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All Outputs (22)

Defendroid: real-time Android code vulnerability detection via blockchain federated neural network with XAI. (2024)
Journal Article
SENANAYAKE, J., KALUTARAGE, H., PETROVSKI, A., PIRAS, L. and AL-KADRI, M.O. 2024. Defendroid: real-time Android code vulnerability detection via blockchain federated neural network with XAI. Journal of information security and applications [online], 82, article number 103741. Available from: https://doi.org/10.1016/j.jisa.2024.103741

Ensuring strict adherence to security during the phases of Android app development is essential, primarily due to the prevalent issue of apps being released without adequate security measures in place. While a few automated tools are employed to redu... Read More about Defendroid: real-time Android code vulnerability detection via blockchain federated neural network with XAI..

Beyond vanilla: improved autoencoder-based ensemble in-vehicle intrusion detection system. (2023)
Journal Article
RAJAPAKSHA, S., KALUTARAGE, H., AL-KADRI, M.O., PETROVSKI, A. and MADZUDZO, G. 2023. Beyond vanilla: improved autoencoder-based ensemble in-vehicle intrusion detection system. Journal of information security and applications [online], 77, article number 103570. Available from: https://doi.org/10.1016/j.jisa.2023.103570

Modern automobiles are equipped with a large number of electronic control units (ECUs) to provide safe driver assistance and comfortable services. The controller area network (CAN) provides near real-time data transmission between ECUs with adequate... Read More about Beyond vanilla: improved autoencoder-based ensemble in-vehicle intrusion detection system..

A multi-objective evolutionary approach to discover explainability trade-offs when using linear regression to effectively model the dynamic thermal behaviour of electrical machines. (2023)
Journal Article
BANDA, T.M., ZĂVOIANU, A.-C., PETROVSKI, A., WÖCKINGER, D. and BRAMERDORFER, G. 2024. A multi-objective evolutionary approach to discover explainability trade-offs when using linear regression to effectively model the dynamic thermal behaviour of electrical machines. ACM transactions on evolutionary learning and optimization [online], 4(1), article number 3. Available from: https://doi.org/10.1145/3597618

Modelling and controlling heat transfer in rotating electrical machines is very important as it enables the design of assemblies (e.g., motors) that are efficient and durable under multiple operational scenarios. To address the challenge of deriving... Read More about A multi-objective evolutionary approach to discover explainability trade-offs when using linear regression to effectively model the dynamic thermal behaviour of electrical machines..

CBANet: an end-to-end cross band 2-D attention network for hyperspectral change detection in remote sensing. (2023)
Journal Article
LI, Y., REN, J., YAN, Y., LIU, Q., MA, P., PETROVSKI, A. and SUN, H. 2023. CBANet: an end-to-end cross band 2-D attention network for hyperspectral change detection in remote sensing. IEEE transactions on geoscience and remote sensing [online], 61, 5513011. Available from: https://doi.org/10.1109/TGRS.2023.3276589

As a fundamental task in remote sensing observation of the earth, change detection using hyperspectral images (HSI) features high accuracy due to the combination of the rich spectral and spatial information, especially for identifying land-cover vari... Read More about CBANet: an end-to-end cross band 2-D attention network for hyperspectral change detection in remote sensing..

AI-based intrusion detection systems for in-vehicle networks: a survey. (2023)
Journal Article
RAJAPAKSHA, S., KALUTARAGE, H., AL-KADRI, M.O., PETROVSKI, A., MADZUDZO, G. and CHEAH, M. 2023. Al-based intrusion detection systems for in-vehicle networks: a survey. ACM computing survey [online], 55(11), article no. 237, pages 1-40. Available from: https://doi.org/10.1145/3570954

The Controller Area Network (CAN) is the most widely used in-vehicle communication protocol, which still lacks the implementation of suitable security mechanisms such as message authentication and encryption. This makes the CAN bus vulnerable to nume... Read More about AI-based intrusion detection systems for in-vehicle networks: a survey..

Android source code vulnerability detection: a systematic literature review. (2023)
Journal Article
SENANAYAKE, J., KALUTARAGE, H., AL-KADRI, M.O., PETROVSKI, A. and PIRAS, L. 2023. Android source code vulnerability detection: a systematic literature review. ACM computing surveys [online], 55(9), article 187, pages 1-37. Available from: https://doi.org/10.1145/3556974

The use of mobile devices is rising daily in this technological era. A continuous and increasing number of mobile applications are constantly offered on mobile marketplaces to fulfil the needs of smartphone users. Many Android applications do not add... Read More about Android source code vulnerability detection: a systematic literature review..

On the class overlap problem in imbalanced data classification. (2020)
Journal Article
VUTTIPITTAYAMONGKOL, P., ELYAN, E. and PETROVSKI, A. 2021. On the class overlap problem in imbalanced data classification. Knowledge-based systems [online], 212, article number 106631. Available from: https://doi.org/10.1016/j.knosys.2020.106631

Class imbalance is an active research area in the machine learning community. However, existing and recent literature showed that class overlap had a higher negative impact on the performance of learning algorithms. This paper provides detailed criti... Read More about On the class overlap problem in imbalanced data classification..

Handling minority class problem in threats detection based on heterogeneous ensemble learning approach. (2020)
Journal Article
EKE, H., PETROVSKI, A. and AHRIZ, H. 2020. Handling minority class problem in threats detection based on heterogeneous ensemble learning approach. International journal of systems and software security and protection [online], 13(3), pages 13-37. Available from: https://doi.org/10.4018/IJSSSP.2020070102

Multiclass problem, such as detecting multi-steps behaviour of Advanced Persistent Threats (APTs) have been a major global challenge, due to their capability to navigates around defenses and to evade detection for a prolonged period of time. Targeted... Read More about Handling minority class problem in threats detection based on heterogeneous ensemble learning approach..

Sensitivity analysis applied to fuzzy inference on the value of information in the oil and gas industry. (2020)
Journal Article
VILELA, M., OLUYEMI, G. and PETROVSKI, A. 2020. Sensitivity analysis applied to fuzzy inference on the value of information in the oil and gas industry. International journal of applied decision sciences [online], 13(3), pages 344-362. Available from: https://doi.org/10.1504/IJADS.2020.10026404

Value of information is a widely accepted methodology for evaluating the need to acquire new data in the oil and gas industry. In the conventional approach to estimating the value of information, the outcomes of a project assessment relate to the dec... Read More about Sensitivity analysis applied to fuzzy inference on the value of information in the oil and gas industry..

Fuzzy logic applied to value of information assessment in oil and gas projects. (2019)
Journal Article
VILELA, M., OLUYEMI, G. and PETROVSKI, A. 2019. Fuzzy logic applied to value of information assessment in oil and gas projects. Petroleum science [online], 16(5), pages 1208-1220. Available from: https://doi.org/10.1007/s12182-019-0348-0

The concept of value of information (VOI) has been widely used in the oil industry when making decisions on the acquisition of new data sets for the development and operation of oil fields. The classical approach to VOI assumes that the outcome of th... Read More about Fuzzy logic applied to value of information assessment in oil and gas projects..

A fuzzy inference system applied to value of information assessment for oil and gas industry. (2019)
Journal Article
VILELA, M., OLUYEMI, G. and PETROVSKI, A. 2019. A fuzzy inference system applied to value of information assessment for oil and gas industry. Decision making: applications in management and engineering [online], 2(2), pages 1-18. Available from: https:// doi.org/10.31181/dmame1902001v

Value of information is a widely accepted methodology for evaluating the need to acquire new data in the oil and gas industry. In the conventional approach to estimating the value of information, the outcomes of a project assessment relate to the dec... Read More about A fuzzy inference system applied to value of information assessment for oil and gas industry..

Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks. (2019)
Journal Article
MCDERMOTT, C.D., ISAACS, J.P. and PETROVSKI, A.V. 2019. Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks. Informatics [online], 6(1), article 8. Available from: https://doi.org/10.3390/informatics6010008

The growth of the Internet of Things (IoT), and demand for low-cost, easy-to-deploy devices, has led to the production of swathes of insecure Internet-connected devices. Many can be exploited and leveraged to perform large-scale attacks on the Intern... Read More about Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks..

Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation. (2019)
Journal Article
OCHEI, L.C., PETROVSKI, A. and BASS, J.M. 2019. Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation. Journal of cloud computing [online], 8, article 1. Available from: https://doi.org/10.1186/s13677-018-0124-5

One of the challenges of deploying multitenant cloud-hosted services that are designed to use (or be integrated with) several components is how to implement the required degree of isolation between the components when there is a change in the workloa... Read More about Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation..

Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis. (2018)
Journal Article
OCHEI, L.C., BASS, J.M. and PETROVSKI, A. 2018. Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis. Journal of cloud computing [online], 7, article ID 22. Available from: https://doi.org/10.1186/s13677-018-0121-8

A challenge, when implementing multi-tenancy in a cloud-hosted software service, is how to ensure that the performance and resource consumption of one tenant does not adversely affect other tenants. Software designers and architects must achieve an o... Read More about Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis..

Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP). (2018)
Journal Article
ANI, M., OLUYEMI, G., PETROVSKI, A. and REZAEI-GOMARI, S. 2019. Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP). Journal of petroleum science and engineering [online], 174, pages 833-843. Available from: https://doi.org/10.1016/j.petrol.2018.11.024

The selection of an optimal model from a set of multiple realizations for dynamic reservoir modelling and production forecasts has been a persistent issue for reservoir modelers and decision makers. Current evidence has shown that many presumably goo... Read More about Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP)..

A framework for achieving the required degree of multitenancy isolation for deploying components of a cloud-hosted service. (2018)
Journal Article
OCHEI, L.C., PETROVSKI, A. and BASS, J.M. 2018. A framework for achieving the required degree of multitenancy isolation for deploying components of a cloud-hosted service. International journal of cloud computing [online], 7(3-4), pages 248-281. Available from: https://doi.org/10.1504/IJCC.2018.095396

Multitenancy allows multiple tenants to access a single instance of a cloud offering. While several approaches exist for implementing multitenancy, little attention has been paid to implementing the required degree of isolation since there are varyin... Read More about A framework for achieving the required degree of multitenancy isolation for deploying components of a cloud-hosted service..

Evolving ANN-based sensors for a context-aware cyber physical system of an offshore gas turbine. (2017)
Journal Article
MAJDANI, F., PETROVSKI, A. and DOOLAN, D. 2017. Evolving ANN-based sensors for a context-aware cyber physical system of an offshore gas turbine. Evolving systems [online], 9(2), pages 119-133. Available from: https://doi.org/10.1007/s12530-017-9206-8

An adaptive multi-tiered framework, that can be utilised for designing a context-aware cyber physical system to carry out smart data acquisition and processing, while minimising the amount of necessary human intervention is proposed and applied. The... Read More about Evolving ANN-based sensors for a context-aware cyber physical system of an offshore gas turbine..

Investigation of computational intelligence techniques for intrusion detection in wireless sensor networks. (2017)
Journal Article
MCDERMOTT, C.D. and PETROVSKI, A. 2017. Investigation of computational intelligence techniques for intrusion detection in wireless sensor networks. International journal of computer networks and communications [online], 9(4), pages 45-56. Available from: https://doi.org/10.5121/ijcnc.2017.9404

Wireless Sensor Networks (WSNs) have become a key technology for the IoT and despite obvious benefits, challenges still exist regarding security. As more devices are connected to the internet, new cyber attacks are emerging which join well-known atta... Read More about Investigation of computational intelligence techniques for intrusion detection in wireless sensor networks..

A framework for unsupervised change detection in activity recognition. (2017)
Journal Article
BASHIR, S.A., PETROVSKI, A. and DOOLAN, D. 2017. A framework for unsupervised change detection in activity recognition. International journal of pervasive computing and communications [online], 13(2), pages 157-175. Available from: https://doi.org/10.1108/IJPCC-03-2017-0027

Purpose - This purpose of this paper is to develop a change detection technique for activity recognition model. The approach aims to detect changes in the initial accuracy of the model after training and when the model is deployed for recognizing new... Read More about A framework for unsupervised change detection in activity recognition..

Clustering and nearest neighbour based classification approach for mobile activity recognition. (2016)
Journal Article
BASHIR, S.A., DOOLAN, D.C. and PETROVSKI, A. 2016. Clustering and nearest neighbour based classification approach for mobile activity recognition. Journal of mobile multimedia [online], 12(1-2), pages 110-124. Available from: https://journals.riverpublishers.com/index.php/JMM/article/view/4487

We present a hybridized algorithm based on clustering and nearest neighbour classifier for mobile activity recognition. The algorithm transforms a training dataset into a more compact and reduced representative set that lessens the computational cost... Read More about Clustering and nearest neighbour based classification approach for mobile activity recognition..