Browsing by Author "Durresi, Mimoza"

Now showing 1 - 6 of 6
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    Architecture for Mobile Heterogeneous Multi Domain Networks
    (Hindawi, 2010-04-01) Durresi, Arjan; Zhang, Ping; Durresi, Mimoza; Barolli, Leonard; Computer and Information Science, School of Science
    Multi domain networks can be used in several scenarios including military, enterprize networks, emergency networks and many other cases. In such networks, each domain might be under its own administration. Therefore, the cooperation among domains is conditioned by individual domain policies regarding sharing information, such as network topology, connectivity, mobility, security, various service availability and so on. We propose a new architecture for Heterogeneous Multi Domain (HMD) networks, in which one the operations are subject to specific domain policies. We propose a hierarchical architecture, with an infrastructure of gateways at highest-control level that enables policy based interconnection, mobility and other services among domains. Gateways are responsible for translation among different communication protocols, including routing, signalling, and security. Besides the architecture, we discuss in more details the mobility and adaptive capacity of services in HMD. We discuss the HMD scalability and other advantages compared to existing architectural and mobility solutions. Furthermore, we analyze the dynamic availability at the control level of the hierarchy.
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    Enhanced Internet Mobility and Privacy Using Public Cloud
    (Hindawi, 2017-06) Zhang, Ping; Durresi, Mimoza; Durresi, Arjan; Computer and Information Science, School of Science
    Internet mobile users are concerned more and more about their privacy nowadays as both researches and real world incidents show that leaking of communication and location privacy can lead to serious consequence, and many research works have been done to anonymize individual user from aggregated location data. However, just the communication itself between the mobile users and their peers or website could collect considerable privacy of the mobile users, such as location history, to other parties. In this paper, we investigated the potential privacy risk of mobile Internet users and proposed a scalable system built on top of public cloud services that can hide mobile user’s network location and traffic from communication peers. This system creates a dynamic distributed proxy network for each mobile user to minimize performance overhead and operation cost.
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    Networked Biomedical System for Ubiquitous Health Monitoring
    (Hindawi, 2008-11-20) Durresi, Arjan; Durresi, Mimoza; Merkoci, Arben; Barolli, Leonard; Computer and Information Science, School of Science
    We propose a distributed system that enables global and ubiquitous health monitoring of patients. The biomedical data will be collected by wearable health diagnostic devices, which will include various types of sensors and will be transmitted towards the corresponding Health Monitoring Centers. The permanent medical data of patients will be kept in the corresponding Home Data Bases, while the measured biomedical data will be sent to the Visitor Health Monitor Center and Visitor Data Base that serves the area of present location of the patient. By combining the measured biomedical data and the permanent medical data, Health Medical Centers will be able to coordinate the needed actions and help the local medical teams to make quickly the best decisions that could be crucial for the patient health, and that can reduce the cost of health service.
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    Secure Authentication in Heterogeneous Wireless Networks
    (Hindawi, 2008-04-03) Durresi, Arjan; Durresi, Mimoza; Barolli, Leonard; Computer and Information Science, School of Science
    The convergence of cellular and IP technologies has pushed the integration of 3G and WLAN networks to the forefront. Gaining secure access to 3G services from 802.11 WLANs is a primary challenge for this new integrated wireless technology. Successful execution of 3G security algorithms can be limited to a specified area by encrypting a user's authentication challenge with spatial data defining his visited WLAN. With limited capacity to determine a user's location only to within a current cell and restrictions on accessing users' location due to privacy, 3G operators must rely on spatial data sent from visited WLANs to implement spatial authentication control. A potential risk is presented to 3G operators since no prior relationship or trust may exist with a WLAN owner. Algorithms to quantify the trust between all parties of 3G-WLAN integrated networks are presented to further secure user authentication. Ad-hoc serving networks and the trust relationships established between mobile users are explored to define stronger algorithms for 3G – WLAN user authentication.
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    Trustability for Resilient Internet of Things Services on 5G Multiple Access Edge Cloud Computing
    (MDPI, 2022-12-16) Uslu, Suleyman; Kaur, Davinder; Durresi, Mimoza; Durresi, Arjan; Computer and Information Science, School of Science
    Billions of Internet of Things (IoT) devices and sensors are expected to be supported by fifth-generation (5G) wireless cellular networks. This highly connected structure is predicted to attract different and unseen types of attacks on devices, sensors, and networks that require advanced mitigation strategies and the active monitoring of the system components. Therefore, a paradigm shift is needed, from traditional prevention and detection approaches toward resilience. This study proposes a trust-based defense framework to ensure resilient IoT services on 5G multi-access edge computing (MEC) systems. This defense framework is based on the trustability metric, which is an extension of the concept of reliability and measures how much a system can be trusted to keep a given level of performance under a specific successful attack vector. Furthermore, trustability is used as a trade-off with system cost to measure the net utility of the system. Systems using multiple sensors with different levels of redundancy were tested, and the framework was shown to measure the trustability of the entire system. Furthermore, different types of attacks were simulated on an edge cloud with multiple nodes, and the trustability was compared to the capabilities of dynamic node addition for the redundancy and removal of untrusted nodes. Finally, the defense framework measured the net utility of the service, comparing the two types of edge clouds with and without the node deactivation capability. Overall, the proposed defense framework based on trustability ensures a satisfactory level of resilience for IoT on 5G MEC systems, which serves as a trade-off with an accepted cost of redundant resources under various attacks.
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    Trustworthy Acceptance: A New Metric for Trustworthy Artificial Intelligence Used in Decision Making in Food–Energy–Water Sectors
    (Springer, 2021-04) Barolli, Leonard; Woungang, Isaac; Enokido, Tomoya; Uslu, Suleyman; Kaur, Davinder; Rivera, Samuel J.; Durresi, Arjan; Durresi, Mimoza; Babbar-Sebens, Meghna; Computer and Information Science, School of Science
    We propose, for the first time, a trustworthy acceptance metric and its measurement methodology to evaluate the trustworthiness of AI-based systems used in decision making in Food Energy Water (FEW) management. The proposed metric is a significant step forward in the standardization process of AI systems. It is essential to standardize the AI systems’ trustworthiness, but until now, the standardization efforts remain at the level of high-level principles. The measurement methodology of the proposed includes human experts in the loop, and it is based on our trust management system. Our metric captures and quantifies the system’s transparent evaluation by field experts on as many control points as desirable by the users. We illustrate the trustworthy acceptance metric and its measurement methodology using AI in decision-making scenarios of Food-Energy-Water sectors. However, the proposed metric and its methodology can be easily adapted to other fields of AI applications. We show that our metric successfully captures the aggregated acceptance of any number of experts, can be used to do multiple measurements on various points of the system, and provides confidence values for the measured acceptance.