Wireless sensor networks (WSNs) have been commonly utilized in event detection and environmental observation applications. The main aim of event detection is to define the presence or absence of an event. Various existing studies in the field of event detection depend on static or threshold values to reveal the occurrence of an event, which can result in imprecise sensor readings. Recently, many studies have utilized fuzzy logic to treat fluctuating sensor readings; as a result, they have decreased the number of false alarms created. However, there is some attention required when utilizing fuzzy logic. One aspect is that the efficiency and accuracy of the fuzzy membership function can be impacted by the utilization of heterogeneous sensors, which may increase the complexity of the fuzzy logic operation as the number of inputs rises. To address these issues, this paper proposes an approach named Probabilistic Collaborative Event Detection (PCED), which is a hybrid event detection technique that is based on a cluster WSN topology. The PCED approach utilizes a validated probabilistic technique for heterogeneous sensor nodes to transform sensing values into probability formulas and introduces a Cluster Head Decision Mechanism to make decisions based on the aggregated data from the sensors. The proposed approach employs fuzzy logic at the fusion center level to enhance the precision of event detection. The effectiveness of this method is thoroughly evaluated using MATLAB software, demonstrating an improvement in the probability of detection and a decrease in the probability of false alarms. PCED is compared to well-established event detection mechanisms such as the REFD mechanism. The results show that PCED reduces the occurrence of false alarms from 37 to 3 in certain scenarios, while improving detection accuracy by up to 19.4% over REDF and decreasing detection latency by up to 17.5%.

Due to increased inspection of internet traffic and the pervasive surveillance practices put in place by many organizations, virtual private networks (VPNs) are now frequently used to safeguard online privacy and circumvent censorship. However, existing VPN protocols are susceptible to methods of detection and blockage employed by network administrators, internet service providers, and in certain cases, governments. Stealth protocols and proxying techniques have therefore been presented as potential means of hiding VPN activity and avoiding discovery. Therefore, the purpose of this work is to assess how well stealth protocols and proxying work to hide the use of VPNs using a thorough experimental setup (i.e., evaluate how well-known stealth VPN protocols like Obfsproxy, Shadowsocks, and WireGuard perform against different detection techniques like deep packet inspection (DPI)). Furthermore, examine the effects of using proxy servers in conjunction with VPN connections in order to further obfuscate traffic signatures and improve privacy. The results center on how well various stealth protocols and proxying techniques defy detection attempts, offering insightful information to VPN users and developers. Thus, the outcomes help strengthen censorship resistance and online particularity in keeping pace with the development of monitoring technology. Also, analyze the efficiency of Obfsproxy, Shadowsocks, and WireGuard to provide comprehensive comparisons of current capabilities and potential enhancements. Finally, a discussion for future VPN design is conducted, focusing on the importance of adaptability in keeping secure communication channels among increasingly sophisticated surveillance measures. Received: 18 June 2024 | Revised: 2 August 2024 | Accepted: 20 August 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data are available on request from the corresponding author upon reasonable request. Author Contribution Statement Mohammad Shehab: Conceptualization, Methodology, Validation, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration. Lial Raja Alzabin: Conceptualization, Methodology, Formal analysis, Resources, Writing – review & editing, Visualization.

In recent years, a range of innovative approaches have been developed to tackle decision-making challenges more effectively. These approaches include concepts such as probability theory, fuzzy set theory, intuitionistic fuzzy sets, vague sets, interval mathematics, and rough set theory. These tools each offer unique approaches to managing uncertainty and imprecision, which are common when working with complex systems. One major issue in software development is failure to meet security requirements. This can be caused by a variety of factors, such as unclear security specifications, evolving threat landscapes, or gaps in communication among stakeholders. To address this persistent problem, this paper introduces a new method designed to quantify security requirements more accurately and streamline the decision-making process for assessing security risks. This approach is based on fuzzy soft set theory, which allows for more flexible and precise handling of uncertain or ambiguous information. By using this method, software engineers and security professionals can gain a clearer understanding of security risks and make better-informed decisions when building secure systems. To demonstrate the practical value of the proposed method, a case study is conducted to evaluate its effectiveness. The results of this case study suggest that security administrators can use this method to implement more targeted and efficient security measures, ensuring that the systems they develop are more resilient to potential threats. Received: 20 July 2025 | Revised: 20 October 2025 | Accepted: 31 October 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data are available from the corresponding author upon reasonable request. Author Contribution Statement Dyala Ibrahim: Conceptualization, Software, Resources, Data curation, Writing – review & editing, Supervision, Project administration. Omar Isam Al Mrayat: Conceptualization, Methodology, Software, Resources, Data curation, Writing – review & editing, Supervision, Project administration. Lial Raja Alzabin: Software, Resources, Data curation, Visualization. Ahmad Alajarmeh: Validation, Visualization. Ahmad Reda Alzighaibi: Validation, Formal analysis, Writing – original draft. Hasan Hashim: Investigation. El-Sayed Atlam: Investigation. Malik Jawarneh: Investigation.