Browsing by Author "Premarathne, US"

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item: Conference-Full-text
Proaasel: prospect theory based continuous authentication attribute selection model
(IEEE, 2016-04) Premarathne, US; Jayasekara, AGBP; Bandara, HMND; Amarasinghe, YWR
Existing continuous authentication models use a fixed set of attributes and do not consider the application specific requirements and associated vulnerabilities in their selection. Selecting appropriate attributes for continuous authentication is essentially a multi-criteria decision making process. Existing multi-criteria decision making models are less competent in providing a preference for each attribute in a set of possible attributes. In this paper we propose a utility based approach: PROAASEL, prospect theory based continuous authentication attribute selection model. The main assumption of our approach is the associated risks for each attribute are pre-defined in terms of known vulnerabilities. The main advantage of our model is the ability to select the attributes based on application specific risk characterizations. We have evaluated PROAASEL using CVE data from [1]. Furthermore, we compared the selection method with existing MCDM techniques TOPSIS and N-model for plausible application scenarios. The results reveal that PROAASEL is more expressive and offer more reliable selection when the associated risks are fixed.
item: Article-Full-text
Reliable context-aware multi-attribute continuous authentication framework for secure energy utilization management in smart homes
(Elsevier, 2015) Premarathne, US
In smart homes, users remotely manage resource utilization tasks and context-aware services using portable devices and mobile communication technologies. Reliability of automated energy consumption management relies upon context-aware continuous authentications of users in executing time-critical tasks. In particular, the contexts of mobility of users and the critical nature of the task are important. Continuous authentication is a robust technique to ensure validity of the authenticity of users over time. Existing continuous authentication techniques do not use the contextual information and dynamic user behavioral characteristics for authentications. We propose a novel context-aware multi-attribute continuous authentication model for secure energy utilization management in smart homes. We use location and the critical nature of the tasks as the contextual information as supporting information for selecting the authentication attributes. We propose novel location and task profiles as context specification metrics and a novel relative-importance based attribute selection technique based on N-model. The usefulness of the proposed solution is validated using real-world data sets. Furthermore, the reliability of the proposed risk based resource management model is analysed as a constraint model using linear temporal logic. Based on the experimental results, this research provides meaningful insights to use pragmatic approaches with security and reliability assurances for resource management applications in smart homes.
item: Article-Full-text
A sum of bernoulli sources approximation for packet switched network traffic in backbone links
(IEE, 2020) Premaratne, U; Premarathne, US
In this letter an intuitive measurement based approximation for packet switched network traffic in backbone links is presented. It consists of a sum of independent non-identical Bernoulli sources. The resulting sum has a Poisson binomial distribution which can be approximated to a skewed Gaussian distribution at the asymptote. It can be further approximated to a binomial distribution for predicting congestion by estimating the number of users of the network. The results are verified using samples of traffic data from 42 academic and research institutions.
item: Article-Full-text
Trust based reliable transmissions strategies for smart home energy consumption management in cognitive radio based smart grid
(Elsevier, 2016) Premarathne, US; Khalil, I; Atiquzzaman, M
Reliability of smart home energy management (SHEM) is enhanced due to the use of opportunistic cognitive radio based communications for reliable transmission of peak period energy utility data. Cognitive radio networks are apt communication solutions capable of offering reliable opportunistic data transmissions through spectrum reuse. Reliable opportunistic data transmissions ensure strategic decision making and to execute critical control operations for sustainable energy utilizations. Accurate spectrum sensing and efficient spectrum sharing are vital to aspects of reliable peak energy consumption data transmission. Cooperative spectrum sensing has been proposed as a more reliable method for gaining accurate spectrum availability detection. Trustworthiness of the local decisions of cooperating users is vital for the accuracy of the final spectrum availability decision. However, measures which can assess the trustworthiness of cooperating users are given less attention. In this paper, we describe a novel multi-attribute trust based framework to facilitate reliable spectrum sensing and priority based spectrum access allocation to enhance delay sensitive data transmissions. We have evaluated our solutions using extensive simulation experiments. Furthermore, we comparatively analyzed the reliability of the proposed user selection method for known spectrum sensing data falsification (SSDF) attack behaviors to accurately identify the non-malicious users. As evidenced by the results proposed novel multi-attribute trust based transmission strategies offer greater reliability in ensuring timely availability of peak period energy utility data for SHEM.