- Salako, K. and Zhao, X. (2023). The Unnecessity of Assuming Statistically Independent Tests in Bayesian Software Reliability Assessments. IEEE Transactions on Software Engineering, 49(4), pp. 2829–2838. doi:10.1109/tse.2022.3233802.
- Zhao, X., Salako, K., Strigini, L., Robu, V. and Flynn, D. (2020). Assessing Safety-Critical Systems from Operational Testing: A Study on Autonomous Vehicles. Information and Software Technology pp. 1–1. doi:10.1016/j.infsof.2020.106393.
- Littlewood, B., Salako, K., Strigini, L. and Zhao, X. (2020). On reliability assessment when a software-based system is replaced by a thought-to-be-better one. Reliability Engineering & System Safety, 197, pp. 106752–106752. doi:10.1016/j.ress.2019.106752.
- Bloomfield, R.E., Popov, P., Salako, K., Stankovic, V. and Wright, D. (2017). Preliminary interdependency analysis: An approach to support critical-infrastructure risk-assessment. Reliability Engineering & System Safety, 167, pp. 198–217. doi:10.1016/j.ress.2017.05.030.
- Netkachov, O., Popov, P. and Salako, K. (2016). Model-Based Evaluation of the Resilience of Critical Infrastructures Under Cyber Attacks. pp. 231–243. doi:10.1007/978-3-319-31664-2_24.
- Netkachov, O., Popov, P. and Salako, K. (2014). Quantification of the Impact of Cyber Attack in Critical Infrastructures. pp. 316–327. doi:10.1007/978-3-319-10557-4_35.
- Salako, K. and Strigini, L. (2013). When does "Diversity" in Development Reduce Common Failures? Insights from Probabilistic Modelling. IEEE Transactions on Dependable and Secure Computing, 99(preprints). doi:10.1109/TDSC.2013.32.
Contact details
Address
Northampton Square
London EC1V 0HB
United Kingdom
About
Overview
Dr Kizito Salako is an applied mathematician and software developer at the Centre for Software Reliability (CSR), City University London. He holds a first-class double honours degree in Mathematics and Statistics from the University of Lagos; a Master of Advanced Study in Mathematics degree from the University of Cambridge (where he was both a Shell Centenary Scholar and a Commonwealth Scholar); and a PhD in Computer Science from City, University of London.
Kizito is passionate about applications of probability theory, Bayesian statistics, geometry and machine-learning techniques, when trying to simulate, assess and forecast the (failure) behaviour of software-based systems. His doctoral thesis clarifies and significantly extends the applicability of a family of probabilistic models used to describe the failure behaviour of multi-version software. He also developed a novel geometric approach to extremising the expected system reliability of a class of fault-tolerant software-based systems; so-called 1-out-of-N systems. Currently, he is particularly interested in the assessment/forecasting challenges that arise when these systems rely on evolving machine-learning solutions.
Since joining CSR, Kizito has contributed to several projects (e.g. DISPO, DIRC, IRRIIS, PIA-FARA, AFTER, DIDERO-PC, DISIEM). He is experienced in building simulations of complex systems using C++, and was instrumental in developing the PIA-FARA simulation engine -- creating modular software that implements and analyses the probabilistic, functional and process relationships that may exist between the components of large-scale interdependent complex critical infrastructure.
Research
Research Interests
Quantitative assessment of the dependability of software-based systems (in particular, systems that are complex, safety/security critical, and that may rely on evolving machine learning solutions):
The development, validation and application of advanced statistical approaches for dependability assessment;
Conservative Bayesian assessment methods, that take into account various forms of dependability evidence when assessing system dependability;
Monte-Carlo methods for simulating complex systems (where these systems are modelled as Generalised Semi-Markov and Markov Regenerative Processes);
The combined use of probabilistic conditional independence relations and physics models in modelling interdependencies between complex systems
The efficacy (in terms of improved reliability) of using diverse-redundant software in fault-tolerant configurations
Statistical forecasting/analyses of system risk, dependability and cyber-security issues:
Investigating the impact of software development strategies on system reliability;
Studying the efficacy of mitigation strategies for a system under cyber-attack;
Studying the efficacy of diverse redundant system architectures in mitigating cyber-attacks, and the implications of such strategies for the likelihood of confidentiality and integrity breaches;
Research Projects
Kizito has collaborated on several national and international research projects. Details of these projects can be found here. The projects include:
DISIEM (funded by the EU horizon-2020 program) Diversity Enhancements for Security Information and Events Management Systems, 2016–2019
CEDRICS (funded by the UK’s EPSRC) Communicating and Evaluating Cyber–Risks and Dependencies, 2014–2017
AFTER (EU funded FP7 project) A Framework for sysTems vulnerability identification, dEfence and Restoration, 2011–2014
DIDERO-PC (funded by the UK’s EPSRC) DIverse DatabasE ReplicatiOn Performance Comparison, 2013–2014
PIA-FARA (funded by the UK’s Technology Strategy Board) Probabilistic Interdependency Analysis: Framework/data-Analysis/Risk–Assessment, 2009–2010
CETIFS (funded by the UK’s Technology Strategy Board) A Critical Infrastructure Interdependency Modelling Feasibility Study, 2008
IRRIIS (EU funded FP6 Project) Integrated Risk–Reduction of Information-based Infrastructure Systems, 2006–2009
DIRC (funded by the UK’s EPSRC) Dependability Integrated Research Collaboration, 2000–2006
Mathematical Interests
Probability Theory and Mathematical Statistics:
measure theoretic probability – probability spaces, integration, conditional expectation, characteristic functions, Radon-Nikodym derivatives and change-of-measure;
stochastic models and processes – filtered probability spaces; stationary/non-stationary; time-series analyses; point processes; order-statistics models; Gaussian processes; Markov processes (Markov chains, Markov renewal processes, Markov reward processes, Markov decision processes, hidden Markov models); hybrid stochastic/deterministic models;
stochastic analysis – convergence of random variables, stochastic calculus/stochastic differential equations (Ito-calculus, jump-diffusion processes);
statistical (Bayesian) inference and modelling – parametric and non-parameteric; estimation theory; posterior predictive distributions; prequential/statistical forecasting systems; asymptotic theory (Slutsky’s theorem, delta-method, portmanteau theorem, weak/strong laws); hypothesis testing; goodness-of-fit analyses; ROC techniques;
Machine Learning Approaches and Considerations: supervised learning (Regression, GLMs, SVMs, ANNs, CNNs, LSTMs); deep reinforcement learning (approximate Q-learning, temporal difference methods)
Mathematical Finance: mean-variance portfolio theory; CAPM, option-pricing, Wiener processes/Brownian motion, Martingales, risk-neutral measures, the Black-Scholes model;
Mathematical Analysis and Vector-Space Theory: real and complex analysis; metric spaces; infinite-dimensional vector-spaces – functional analysis (Banach/Hilbert spaces); finite-dimensional vector-spaces – linear/multilinear algebra, differential geometry/calculus on manifolds, tensor calculus; applications of fixed-point theorems; non-linear dynamical systems theory;
Mathematical/Statistical Optimisation: linear programming, convex optimisation, stochastic gradient methods, dynamic programming, simulated annealing, steepest descent;
Publications
Publications by category
Chapters (2)
- In Flammini, F. (Ed.), (2019). Resilience of Cyber-Physical Systems. In Springer International Publishing. ISBN 978-3-319-95596-4.
- Netkachov, O., Popov, P. and Salako, K. (2019). Quantitative Evaluation of the Efficacy of Defence-in-Depth in Critical Infrastructures. Resilience of Cyber-Physical Systems (pp. 89–121). Springer International Publishing. ISBN 978-3-319-95596-4.
Conference papers and proceedings (9)
- Chakherlou, R.A., Salako, K. and Strigini, L. (2022). Arguing safety of an improved autonomous vehicle from safe operation before the change: new results. 2022 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) 31 Oct 2022 – 3 Nov 2022. doi:10.1109/issrew55968.2022.00085
- Salako, K., Strigini, L. and Zhao, X. (2021). Conservative Confidence Bounds in Safety, from Generalised Claims of Improvement & Statistical Evidence. 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) 21-24 June. doi:10.1109/dsn48987.2021.00055
- Salako, K. (2020). Loss-Size and Reliability Trade-Offs Amongst Diverse Redundant Binary Classifiers. doi:10.1007/978-3-030-59854-9_8
- Zhao, X., Robu, V., Flynn, D., Salako, K. and Strigini, L. (2019). Assessing the Safety and Reliability of Autonomous Vehicles from Road Testing. 2019 IEEE 30th International Symposium on Software Reliability Engineering (ISSRE) 28-31 October. doi:10.1109/issre.2019.00012
- Popov, P., Salako, K.O. and Stankovic, V. (2015). Stochastic modeling for performance evaluation of database replication protocols. 12th International Conference on Quantitative Evaluation of Systems 1-3 September, Madrid, Spain. doi:10.1007/978-3-319-22264-6_2
- Jones, K. and Salako, K. (2013). Modeling Security Policy and the Effect for End-Users. HCI International 2013: 15th International Conference on Human-Computer Interaction 21-26 July, Las Vegas, Nevada, US.
- Bloomfield, R.E., Chozos, N. and Salako, K. (2009). Current Capabilities, Requirements and a Proposed Strategy for Interdependency Analysis in the UK.
- Bloomfield, R.E., Buzna, L., Popov, P.T., Salako, K. and Wright, D. (2009). Stochastic Modelling of the Effects of Interdependencies between Critical Infrastructure.
- Salako, K. (2007). Bounds on the Reliability of Fault-Tolerant Software Built by Forcing Diversity.
Internet publication
- Salako, K. Home Page.
Journal articles (7)
Report
- Salako, K., Strigini, L. and Zhao, X. (2021). Proofs of Conservative Confidence Bounds on PFD, Using Claims of Improved Reliability..
Software (3)
- Salako, K., Stankovic, V. and Popov, P. (2015). Stochastic model for performance evaluation of database replication protocols..
- Popov, P., Salako, K. and Stankovic, V. (2015). Stochastic Modeling for Performance Evaluation of Database Replication Protocols. Springer International Publishing.
- Netkachov, O., Popov, P. and Salako, K. Simulation model of the extended Nordic32 network..