A Novel Approach to Multimedia Ontology Engineering for Automated Reasoning over Audiovisual LOD Datasets

Multimedia reasoning, which is suitable for, among others, multimedia content analysis and high-level video scene interpretation, relies on the formal and comprehensive conceptualization of the represented knowledge domain. However, most multimedia ontologies are not exhaustive in terms of role definitions, and do not incorporate complex role inclusions and role interdependencies. In fact, most multimedia ontologies do not have a role box at all, and implement only a basic subset of the available logical constructors. Consequently, their application in multimedia reasoning is limited. To address the above issues, VidOnt, the very first multimedia ontology with SROIQ(D) expressivity and a DL-safe ruleset has been introduced for next-generation multimedia reasoning. In contrast to the common practice, the formal grounding has been set in one of the most expressive description logics, and the ontology validated with industry-leading reasoners, namely HermiT and FaCT++. This paper also presents best practices for developing multimedia ontologies, based on my ontology engineering approach

A Unified Nanopublication Model for Effective and User-Friendly Access to the Elements of Scientific Publishing

Scientific publishing is the means by which we communicate and share scientific knowledge, but this process currently often lacks transparency and machine-interpretable representations. Scientific articles are published in long coarse-grained text with complicated structures, and they are optimized for human readers and not for automated means of organization and access. Peer reviewing is the main method of quality assessment, but these peer reviews are nowadays rarely published and their own complicated structure and linking to the respective articles is not accessible. In order to address these problems and to better align scientific publishing with the principles of the Web and Linked Data, we propose here an approach to use nanopublications as a unifying model to represent in a semantic way the elements of publications, their assessments, as well as the involved processes, actors, and provenance in general. To evaluate our approach, we present a dataset of 627 nanopublications representing an interlinked network of the elements of articles (such as individual paragraphs) and their reviews (such as individual review comments). Focusing on the specific scenario of editors performing a meta-review, we introduce seven competency questions and show how they can be executed as SPARQL queries. We then present a prototype of a user interface for that scenario that shows different views on the set of review comments provided for a given manuscript, and we show in a user study that editors find the interface useful to answer their competency questions. In summary, we demonstrate that a unified and semantic publication model based on nanopublications can make scientific communication more effective and user-friendly

Knowledge representation to support partially automated honeypot analysis based on Wireshark packet capture files

The automation of packet analysis, even partially, is very much desired, because packet analysis is time-consuming and requires technical knowledge and skills. This paper presents the Packet Analysis Ontology (PAO), a novel OWL ontology that covers the terminology of packet analysis, including concepts and properties, as well as their restrictions, to be used for knowledge representation and automated reasoning in this field. This ontology defines protocols and ports required for capturing the semantics of network activities, many of which are not defined in any other ontology

Conceptual Characterization of Cybersecurity Ontologies

[EN] Cybersecurity is known as the practice of protecting systems from digital attacks. Organizations are seeking efficient solutions for the management and protection of their assets. It is a complex issue, especially for great enterprises, because it requires an interdisciplinary approach. The kinds of problems enterprises must deal with and this domain complexity induces misinterpretations and misunderstandings about the concepts and relations in question. This article focus on dealing with Cybersecurity from an ontological perspective. The first contribution is a search of previously existing works that have defined Cybersecurity Ontologies. The paper describes the process to search these works. The second contribution of the paper is the definition of characteristics to classify the papers of Cybersecurity Ontologies previously found. This classification aims to compare the previous works with the same criteria. The third contribution of the paper is the analysis of the results of the comparison of previous works in the field of Cybersecurity Ontologies. Moreover, the paper discusses the gaps found and proposes good practice actions in Ontology Engineering for this domain. The article ends with some next steps proposed in the evolution towards a pragmatic and iterative solution that meets the needs of organizations.Martins, BF.; Serrano-Gil, LJ.; Reyes Román, JF.; Panach, JI.; Pastor López, O.; Rochwerger, B. (2020). Conceptual Characterization of Cybersecurity Ontologies. Springer. 323-338. https://doi.org/10.1007/978-3-030-63479-7_22S323338Baader, F., et al.: The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, Cambridge (2003)Ben-Asher, N., Oltramari, A., Erbacher, R.F., Gonzalez, C.: Ontology-based adaptive systems of cyber defense. In: STIDS. pp. 34–41 (2015)Bergner, S., Lechner, U.: Cybersecurity ontology for critical infrastructures. In: KEOD. pp. 80–85 (2017)Bizer, C., Heath, T., Berners-Lee, T.: Linked data:the story so far. In: Semantic Services, Interoperability and Web Applications: Emerging Concepts. pp. 205–227. IGI Global (2011)Blanco, C., Lasheras, J., Valencia-García, R., Fernández-Medina, E., Toval, A., Piattini, M.: A systematic review and comparison of security ontologies. In: 3th International Conference on Availability, Reliability and Security. pp. 813–820. IEEE (2008)Booth, H., Turner, C.: Vulnerability description ontology (vdo). A Framework for Characterizing Vulnerabilities, NIST (2016)Borgo, S., Masolo, C.: Ontological foundations of dolce. In: Poli, R., Healy, M., Kameas, A., (eds.) Theory and Applications of Ontology: Computer Applications. Springer, Dordrecht (2010) https://doi.org/10.1007/978-90-481-8847-5_13Degen, W., Heller, B., Herre, H., Smith, B.: Gol: toward an axiomatized upper-level ontology. In: Proceedings of the International Conference on Formal Ontology in Information Systems-Volume. pp. 34–46 (2001)Dietz, M., Putz, B., Pernul, G.: A distributed ledger approach to digital twin secure data sharing. In: IFIP Annual Conference on Data and Applications Security and Privacy. pp. 281–300. Springer (2019)https://doi.org/10.1007/978-3-030-22479-0_15Elnagdy, S.A., Qiu, M., Gai, K.: Cyber incident classifications using ontology-based knowledge representation for cybersecurity insurance in financial industry. In: 2016 IEEE 3rd International Conference on Cyber Security and Cloud Computing (CSCloud). pp. 301–306. IEEE (2016)Falbo, R.D.A.: SABiO: Systematic Approach for Building Ontologies. In: Proceedings of the 1st Joint Workshop ONTO.COM/ODISE on Ontologies in Conceptual Modeling and Information Systems Engineering (2014)Fernández-López, M., Gómez-Pérez, A., Juristo, N.: Methontology: from ontological art towards ontological engineering. In: Proceedings of the Ontological Engineering AAAI-97 Spring Symposium Series. American Association for Artificial Intelligence (1997)Finkel, J.R., Grenager, T., Manning, C.: Incorporating non-local information into information extraction systems by gibbs sampling. In: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics. ACL 2005, p. 363–370. USA (2005)Giaretta, P., Guarino, N.: Ontologies and knowledge bases towards a terminological clarification. Towards very large knowledge bases: knowledge building & knowledge sharing 25, 32 (1995)Grégio, A., Bonacin, R., Nabuco, O., Afonso, V.M., De Geus, P.L., Jino, M.: Ontology for malware behavior: a core model proposal. In: 2014 IEEE 23rd International WETICE Conference. pp. 453–458. IEEE (2014)Guarino, N.: Formal ontology in information systems. In: Proceedings of the 1st International Conference. pp. 6–8. IOS Press, Trento, Italy (1998)Guarino, N.: The ontological level. Philosophy and the Cognitive Sciences (1994)Guizzardi, G.: The role of foundational ontology for conceptual modeling and domain ontology representation, keynote paper. In: 7th International Baltic Conference on Databases and Information Systems (DB&IS), Vilnius, IEEE Press (2006)Guizzardi, G.: Ontological Foundations for Structural Conceptual Models. CTIT, Centre for Telematics and Information Technology (2005)Guizzardi, G.: On ontology, ontologies, conceptualizations, modeling languages, and (meta) models. Front. Artif. Intell. Appl. 155, 18 (2007)Guizzardi, G., Ferreira Pires, L., van Sinderen, M.: An ontology-based approach for evaluating the domain appropriateness and comprehensibility appropriateness of modeling languages. In: Briand, L., Williams, C. (eds.) MODELS 2005. LNCS, vol. 3713, pp. 691–705. Springer, Heidelberg (2005). https://doi.org/10.1007/11557432_51Hadar, E., Hassanzadeh, A.: Big data analytics on cyber attack graphs for prioritizing agile security requirements. In: 2019 IEEE 27th International Requirements Engineering Conference (RE). pp. 330–339. IEEE (2019)Herre, H.: General formal ontology (gfo): a foundational ontology for conceptual modelling. In: Poli, R., Healy, M., Kameas, A. (eds) Theory and Applications of Ontology: Computer Applications. Springer, Dordrecht (2010) https://doi.org/10.1007/978-90-481-8847-5_14Horrocks, I., et al.: Daml+oil: a description logic for the semantic web. IEEE Data Eng. Bull. 25(1), 4–9 (2002)Iannacone, M., et al.: Developing an ontology for cyber security knowledge graphs. In: 10th Annual Cyber and Information Security Research Conference (2015)Jia, Y., Qi, Y., Shang, H., Jiang, R., Li, A.: A practical approach to constructing a knowledge graph for cybersecurity. Engineering 4(1), 53–60 (2018)Kang, D., Lee, J., Choi, S., Kim, K.: An ontology-based enterprise architecture. Expert Syst. Appl. 37(2), 1456–1464 (2010)Keil, J.M., Schindler, S.: Comparison and evaluation of ontologies for units of measurement. Semantic Web 10(1), 33–51 (2019)Mascardi, V., Cordì, V., Rosso, P.: A comparison of upper ontologies. In: Woa. vol. 2007, pp. 55–64 (2007)Mozzaquatro, B.A., Agostinho, C., Goncalves, D., Martins, J., Jardim-Goncalves, R.: An ontology-based cybersecurity framework for the internet of things. Sensors 18(9), 3053 (2018)Mundie, D.A., Ruefle, R., Dorofee, A.J., Perl, S.J., McCloud, J., Collins, M.: An incident management ontology. In: STIDS. pp. 62–71 (2014)Narayanan, S., Ganesan, A., Joshi, K., Oates, T., Joshi, A., Finin, T.: Cognitive techniques for early detection of cybersecurity events. arXiv preprint arXiv:1808.00116 (2018)Obrst, L., Chase, P., Markeloff, R.: Developing an ontology of the cyber security domain. In: STIDS. pp. 49–56 (2012)Oltramari, A., Cranor, L.F., Walls, R.J., McDaniel, P.: Computational ontology of network operations. In: MILCOM 2015–2015 IEEE Military Communications Conference. pp. 318–323. IEEE (2015)Oltramari, A., Cranor, L.F., Walls, R.J., McDaniel, P.D.: Building an ontology of cyber security. In: STIDS. pp. 54–61. Citeseer (2014)Oltramari, A., Henshel, D.S., Cains, M., Hoffman, B.: Towards a human factors ontology for cyber security. In: STIDS. pp. 26–33 (2015)Oltramari, A., Vetere, G., Lenzerini, M., Gangemi, A., Guarino, N.: Senso comune. In: LREC (2010)Onwubiko, C.: Cocoa: An ontology for cybersecurity operations centre analysis process. In: 2018 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA). pp. 1–8 (2018)Ou, X., Govindavajhala, S., Appel, A.W.: Mulval: A logic-based network security analyzer. In: USENIX security symposium. vol. 8, pp. 113–128. Baltimore (2005)Parmelee, M.C.: Toward an ontology architecture for cyber-security standards. STIDS 713, 116–123 (2010)Pipa, A.M.C.: OWL ontology quality assessment and optimization in the cybersecurity domain. Ph.D. thesis, Instituto Universitário de Lisboa (2018)Rose, S., Engel, D., Cramer, N., Cowley, W.: Automatic keyword extraction from individual documents. In: Berry, M.W., Kogan, J. (eds.) Text Mining. Applications and Theory, pp. 1–20. John Wiley and Sons, Ltd (2010)Rutkowski, A., et al.: Cybex: The cybersecurity information exchange framework (x.1500). SIGCOMM Comput. Commun. Rev. 40(5), 59–64 (2010)Sikos, L.F.: OWL ontologies in cybersecurity: conceptual modeling of cyber-knowledge. In: Sikos, L.F. (ed.) AI in Cybersecurity. ISRL, vol. 151, pp. 1–17. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-98842-9_1Singhal, A., Ou, X.: Security risk analysis of enterprise networks using probabilistic attack graphs. Network Security Metrics, pp. 53–73. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-66505-4_3Syed, R., Zhong, H.: Cybersecurity vulnerability management: An ontology-based conceptual model (2018)Syed, Z., Padia, A., Finin, T., Mathews, L., Joshi, A.: UCO: A unified cybersecurity ontology. In: Workshops at the Thirtieth AAAI Conference on Artificial Intelligence (2016)Takahashi, T., Kadobayashi, Y.: Reference ontology for cybersecurity operational information. Comput. J. 58(10), 2297–2312 (2015)Takahashi, T., Fujiwara, H., Kadobayashi, Y.: Building ontology of cybersecurity operational information. In: Proceedings of the Sixth Annual Workshop on Cyber Security and Information intelligence Research. pp. 1–4 (2010)Takahashi, T., Kadobayashi, Y.: Cybersecurity information exchange techniques: Cybersecurity information ontology and cybex. J. National Instit. Inf. Commun. Technol. 58(3/4), 127–135 (2011)Takahashi, T., Kadobayashi, Y., Fujiwara, H.: Ontological approach toward cybersecurity in cloud computing. In: Proceedings of the 3rd International Conference on Security of Information and Networks. pp. 100–109 (2010)Undercofer, J., Joshi, A., Finin, T., Pinkston, J., et al.: A target-centric ontology for intrusion detection. In: Workshop on Ontologies in Distributed Systems, held at The 18th International Joint Conference on Artificial Intelligence (2003)Wand, Y., Weber, R.: On the deep structure of information systems. Inf. Syst. J. 5(3), 203–223 (1995)Wang, J.Z., Ali, F.: An efficient ontology comparison tool for semantic web applications. In: The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2005). pp. 372–378. IEEE (2005)Wang, J.A., Guo, M.: Ovm: an ontology for vulnerability management. In: 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies. pp. 1–4 (2009)Wieringa, R.: Design Science Methodology for Information Systems and Software Engineering. Springer, Berlin (2014)Zuanelli, E.: The cybersecurity ontology platform: the poc solution. e-AGE2017 p. 1 (2017

A Unified Nanopublication Model for Effective and User-Friendly Access to the Elements of Scientific Publishing

Scientific publishing is the means by which we communicate and share scientific knowledge, but this process currently often lacks transparency and machine-interpretable representations. Scientific articles are published in long coarse-grained text with complicated structures, and they are optimized for human readers and not for automated means of organization and access. Peer reviewing is the main method of quality assessment, but these peer reviews are nowadays rarely published and their own complicated structure and linking to the respective articles are not accessible. In order to address these problems and to better align scientific publishing with the principles of the Web and Linked Data, we propose here an approach to use nanopublications as a unifying model to represent in a semantic way the elements of publications, their assessments, as well as the involved processes, actors, and provenance in general. To evaluate our approach, we present a dataset of 627 nanopublications representing an interlinked network of the elements of articles (such as individual paragraphs) and their reviews (such as individual review comments). Focusing on the specific scenario of editors performing a meta-review, we introduce seven competency questions and show how they can be executed as SPARQL queries. We then present a prototype of a user interface for that scenario that shows different views on the set of review comments provided for a given manuscript, and we show in a user study that editors find the interface useful to answer their competency questions. In summary, we demonstrate that a unified and semantic publication model based on nanopublications can make scientific communication more effective and user-friendly