Dr Hatem Ahriz's Outputs (27)

Detection of false command and response injection attacks for cyber physical systems security and resilience. (2020)
Presentation / Conference Contribution
EKE, H., PETROVSKI, A. and AHRIZ, H. 2020. Detection of false command and response injection attacks for cyber physical systems security and resilience. In Proceedings of the 13th Security of information and networks international conference 2020 (SIN 2020), 4-7 November 2020, Merkez, Turkey. New York: ACM [online], article number 10, pages 1-8. Available from: https://doi.org/10.1145/3433174.3433615

The operational cyber-physical system (CPS) state, safety and resource availability is impacted by the safety and security measures in place. This paper focused on i) command injection (CI) attack that alters the system behaviour through injection of... Read More about Detection of false command and response injection attacks for cyber physical systems security and resilience..

Predicting permeability based on core analysis. (2020)
Presentation / Conference Contribution
KONTOPOULOS, H., AHRIZ, H., ELYAN, E. and ARNOLD, R. 2020. Predicting permeability based on core analysis. In Iliadis, L., Angelov, P.P., Jayne, C. and Pimenidis, E. (eds.) Proceedings of the 21st Engineering applications of neural networks conference 2020 (EANN 2020); proceedings of the EANN 2020, 5-7 June 2020, Halkidiki, Greece. Proceedings of the International Neural Networks Society, vol 2. Cham: Springer [online], pages 143-154. Available from: https://doi.org/10.1007/978-3-030-48791-1_10

Knowledge of permeability, a measure of the ability of rocks to allow fluids to flow through them, is essential for building accurate models of oil and gas reservoirs. Permeability is best measured in the laboratory using special core analysis (SCAL)... Read More about Predicting permeability based on core analysis..

The use of machine learning algorithms for detecting advanced persistent threats. (2019)
Presentation / Conference Contribution
EKE, H.N., PETROVSKI, A. and AHRIZ, H. 2019. The use of machine learning algorithms for detecting advanced persistent threats. In Makarevich, O., Babenko, L., Anikeev, M., Elci, A. and Shahriar, H. (eds.). Proceedings of the 12th Security of information and networks international conference 2019 (SIN 2019), 12-15 September 2019, Sochi, Russia. New York: ACM [online], article No. 5. Available from: https://doi.org/10.1145/3357613.3357618

Advanced Persistent Threats (APTs) have been a major challenge in securing both Information Technology (IT) and Operational Technology (OT) systems. Due to their capability to navigates around defenses and to evade detection for a prolonged period of... Read More about The use of machine learning algorithms for detecting advanced persistent threats..

Dynamic agent prioritisation with penalties in distributed local search. (2013)
Presentation / Conference Contribution
SAMBO-MAGAJI, A., ARANA, I. and AHRIZ, H. 2013. Dynamic agent prioritisation with penalties in distributed local search. In Filipe, J. and Fred, A. (eds.) Proceedings of the 5th International conference on agents and artificial intelligence (ICAART 2013), 15-18 February 2013, Barcelona, Spain. Setúbal: Science and Technology Publications [online], volume 1, pages 276-281. Available from: https://doi.org/10.5220/0004259202760281

Distributed Constraint Satisfaction Problems (DisCSPs) solving techniques solve problems which are distributed over a number of agents.The distribution of the problem is required due to privacy, security or cost issues and, therefore centralised prob... Read More about Dynamic agent prioritisation with penalties in distributed local search..

Plan recommendation for well engineering. (2011)
Presentation / Conference Contribution
THOMSON, R., MASSIE, S., CRAW, S., AHRIZ, H. and MILLS, I. 2011. Plan recommendation for well engineering. In Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K. and Ali, M. (eds.) Modern approaches in applied intelligence: proceedings of the 24th International conference on industrial, engineering and other applications of applied intelligent systems (IEA/AIE 2011), 28 June - 1 July 2011, Syracuse, USA. Lecture notes in computer science, 6704. Berlin: Springer [online], part II, pages 436-445. Available from: https://doi.org/10.1007/978-3-642-21827-9_45

Good project planning provides the basis for successful offshore well drilling projects. In this domain, planning occurs in two phases: an onshore phase develops a project plan; and an offshore phase implements the plan and tracks progress. The Perfo... Read More about Plan recommendation for well engineering..

Multi-HDCS: solving DisCSPs with complex local problems cooperatively. (2010)
Presentation / Conference Contribution
LEE, D., ARANA, I., AHRIZ, H. and HUI, K. 2009. Multi-HDCS: solving DisCSPs with complex local problems cooperatively. In Huang, X.J., Ghorbani, A.A., Hacid, M.-S. and Yamaguchi, T. (eds.) Proceedings of the 2010 IEEE/WIC/ACM international conference on intelligent agent technology (IAT 2010), co-located with the 2010 IEEE/WIC/ACM international conference on web intelligence (WI 2010), and the joint conference workshops (WI-IAT Workshops 2010), 31 August - 3 September 2010, Toronto, Canada. Los Alamitos: IEEE Computer Society [online], volume 2, article number 5614767, pages 295-302. Available from: https://doi.org/10.1109/WI-IAT.2010.141

We propose Multi-HDCS, a new hybrid approach for solving Distributed CSPs with complex local problems. In Multi-HDCS, each agent concurrently: (i) runs a centralised systematic search for its complex local problem; (ii) participates in a distributed... Read More about Multi-HDCS: solving DisCSPs with complex local problems cooperatively..

A hybrid approach to solving coarse-grained DisCSPs. (2009)
Presentation / Conference Contribution
LEE, D., ARANA, I., AHRIZ, H. and HUI, K.-Y. 2009. A hybrid approach to solving coarse-grained DisCSPs. In Proceedings of the 8th International conference on autonomous agents and multiagent systems (AAMAS 2009), 10-15 May 2009, Budapest, Hungary. Richland, South Carolina: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) [online], pages 1235-1236. Available from: http://www.aamas-conference.org/Proceedings/aamas09/pdf/02_Extended_Abstract/C_SP_0555.pdf

A coarse-grained Distributed Constraint Satisfaction Problem (DisCSP) consists of several loosely connected constraint satisfaction subproblems, each assigned to an individual agent. We present Multi-Hyb, a two-phase concurrent hybrid approach for so... Read More about A hybrid approach to solving coarse-grained DisCSPs..

Multi-Hyb: a hybrid algorithm for solving DisCSPs with complex local problems. (2009)
Presentation / Conference Contribution
LEE, D., ARANA, I., AHRIZ, H. and HUI, K.-Y. 2009. Multi-Hyb: a hybrid algorithm for solving DisCSPs with complex local problems. In Baeza-Yates, R., Lang, J., Mitra, S., Parsons, S. and Pasi, G. (eds.) Proceedings of the 2009 IEEE/WIC/ACM international conference on intelligent agent technology (IAT 2009), co-located with the 2009 IEEE/WIC/ACM international conference on web intelligence (WI 2009), and the joint conference workshops (WI-IAT Workshops 2009), 15-18 September 2009, Milan, Italy. Los Alamitos: IEEE Computer Society [online], volume 2, article number 5284811, pages 379-382. Available from: https://doi.org/10.1109/WI-IAT.2009.181

A coarse-grained Distributed Constraint Satisfaction Problem (DisCSP) is a constraint problem where several agents, each responsible for solving one part (a complex local problem), cooperate to determine an overall solution. Thus, agents solve the ov... Read More about Multi-Hyb: a hybrid algorithm for solving DisCSPs with complex local problems..

DynABT: dynamic asynchronous backtracking for dynamic DisCSPs. (2008)
Presentation / Conference Contribution
OMOMOWO, B., ARANA, I. and AHRIZ, H. 2008. DynABT: dynamic asynchronous backtracking for dynamic DisCSPs. In Dochev, D., Pistore, M. and Traverso, P. (eds.) Proceedings of the 13th International conference on artificial intelligence: methodology, systems and applications (AIMSA 2008), 4-6 September 2008, Varna, Bulgaria. Lecture notes in computer science, 5253. Berlin: Springer [online], pages 285-296. Available from: https://doi.org/10.1007/978-3-540-85776-1_24

Constraint Satisfaction has been widely used to model static combinatorial problems. However, many AI problems are dynamic and take place in a distributed environment, i.e. the problems are distributed over a number of agents and change over time. Dy... Read More about DynABT: dynamic asynchronous backtracking for dynamic DisCSPs..

A hybrid approach to distributed constraint satisfaction. (2008)
Presentation / Conference Contribution
LEE, D., ARANA, I., AHRIZ, H. and HUI, K.-Y. 2008. A hybrid approach to distributed constraint satisfaction. In Dochev, D., Pistore, M. and Traverso, P. (eds.) Proceedings of the 13th International conference on artificial intelligence: methodology, systems and applications (AIMSA 2008), 4-6 September 2008, Varna, Bulgaria. Lecture notes in computer science, 5253. Berlin: Springer [online], pages 375-379. Available from: https://doi.org/10.1007/978-3-540-85776-1_33

We present a hybrid approach to Distributed Constraint Satisfaction which combines incomplete, fast, penalty-based local search with complete, slower systematic search. Thus, we propose the hybrid algorithm PenDHyb where the distributed local search... Read More about A hybrid approach to distributed constraint satisfaction..

Escaping local optima: constraint weights vs value penalties. (2007)
Presentation / Conference Contribution
BASHARU, M., ARANA, I. and AHRIZ, H. 2008. Escaping local optima: constraint weights vs. value penalties. In Bramer, M., Coenen, F. and Petridis, M. (eds.) Research and development in intelligent systems XXIV: technical proceedings of the 27th Annual international conference of the British Computer Society's Specialist Group on Artificial Intelligence (SGAI) (AI-2007): innovative techniques and applications of artificial intelligence, 10-12 December 2007, Cambridge, UK. London: Springer [online], pages 51-64. Available from: https://doi.org/10.1007/978-1-84800-094-0_5

Constraint Satisfaction Problems can be solved using either iterative improvement or constructive search approaches. Iterative improvement techniques converge quicker than the constructive search techniques on large problems, but they have a propensi... Read More about Escaping local optima: constraint weights vs value penalties..

DisBO-wd: a distributed constraint satisfaction algorithm for coarse-grained distributed problems. (2007)
Presentation / Conference Contribution
BASHARU, M., ARANA, I. and AHRIZ, H. 2008. DisBO-wd: a distributed constraint satisfaction algorithm for coarse-grained distributed problems. In Bramer, M., Coenen, F. and Petridis, M. (eds.) Research and development in intelligent systems XXIV: technical proceedings of the 27th Annual international conference of the British Computer Society's Specialist Group on Artificial Intelligence (SGAI) (AI-2007): innovative techniques and applications of artificial intelligence, 10-12 December 2007, Cambridge, UK. London: Springer [online], pages 23-36. Available from: https://doi.org/10.1007/978-1-84800-094-0_3

We present a distributed iterative improvement algorithm for solving coarse-grained distributed constraint satisfaction problems (DisCSPs). Our algorithm is inspired by the Distributed Breakout for coarse-grained DisCSPs where we introduce a constrai... Read More about DisBO-wd: a distributed constraint satisfaction algorithm for coarse-grained distributed problems..

Solving coarse-grained DisCSPs with Multi-DisPeL and DisBO-wd. (2007)
Presentation / Conference Contribution
BASHARU, M., ARANA, I. and AHRIZ, A. 2007. Solving coarse-grained DisCSPs with Multi-DisPeL and DisBO-wd. In Lin, T.Y., Bradshaw, J.M., Klusch, M., Zhang, C., Broder, A. and Ho, H. (eds.) Proceedings of the 2007 IEEE/WIC/ACM international conference on intelligent agent technology (IAT 2007), 2-5 November 2007, Silicon Valley, USA. Los Alamitos: IEEE Computer Society [online], article number 4407307, pages 335-341. Available from: https://doi.org/10.1109/IAT.2007.68

We present Multi-DisPel, a penalty-based local search distributed algorithm which is able to solve coarse-grained Distributed Constraint Satisfaction Problems (DisCSPs) efficiently. Multi-DisPeL uses penalties on values in order to escape local optim... Read More about Solving coarse-grained DisCSPs with Multi-DisPeL and DisBO-wd..

Stoch-DisPeL: exploiting randomisation in DisPeL. (2006)
Presentation / Conference Contribution
BASHARU, M., ARANA, I. and AHRIZ, H. 2006. Stoch-DisPeL: exploiting randomisation in DisPeL. Presented at the 7th International workshop on distributed constraint reasoning (DCR 2006), part of the 5th International joint conference on autonomous agents and multiagent systems (AAMAS 2006), 8-12 May 2006, Hakodate, Japan.

We present Stoch-DisPeL, an extension of the distributed constraint programming algorithm DisPeL which incorporates randomisation into the algorithm. We justify the introduction of stochastic moves and analyse its performance on random DisCSPs and on... Read More about Stoch-DisPeL: exploiting randomisation in DisPeL..

Distributed guided local search for solving binary DisCSPs. (2005)
Presentation / Conference Contribution
BASHARU, M., ARANA, I. and AHRIZ, H. 2005. Distributed guided local search for solving binary DisCSPs. In Russell, I. and Markov, Z. (eds.) Proceedings of the 18th International conference of the Florida Artificial Intelligence Research Society (FLAIRS 2005), 16-18 May 2005, Clearwater, USA. Palo Alto: AAAI Press [online], pages 660-665. Available from: http://www.aaai.org/Papers/FLAIRS/2005/Flairs05-108.pdf

We introduce the Distributed Guided Local Search (Dist- GLS) algorithm for solving Distributed Constraint Satisfaction Problems. Our algorithm is based on the centralised Guided Local Search algorithm, which is extended with additional heuristics in... Read More about Distributed guided local search for solving binary DisCSPs..

Solving DisCSPs with penalty-driven search. (2005)
Presentation / Conference Contribution
BASHARU,M., ARANA, I. and AHRIZ, H. 2005. Solving DisCSPs with penalty-driven search. In Proceedings of the 20th American Association for Artificial Intelligence national conference on artificial intelligence (AAAI-05), co-located with the 17th Annual conference on innovative applications of artificial intelligence (IAAI-05), 9-13 July 2005, Pittsburgh, USA. Palo Alto: AAAI Press, pages 47-52.

We introduce the Distributed, Penalty-driven Local search algorithm (DisPeL) for solving Distributed Constraint Satisfaction Problems. DisPeL is a novel distributed iterative improvement algorithm which escapes local optima by the use of both tempora... Read More about Solving DisCSPs with penalty-driven search..

An online collaborative tool for sustainable design. (2005)
Presentation / Conference Contribution
BENNADJI, A., AHRIZ, H. and BELAKEHAL, A. 2005. An online collaborative tool for sustainable design. In Imbabi, M.S. and Mitchell, C.P. (eds.) Renewable energy, technology, innovation and the environment: proceedings of the 2005 Regional meeting of the World Renewable Energy Congress (WREC 2005): innovation in Europe, 22-27 May 2005, Aberdeen, UK. Amsterdam: Elsevier.

One of the most important aspects a design team needs to consider fairly early on is that of energy saving, cost, thermal comfort and the effect on the environment in terms of CO2 emissions. This paper presents an online collaborative tool that allow... Read More about An online collaborative tool for sustainable design..

Escaping local optima with penalties in distributed iterative improvement search. (2005)
Presentation / Conference Contribution
BASHARU, M., ARANA, I. and AHRIZ, H. 2005. Escaping local optima with penalties in distributed iterative improvement search. Presented at the 6th International workshop on distributed constraint reasoning (DCR 2005), part of the 19th International joint conference on artificial intelligence (IJCAI-05), 30 July - 5 August 2005, Edinburgh, UK.

The advantages offered by iterative improvement search make it a popular technique for solving problems in centralised settings. However, the key challenge with this approach is finding effective strategies for dealing with local optima. Such strateg... Read More about Escaping local optima with penalties in distributed iterative improvement search..

Escaping local optima in multi-agent oriented constraint satisfaction. (2004)
Presentation / Conference Contribution
BASHARU, M., AHRIZ, H. and ARANA, I. 2004. Escaping local optima in multi-agent oriented constraint satisfaction. In Coenen, F., Preece, A. and Macintosh, A. (eds.) Research and development in intelligent systems XX: technical proceedings of the 23rd Annual international conference of the British Computer Society's Specialist Group on Artificial Intelligence (SGAI) (AI-2003), 15-17 December 2003, Cambridge, UK. London: Springer [online], pages 97-110. Available from: https://doi.org/10.1007/978-0-85729-412-8_8

We present a multi-agent approach to constraint satisfaction where feedback and reinforcement are used in order to avoid local optima and, consequently, to improve the overall solution. Our approach, FeReRA, is based on the fact that an agents local... Read More about Escaping local optima in multi-agent oriented constraint satisfaction..

Building models through formal specification. (2004)
Presentation / Conference Contribution
RENKER, G. and AHRIZ, H. 2004. Building models through formal specification. In Régin, J.-C. and Rueher, M. (eds.) Integration of AI and OR techniques in constraint programming for combinatorial optimization problems: proceedings of the 1st International conference on integration of artificial intelligence and operations research techniques in constraint programming (CPAIOR 2004), 20-22 April 2004, Nice, France. Lecture notes in computer science, 3011. Berlin: Springer [online], pages 395-401. Available from: https://doi.org/10.1007/978-3-540-24664-0_29

Over the past years, a number of increasingly expressive languages for modelling constraint and optimisation problems have evolved. In developing a strategy to ease the complexity of building models for constraint and optimisation problems, we have a... Read More about Building models through formal specification..