Evaluation of Tools and Techniques for the Generation of Warning Alerts: A Survey Paper

Authors

  • Abid Ghaffar Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, P.O Box 10, 50728 Kuala Lumpur, Malaysia and Department of Computer Science, Foundation Year Program, Umm Alqura University, Makkah, Saudi Arabia.
  • Mohamed Ridza Wahiddin
  • Mohamad Fauzan Noordin
  • Asadullah Shaikh

DOI:

https://doi.org/10.14738/tmlai.32.1078

Keywords:

Brahms Model, Human behaviour Modelling, Cognitive Science, Security and Privacy, Warning Dialogues, Mental Model Approach

Abstract

Quality assurance is a key factor for the improvement of an organisational behaviour. It is quite challenging to enhance an organisational performance without realising internal errors and mistakes done by its employees. We have also experienced that most of the security solutions are unsuccessful wherever human behaviour is involved. Organisations sometimes pay huge cost for its survival especially when human error is untraceable and misleading. Online survey has been conducted from different professionals serving at different positions in different organisations. Variety of multi-agent system tools (MAS) is available in the market for modelling and simulation of human behaviour. Brahms modelling and simulation tool has been selected among different multi-agent system tools due to its distinguished features to detect human errors in an organisation which supports warning alert generation system.

Author Biography

Abid Ghaffar, Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, P.O Box 10, 50728 Kuala Lumpur, Malaysia and Department of Computer Science, Foundation Year Program, Umm Alqura University, Makkah, Saudi Arabia.

Abid Ghaffar is currently a Ph.D student in the Department of Computer Science, Kulliyah of Information and Communication Technology, International Islamic University, Malaysia.  He is also a faculty member at the same time in the Department of Computer Science as lecturer, Foundation Year Program, Umm Al-qura University, Makkah, Saudi Arabia. He has completed his M.Sc degree in Computer Science from Gomal University, D.I. Khan, N.W.F.P., Pakistan, B.Sc from Punjab University, Pakistan. He has more than fifteen years teaching experience including two and a half year industrial experience.

 

References

. El Fallah Seghrouchni, A., Dix, J., Dastani, M., & Bordini, R. H. (2009). Multi-Agent Programming. Multi-Agent Programming :: Languages, Tools and Applications, ISBN 978-0-387-89298-6. Springer-Verlag US, 2009, 1.

. AOS Limited. An Agent Infrastructure for Providing the Decision-Making Capability Required

for Autonomous Systems, 2013.

. Blum, C., & Li, X. (2008). Swarm intelligence in optimization (pp. 43-85). Springer Berlin Heidelberg.

. Bordini, R. H., Braubach, L., Dastani, M., El Fallah-Seghrouchni, A., Gomez-Sanz, J. J., Leite, J., ... & Ricci, A. (2006). A survey of programming languages and platforms for multi-agent systems. Informatica (Slovenia), 30(1), 33-44.

. Dix, J., & Seghrouchni, A. E. F. (2005). Multi-Agent Programming. R. H. Bordini, & M. Dastani (Eds.). Springer Science+ Business Media, Incorporated.

. Bordini, R. H., Hübner, J. F., & Wooldridge, M. (2007). Programming multi-agent systems in AgentSpeak using Jason (Vol. 8). John Wiley & Sons.

. Bravo-Lillo, C., Cranor, L. F., Downs, J. S., & Komanduri, S. (2011). Bridging the gap in computer security warnings: A mental model approach. IEEE Security & Privacy, 9(2), 0018-26.

. Caire, F. B. G., Poggi, A., & Rimassa, G. (2003). JADE. A white paper.

. Dastani, M., Hbner, J. F., & Logan, B. (2013). Programming Multi-Agent Systems: 10th International Workshop, ProMAS 2012, Valencia, Spain, June 5, 2012, Revised Selected Papers. Springer Publishing Company, Incorporated.

. Pereira, F. C., & Shieber, S. M. (2002). Prolog and natural-language analysis. Microtome Publishing.

. Fernando Koch. 3APLM Platform for Deliberative Agents in Mobile Devices, 2005.

. Ghaffar, A., Wahiddin, M. R., & Shaikh, A. (2013). Computer Assisted Alerts Using Mental Model Approach for Customer Service Improvement. Journal of Software Engineering and Applications, 6(05), 21.

. Huber, M. J. (1999, April). JAM: A BDI-theoretic mobile agent architecture. In Proceedings of the third annual conference on Autonomous Agents (pp. 236-243). ACM.

. Borst, J. P., & Anderson, J. R. (2014). Using the ACT-R Cognitive Architecture in combination with fMRI data. An Introduction to Model-Based Cognitive Neuroscience. Springer, New York.

. Jevtić, A. (2011). Swarm intelligence: novel tools for optimization, feature extraction, and multi-agent system modeling (Doctoral dissertation, Telecomunicacion).

. Laird, J. (2012). The Soar cognitive architecture. MIT Press.

. J. Preece. A Brief History of Human Behaviour and How to Become an Enlightened Global Citizen (Smashwords Edition, 2013).

. Bratko. Prolog Programming For Artificial Intelligence, Addison-Wesley, 1986.

. Macal, C. M., & North, M. J. (2009, December). Agent-based modeling and simulation. In Winter simulation conference (pp. 86-98). Winter Simulation Conference.

. North, M. J., Collier, N. T., & Vos, J. R. (2006). Experiences creating three implementations of the repast agent modeling toolkit. ACM Transactions on Modeling and Computer Simulation (TOMACS), 16(1), 1-25.

. Panigrahi, B. K., Shi, Y., & Lim, M. H. (2011). Handbook of swarm intelligence: concepts, principles and applications (Vol. 8). Springer Science & Business Media.

. Robbins, S., Judge, T. A., Millett, B., & Boyle, M. (2013). Organisational behaviour. Pearson Higher Education AU.

. Seah, C., Sierhuis, M., and J. C., Clancey. Multi-agent modeling and simulation approach for design and analysis of MER Mission Operations. In Proceedings of 2005 International conference on Human-Computer interface advances for modeling and simulation (SIMCHI 2005), pages 73–78. Citeseer, 2005.

. Sierhuis, M., Modeling and simulating work practice: BRAHMS: A multiagent modeling and simulation language for work system analysis and design. Ph.D Thesis, UvA-DARE, University of Amsterdam (UvA) 2001.

. Sierhuis, M. (2013). Multi-agent activity modeling with the Brahms environment. In Theory, Practice, and Applications of Rules on the Web, pages 34–35. Springer Berlin Heidelberg.

. Sierhuis, M., & Clancey, W. J. (2002). Modeling and simulating practices, a work method for work systems design. Intelligent Systems, IEEE, 17(5), 32-41.

. Sierhuis, M., Clancey, W. J., & Van Hoof, R. J. (2007). Brahms: a multi-agent modelling environment for simulating work processes and practices.International Journal of Simulation and Process Modelling, 3(3), 134-152.

. Tisue, S., & Wilensky, U. (2004, May). Netlogo: A simple environment for modeling complexity. In International conference on complex systems (pp. 16-21).

. Uri Wilensky. NetLogo User Manual, version 5.0.5, 2013.

. M. F. Noordin. (2013). ICT and Islam, IIUM Press.

. Ghaffar, A., Wahiddin, M. R., Noordin, M. F., & Shaikh, A. (2015). A Framework to Improve Customer Service Using Brahms Model. IJEIR, 4(1), 99-106.

. Ghaffar, A., Wahiddin, M. R., Shaikh, A., and Ahmad, A. (11-13 Feb. 2015). Generating Alerts using context aware security and Brahms Model for customer service improvement. Accepted paper in International Multi-Topic Conference, Mehran University, Jamshoro, Pakistan. IMTIC’15.

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Published

2015-05-02

How to Cite

Ghaffar, A., Ridza Wahiddin, M., Fauzan Noordin, M., & Shaikh, A. (2015). Evaluation of Tools and Techniques for the Generation of Warning Alerts: A Survey Paper. Transactions on Engineering and Computing Sciences, 3(2), 10. https://doi.org/10.14738/tmlai.32.1078