Mosarrat Jahan

Md. Sadmin Tahmid Khan, Md. Saim Ahmmed Utsho, Mosarrat Jahan

Sybil attacks create an illusion of traffic congestion by utilizing fake identities, which undermines the reliable and safe operation of vehicular ad hoc networks (VANETs). Existing detection mechanisms struggle to effectively handle Sybil attacks as they are (i) susceptible to high false positive rates (FPR) due to the overlapping trajectories of both Sybil and legitimate vehicles, (ii) not practical for real-world deployment due to manual calibrations with ground data, (iii) ineffective for sparse distribution of roadside units (RSUs) and vehicles as they depend heavily on the presence of both, and (iv) inefficient due to computational overheads. This paper addresses these shortcomings and proposes a robust framework to tackle these issues. The proposed scheme reduces the FPR by utilizing GPS location data, enabling the construction of more accurate and distinguishable trajectories. Besides, it employs DBSCAN clustering to identify Sybil vehicles, facilitating unsupervised parameter selection. GPS data eliminates the dependency on RSUs and vehicles, making this scheme effective in both sparse and dense regions. Additionally, the proposed scheme is lightweight and consistent across vehicles with heterogeneous capacities. Experimental results demonstrate that the proposed scheme reduces the FPR by approximately 68% in dense regions and 70% in sparse areas. Furthermore, it lowers the false negative rate (FNR) by 67% in the sparse region and achieves a competitive detection rate compared to the existing methods in both dense and sparse regions. Additionally, the proposed scheme decreases the detection time by almost 80% in dense regions and 43% in sparse ones.

Mosarrat Jahan, Fatema Tuz Zohra, Md. Kamal Parvez et al.

Wireless Body Area Network (WBAN) ensures high-quality healthcare services by endowing distant and continual monitoring of patients' health conditions. The security and privacy of the sensitive health-related data transmitted through the WBAN should be preserved to maximize its benefits. In this regard, user authentication is one of the primary mechanisms to protect health data that verifies the identities of entities involved in the communication process. Since WBAN carries crucial health data, every entity engaged in the data transfer process must be authenticated. In literature, an end-to-end user authentication mechanism covering each communicating party is absent. Besides, most of the existing user authentication mechanisms are designed assuming that the patient's mobile phone is trusted. In reality, a patient's mobile phone can be stolen or comprised by malware and thus behaves maliciously. Our work addresses these drawbacks and proposes an end-to-end user authentication and session key agreement scheme between sensor nodes and medical experts in a scenario where the patient's mobile phone is semi-trusted. We present a formal security analysis using BAN logic. Besides, we also provide an informal security analysis of the proposed scheme. Both studies indicate that our method is robust against well-known security attacks. In addition, our scheme achieves comparable computation and communication costs concerning the related existing works. The simulation shows that our method preserves satisfactory network performance.