2015.05.370_bib0305 doi: 10.1109/ARES.2008.171 – ident: 10.1016/j.procs.2015.05.370_bib0035 doi: 10.1109/TSE.1987.232894 – ident: 10.1016/j.procs.2015.05.370_bib0010 – ident: 10.1016/j.procs.2015.05.370_bib0140 doi: 10.1109/ICIF.2006.301670 – ident: 10.1016/j.procs.2015.05.370_bib0200 doi: 10.1109/MSP.2009.87 – ident: 10.1016/j.procs.2015.05.370_bib0095 doi: 10.1002/qre.392 – ident: 10.1016/j.procs.2015.05.370_bib0110 doi: 10.1145/342009.335388 – ident: 10.1016/j.procs.2015.05.370_bib0310 doi: 10.1109/ICDCSW.2012.42 – ident: 10.1016/j.procs.2015.05.370_bib0390 doi: 10.1007/978-3-642-40543-3_71 – ident: 10.1016/j.procs.2015.05.370_bib0370 doi: 10.1016/j.infsof.2008.02.006 – ident: 10.1016/j.procs.2015.05.370_bib0255 doi: 10.1109/12.24266 – ident: 10.1016/j.procs.2015.05.370_bib0345 doi: 10.1109/MAES.2014.130115 – ident: 10.1016/j.procs.2015.05.370_bib0215 doi: 10.1109/MAES.2014.130115 – ident: 10.1016/j.procs.2015.05.370_bib0070 – ident: 10.1016/j.procs.2015.05.370_bib0410 doi: 10.1117/12.2016326 – ident: 10.1016/j.procs.2015.05.370_bib0130 doi: 10.1016/j.ins.2007.03.025 – ident: 10.1016/j.procs.2015.05.370_bib0150 doi: 10.1109/PDP.2011.45 – ident: 10.1016/j.procs.2015.05.370_bib0020 doi: 10.6028/NIST.SP.800-94 – ident: 10.1016/j.procs.2015.05.370_bib0060 doi: 10.1109/SECPRI.1988.8098 – ident: 10.1016/j.procs.2015.05.370_bib0325 doi: 10.1117/12.2054690 – ident: 10.1016/j.procs.2015.05.370_bib0155 – ident: 10.1016/j.procs.2015.05.370_bib0225 – ident: 10.1016/j.procs.2015.05.370_bib0250 – ident: 10.1016/j.procs.2015.05.370_bib0300 doi: 10.1109/DSNW.2012.6264686 – ident: 10.1016/j.procs.2015.05.370_bib0330 – ident: 10.1016/j.procs.2015.05.370_bib0365 doi: 10.1145/2480362.2480505 – ident: 10.1016/j.procs.2015.05.370_bib0100 doi: 10.1007/978-1-4615-0953-0_4 – ident: 10.1016/j.procs.2015.05.370_bib0145 – ident: 10.1016/j.procs.2015.05.370_bib0420 – ident: 10.1016/j.procs.2015.05.370_bib0260 doi: 10.1016/S0065-2458(08)60008-X – ident: 10.1016/j.procs.2015.05.370_bib0315 – ident: 10.1016/j.procs.2015.05.370_bib0125 doi: 10.1145/586110.586146 – ident: 10.1016/j.procs.2015.05.370_bib0240 – ident: 10.1016/j.procs.2015.05.370_bib0055 doi: 10.1109/AICCSA.2011.6126606 – ident: 10.1016/j.procs.2015.05.370_bib0045 – ident: 10.1016/j.procs.2015.05.370_bib0320 – ident: 10.1016/j.procs.2015.05.370_bib0355 doi: 10.1109/NAECON.2014.7045790 – ident: 10.1016/j.procs.2015.05.370_bib0025 doi: 10.1109/ICAC.2008.25 – ident: 10.1016/j.procs.2015.05.370_bib0175 doi: 10.1109/ICCIS.2013.515 – ident: 10.1016/j.procs.2015.05.370_bib0350 doi: 10.1007/s10846-013-9964-x – ident: 10.1016/j.procs.2015.05.370_bib0120 doi: 10.1145/335191.335437 – ident: 10.1016/j.procs.2015.05.370_bib0270 – ident: 10.1016/j.procs.2015.05.370_bib0335 doi: 10.1109/ICIF.2006.301581 – ident: 10.1016/j.procs.2015.05.370_bib0415 – ident: 10.1016/j.procs.2015.05.370_bib0190 doi: 10.1109/SERVICES.2011.45 – ident: 10.1016/j.procs.2015.05.370_bib0115 – ident: 10.1016/j.procs.2015.05.370_bib0295 doi: 10.1117/12.2050782 – ident: 10.1016/j.procs.2015.05.370_bib0375 doi: 10.1109/ICCAC.2014.35 – ident: 10.1016/j.procs.2015.05.370_bib0075 doi: 10.3233/JCS-2002-101-205 – ident: 10.1016/j.procs.2015.05.370_bib0170 doi: 10.1007/s11227-012-0831-5 – ident: 10.1016/j.procs.2015.05.370_bib0280 – ident: 10.1016/j.procs.2015.05.370_bib0245 – ident: 10.1016/j.procs.2015.05.370_bib0220 – ident: 10.1016/j.procs.2015.05.370_bib0235 – ident: 10.1016/j.procs.2015.05.370_bib0275 doi: 10.1007/978-1-4614-0977-9_2 – ident: 10.1016/j.procs.2015.05.370_bib0380 doi: 10.1504/IJCC.2013.055266 – ident: 10.1016/j.procs.2015.05.370_bib0395 doi: 10.1109/NAECON.2011.6183090 – ident: 10.1016/j.procs.2015.05.370_bib0040 – ident: 10.1016/j.procs.2015.05.370_bib0405 – ident: 10.1016/j.procs.2015.05.370_bib0015 doi: 10.1016/S1389-1286(99)00112-7 – ident: 10.1016/j.procs.2015.05.370_bib0065 – ident: 10.1016/j.procs.2015.05.370_bib0205 doi: 10.1007/978-1-4614-3296-8_4 – ident: 10.1016/j.procs.2015.05.370_bib0290 – ident: 10.1016/j.procs.2015.05.370_bib0340 – ident: 10.1016/j.procs.2015.05.370_bib0135 doi: 10.1117/12.720090 |
| SSID | ssj0000388917 |
| Score | 2.1394713 |
| Snippet | Future crisis management systems needresilient and trustworthy infrastructures to quickly develop reliable applications and processes, andensure end-to-end... In this paper, the multi-criteria decision making in which criteria are assumed to be dependent with each other is investigated. Choquet integral is employed... |
| SourceID | hal crossref elsevier |
| SourceType | Open Access Repository Enrichment Source Index Database Publisher |
| StartPage | 2623 |
| SubjectTerms | cloud computing Computation and Language Computer Science Cryptography and Security Data Structures and Algorithms Mathematical Software rDaaS resilience service-oriented computing Software Engineering trust and security Ubiquitous Computing Web |
| Title | Resilient and Trustworthy Dynamic Data-driven Application Systems (DDDAS) Services for Crisis Management Environments |
| URI | https://dx.doi.org/10.1016/j.procs.2015.05.370 https://hal.science/hal-01212583 |
| Volume | 51 |
| WOSCitedRecordID | wos000373939100268&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: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 1877-0509 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000388917 issn: 1877-0509 databaseCode: M~E dateStart: 20100101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9NAEF6lhQMX3ojy0gpxAIWVsnZs7x6jpqiHKEI0SL1Z612vcAmhStKoXPhZ_D5m9uEYChE9cLGSlb12Mp_npZlvCHk1LFKV1UoyJY1iw8pKJkxRM4v-OMQTtajc1JJJMZ2K01P5vtf7EXthNvNisRCXl_L8v4oa1kDY2Dp7DXG3m8ICfAahwxHEDsd_EvyHetXMm1g6PsOeClcH-K0_9tPnQdJrxcwS9Zz3Qn3aLrKXo9M5Ho9HJ5gxiLrElSMegkZoVp2Smf5Rp0-u6-e6_gOAnitZx6kR_WBqt5lT47AC2gZ82C9bRbhsfO_7CQQI7fJowqY49cmGS-BFtu1O4P_7eVag0z93sxi-gzOoXFEUDFlovEX6w1rQ04GYNija3LcpB6Od5J465opB8LmJMzRHGtnZeYZErakfVvIr_fZvZrEtVox1cGel26TETcpBVsIme-RGUkBIhiWj37e5PWTYkW7Yc_tDIuGVKy288jB_c4r2PsX0vnN3ZnfJ7RCn0JHH1z3Sqxf3yZ04A4QGk_CAXLRwowA32oEbDXCjHbjRDtxogBt97cD2hkaoUYAa9VCjW6jRLtQeko_vjmaHxyyM8mA6FcmaaZ4ra2qZ2CFEKJpnmnPwEuRAmIGpLK-kGuZWQ_iO4x2kKjII42vFpYHzuFHpI7K_-LqoHxOqMUKHuCXH2DkTQhU57KErzo22RWUPSBL_y1IHnnsctzIvdwjygLxtLzr3NC-7T8-jkMrw-ngPtATc7b7wJYi0vQVyux-PJiWuIblikol0w59c72Geklv4zecFn5H99fKifk5u6s26WS1fOGT-BL9NxDE |
| linkProvider | ISSN International Centre |
| 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=Resilient+and+Trustworthy+Dynamic+Data-driven+Application+Systems+%28DDDAS%29+Services+for+Crisis+Management+Environments&rft.jtitle=Procedia+computer+science&rft.au=Badr%2C+Youakim&rft.au=Hariri%2C+Salim&rft.au=AL-Nashif%2C+Youssif&rft.au=Blasch%2C+Erik&rft.date=2015&rft.issn=1877-0509&rft.eissn=1877-0509&rft.volume=51&rft.spage=2623&rft.epage=2637&rft_id=info:doi/10.1016%2Fj.procs.2015.05.370&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_procs_2015_05_370 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1877-0509&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1877-0509&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1877-0509&client=summon |