With the increasing sophistication of financial frauds, there is now a need for more advanced, secure, and scalable detection mechanisms. A fraud detection framework has been proposed that uses Federated Deep Learning (FDL) and Quantum Key Distribution (QKD) for non-IID financial data while carrying out secure communication. Using FL algorithms-FedAvg, FedAdagrad, FedAMP, and FedDyn-on partitioned client data, we demonstrate that FedDyn outperforms the other algorithms with an accuracy of 97.74%. Furthermore, we use Continuous-Variable QKD to encrypt the model updates to secure client-server communication, achieving a secure key ratio of above 98% and key rates of more than 250,000 bits/sec. Lastly, we implemented an elaborate suite of evaluations consisting of client-wise metrics, ROC curves, and t-SNE plots to validate the efficacy of our model implementation in terms of both performance and privacy preservation. Through our results, we address the brought-up importance of distributed intelligence powered by quantum encryption against advanced financial frauds.
Param Desai, Mohammad S. Obaidat, Mahek Desai et al.· International Conference on...· 0 citations
The high mobility and decentralized nature of Vehicular Ad Hoc Networks (VANETs) present significant security challenges. Specifically, detecting attacks and establishing secure, reliable routing protocols are major critical concerns in the vehicular environment. These attacks can significantly degrade network performance and hinder communication between vehicles. Insider attacks, such as Blackhole attacks, have the potential to severely disrupt VANET systems. This study introduces a novel trust management scheme that incorporates cryptographic techniques to address the important issues of secure routing in VANETs, which also helps in the detection of attacks. In this work, nodes' trust scores are evaluated, and the forwarding node for packet dissemination is chosen based on these scores. Furthermore, an elliptic curve cryptographic (ECC) signcryption technique is added for providing security to the network by authenticating the nodes, which mitigates the misbehaving nodes from the network. The simulation and comparative analysis show the efficacy of the proposed scheme. The proposed approach attained a packet delivery ratio (PDR) of 92.8%, indicating high reliability in data dissemination. Furthermore, the achieved results of throughput and End‐to‐End (E2E) delay are 232.32 KBps and 0.02 s, respectively. The obtained outcomes show enhancements of 94.182%, 49.67%, and 6% in PDR, throughput, and E2E delay, respectively, with respect to the existing techniques.
Nidhi Jaswani, Mou Dasgupta, Sangram Ray et al.· Security and Privacy· 0 citations