Vanredni profesor, University of Sarajevo
Polje Istraživanja: Computer security and reliability Cryptography (Computer science) Network science
Secure communication makes the widespread use of telecommunication networks and services possible. With the constant progress of computing and mathematics, new cryptographic methods are being diligently developed. Quantum Key Distribution (QKD) is a promising technology that provides an Information-Theoretically Secure (ITS) solution to the secret-key agreement problem between two remote parties. QKD networks based on trusted repeaters are built to provide service to a larger number of parties at arbitrary distances. They function as an add-on technology to traditional networks, generating, managing, distributing, and supplying ITS cryptographic keys. Since key resources are limited, integrating QKD network services into critical infrastructures necessitates effective key management. As a result, this paper provides a comprehensive review of QKD network key management approaches. They are analyzed to facilitate the identification of potential strategies and accelerate the future development of QKD networks.
In the ongoing discourse surrounding integrating QKD networks as a service for critical infrastructures, key storage design often receives insufficient attention. Nonetheless, it bears crucial significance as it profoundly impacts the efficiency of QKD network services, thereby shaping its suitability for diverse applications. In this article, we analyze the effectiveness of key storage designs developed through practical testbeds and propose a novel key storage design to increase the effectiveness of key creation and supply. All key storage designs underwent analysis using network simulation tools, and the findings demonstrate that the novel key storage design surpasses existing approaches in terms of performance.
Quantum Key Distribution (QKD), a novel secret key agreement primitive, enables long-awaited practical Information-Theoretical Security (ITS). Over the last two decades, academic and industrial communities have devoted their time and resources to developing QKD- based networks that distribute ITS keys to remote parties. However, because of the limited availability of QKD network testbeds to the larger research community and the difficulty and cost of their deployment, progress in this area has been noticeably slow. To that end, we provide an analysis of selected simulated use-cases from the EU H2020 OPENQKD project using the QKDNetSim network simulator. The tool has been extensively upgraded to test novel network management methodologies applied to large-scale QKD networks.
IP devices are ubiquitously spread, for both residential and industrial purposes, thanks to the low integration costs and rapid development cycle of all-IP-based 5G+ technologies. As a consequence, the engineering community now considers their automatization and energy scheduling/management as relevant research fields. These topics have a striking relevance also for the development of smart city networks. As a drawback, most ID-device applications produce a large amount of data (high-frequency complexity), requiring supervised machine learning algorithms to be properly analyzed. In this research, we focus on the performance of vehicular mobility and imaging systems, recognizing scenarios (with powered-on devices) in real-time, with the help of a simple convolutional neural network, proving the effectiveness of such an innovative low-cost approach.
Anonymous communication networks (ACNs) enable Internet browsing in a way that prevents accessed content from being traced back to the user. This provides a high level of privacy, protecting individuals from being tracked by advertisers, governments, and other entities. The Tor network, a prominent example of such a network, uses a layered encryption scheme to encapsulate data packets, employing Tor nodes to obscure the routing process before the packets enter the public Internet. While Tor is capable of providing substantial privacy, its encryption relies on schemes such as RSA and Diffie-Hellman for distributing symmetric keys, which are vulnerable to quantum computing attacks and are currently in the process of being phased out. To overcome this threat, we propose a quantum resistant alternative to RSA and Diffie-Hellman for distributing symmetric keys, namely, quantum key distribution (QKD). Standard QKD networks depend on trusted nodes to relay keys across long distances. However, reliance on trusted nodes in the quantum network does not meet the criteria necessary for establishing a Tor circuit in the ACN. We address this issue by developing a protocol and network architecture that integrates QKD without the need for trusted nodes, thus meeting the requirements of the Tor network and creating a quantum secure anonymous communication network.
With the low integration costs and quick development cycle of all-IP-based 5G+ technologies, it is not surprising that the proliferation of IP devices for residential or industrial purposes is ubiquitous. Energy scheduling/management and automated device recognition are popular research areas in the engineering community, and much time and work have been invested in producing the systems required for smart city networks. However, most proposed approaches involve expensive and invasive equipment that produces huge volumes of data (high-frequency complexity) for analysis by supervised learning algorithms. In contrast to other studies in the literature, we propose an approach based on encoding consumption data into vehicular mobility and imaging systems to apply a simple convolutional neural network to recognize certain scenarios (devices powered on) in real time and based on the nonintrusive load monitoring paradigm. Our idea is based on a very cheap device and can be adapted at a very low cost for any real scenario. We have also created our own data set, taken from a real domestic environment, contrary to most existing works based on synthetic data. The results of the study’s simulation demonstrate the effectiveness of this innovative and low-cost approach and its scalability in function of the number of considered appliances.
With the development of new technologies, next-generation mobile networks have brought new services with strict performance and security requirements. One promising solution that can ensure the highest possible level of security is quantum key distribution (QKD). This technology provides information-theoretical security using the principles of quantum physics. This paper presents an extended analysis of one implementation of the QKD key delivery protocol defined in the ETSI GS QKD 014 standard, considering a multi-user environment. We propose an empirically derived model of key delivery latency in such an environment based on regression analysis of experimental results. Using the proposed model, we estimate the limitations of the implemented solution in terms of maximum number of simultaneous users connected to one key management server, considering several applications in 5G/6G networks.
The wide range of supported services in modern telecommunication networks has increased the demand for highly secure means of communication. Common security frameworks based on the computational security model are expected to become insecure due to significant advances in quantum computing. Quantum key distribution (QKD), a new secret key agreement primitive, enables long-anticipated practical information-theoretical security (ITS). Over the past two decades, academic and industrial communities have devoted their time and resources to developing QKD-based networks that can distribute and serve ITS keys to remote parties. However, because the availability of QKD network testbeds to the larger research community is limited and the deployment of such systems is costly and difficult, progress in this area is noticeably slow. To address this problem and spur future development and education, we provide a valuable, unique tool for simulating a QKD network. The tool is essential to testing novel network management methodologies applied to large-scale QKD networks. The simulator model contained in the tool was validated by simulating a network with six nodes and three pairs of users. The results indicate that the designed functional elements operate correctly.
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