Biblio

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2022-09-30
Asare, Bismark Tei, Quist-Aphetsi, Kester, Nana, Laurent, Simpson, Grace.  2021.  A nodal Authentication IoT Data Model for Heterogeneous Connected Sensor Nodes Within a Blockchain Network. 2021 International Conference on Cyber Security and Internet of Things (ICSIoT). :65–71.
Modern IoT infrastructure consists of different sub-systems, devices, applications, platforms, varied connectivity protocols with distinct operating environments scattered across different subsystems within the whole network. Each of these subsystems of the global system has its peculiar computational and security challenges. A security loophole in one subsystem has a directly negative impact on the security of the whole system. The nature and intensity of recent cyber-attacks within IoT networks have increased in recent times. Blockchain technology promises several security benefits including a decentralized authentication mechanism that addresses almost readily the challenges with a centralized authentication mechanism that has the challenges of introducing a single point of failure that affects data and system availability anytime such systems are compromised. The different design specifications and the unique functional requirements for most IoT devices require a strong yet universal authentication mechanism for multimedia data that assures an additional security layer to IoT data. In this paper, the authors propose a decentralized authentication to validate data integrity at the IoT node level. The proposed mechanism guarantees integrity, privacy, and availability of IoT node data.
2020-04-10
Asare, Bismark Tei, Quist–Aphetsi, Kester, Nana, Laurent.  2019.  Nodal Authentication of IoT Data Using Blockchain. 2019 International Conference on Computing, Computational Modelling and Applications (ICCMA). :125—1254.
Pervasive systems over the years continuous to grow exponentially. Engagement of IoT in fields such as Agriculture, Home automation, industrial applications etc is on the rise. Self organizing networks within the IoT field give rise to engagement of various nodes for data communication. The rise in Cyber-attacks within IoT pose a lot of threat to these connected nodes and hence there is a need for data passing through nodes to be verified during communication. In this paper we proposed a nodal authentication approach in IoT using blockchain in securing the integrity of data passing through the nodes in IoT. In our work, we engaged the GOST algorithm in our approach. At the end, we achieved a nodal authentication and verification of the transmitted data. This makes it very difficult for an attacker to fake a node in the communication chain of the connected nodes. Data integrity was achieved in the nodes during the communication.
2017-06-27
Bouziane, Mohamed, Gire, Sophie, Monin, François, Nana, Laurent.  2016.  Formal Proof of Security Algorithms Based on Reachability Reduction. Proceedings of the 8th International Conference on Management of Digital EcoSystems. :67–72.

This work is motivated by the rapid increase of the number of attacks in computer networks and software engineering. In this paper we study identity snowball attacks and formally prove the correctness of suggested solutions to this type of attack (solutions that are based on the graph reachability reduction) using a proof assistant. We propose a model of an attack graph that captures technical informations about the calculation of reachability of the graph. The model has been implemented with the proof assistant PVS 6.0 (Prototype Verification System). It makes it possible to prove algorithms of reachability reduction such as Sparsest\_cut.

2017-05-22
Ghadi, Musab, Laouamer, Lamri, Nana, Laurent, Pascu, Anca.  2016.  A Robust Associative Watermarking Technique Based on Frequent Pattern Mining and Texture Analysis. Proceedings of the 8th International Conference on Management of Digital EcoSystems. :73–81.

Nowadays, the principle of image mining plays a vital role in various areas of our life, where numerous frameworks based on image mining are proposed for object recognition, object tracking, sensing images and medical image diagnosis. Nevertheless, the research in the image authentication based on image mining is still confined. Therefore, this paper comes to present an efficient engagement between the frequent pattern mining and digital watermarking to contribute significantly in the authentication of images transmitted via public networks. The proposed framework exploits some robust features of image to extract the frequent patterns in the image data. The maximal relevant patterns are used to discriminate between the textured and smooth blocks within the image, where the texture blocks are more appropriate to embed the secret data than smooth blocks. The experiment's result proves the efficiency of the proposed framework in terms of stabilization and robustness against different kind of attacks. The results are interesting and remarkable to preserve the image authentication.