Background: In the wake of escalating cyber threats and the indispensability of ro-bust network security mechanisms, it becomes crucial to understand the evolving landscape of cryptographic research. Recognizing the s...
详细信息
Robust fake speech detection systems are crucial in an era where audio recordings can be easily altered or developed due to advancements in technology. The potential impact of this technology could be devastating due ...
详细信息
Agriculture is the primary source of food, fuel, and raw materials and is vital to any country’s economy. Farmers, the backbone of agriculture, primarily rely on instinct to determine what crops to plant in any given...
详细信息
In complex networks, identifying influential nodes becomes critical as these networks emerge rapidly. Extensive studies have been carried out on intricate networks to comprehend diverse real-world networks, including ...
详细信息
In complex networks, identifying influential nodes becomes critical as these networks emerge rapidly. Extensive studies have been carried out on intricate networks to comprehend diverse real-world networks, including transportation networks, facebook networks, animal social networks, etc. Centrality measures like degree, betweenness, closeness, and clustering centralities are used to find influential nodes, but these measures have limitations in implementation with large-scale networks. These centrality measures are classified into global and local centralities. Semi-local structures perform well compared to local and global centralities but efficient centrality for finding influential nodes remains a challenging issue in large-scale networks. To address this challenge, a Semi-Local Average Isolating Centrality (SAIC) metric is proposed that integrates semi-local and local information to identify important nodes in large networks, along with the relative change in average shortest path. Here, we consider extended neighborhood concept for selecting the nodes nearest neighbors along with the weighted edge policy to find the best influential nodes by using SAIC. Along with these, SAIC also consider isolated nodes which significantly impact the network connectedness by maximizing the number of connected components upon removal. As a result SAIC differentiates itself from other centrality metrics by employing a distributed approach to define semi-local structure and utilizing an efficient edge weighting policy. The analysis of SAIC has been performed on multiple real-time datasets using Kendall tau’s coefficient. Using the Susceptible-Infected-Recovered (SIR) and Independent Cascade(IC) models, the performance of SAIC has been examined to determine maximum information spread in comparison to the most recent metrics in some real-world datasets. Our proposed method SAIC performs better in terms of information spreading when compare with other exisiting methods, with an imp
The use of management by objectives (MBOs) methodologies, particularly the objectives and key results (OKRs) framework, has gained widespread attention in recent years as a means of improving organizational performanc...
详细信息
In this paper, we identified an issue where the I/O performance of specific tasks could not be guaranteed during multi-process I/O operations, despite the use of the latest storage technologies in virtualized environm...
详细信息
Airplanes play a critical role in global transportation, ensuring the efficient movement of people and goods. Although generally safe, aviation systems occasionally encounter incidents and accidents that underscore th...
详细信息
A common problem on the streets of Dhaka, the capital of a developing country Bangladesh, is the reduction in the effective road width and blockage of roads due to various side friction elements. Despite significant e...
详细信息
A common problem on the streets of Dhaka, the capital of a developing country Bangladesh, is the reduction in the effective road width and blockage of roads due to various side friction elements. Despite significant efforts to study the effects of side friction in different contexts, a comprehensive study that efficiently models side friction elements and then analyzes their impacts using a contextually appropriate simulator for heterogeneous non-lane-based traffic in cities like Dhaka is yet to be conducted in the literature. Therefore, in this study, we attempt to fill this gap. Here, based on real data analysis, we list side friction elements that exhibit substantial impacts on the regular traffic flow on the streets of Dhaka, which includes different categories of roadside objects, pedestrians, and non-motorized vehicles. Subsequently, we model the side friction elements using parameters that effectively capture their characteristics. Leveraging the formulated models, we extend our microscopic road traffic simulator, DhakaSim, which has been proven to appropriately simulate the heterogeneous non-lane-based traffic in cities like Dhaka. To the best of our knowledge, the updated simulator is the only simulator capable of simulating heterogeneous traffic of cities like Dhaka while capturing its real inherent complexities, such as a large number of parked vehicles and irregular pedestrian movement. We rigorously validate the updated simulator using Google Maps data and utilize it to conduct an extensive simulation study analyzing the impacts of side friction elements. Our study reveals that the average speed of Dhaka can be reduced by up to 36.55% and the average waiting time can be increased by up to 161.3% due to side friction. Here, pedestrians exhibit a significantly more negative impact on traffic compared to other side friction elements, making them one of the leading causes of congestion on the streets of Dhaka. Moreover, while non-motorized traffic reduces t
Spectrum sensing data falsification (SSDF) attack, i.e., Byzantine attack, is one of the critical threats of the cooperative spectrum sensing where the Byzantine attackers (BAs) forward incorrect local sensing results...
详细信息
Spectrum sensing data falsification (SSDF) attack, i.e., Byzantine attack, is one of the critical threats of the cooperative spectrum sensing where the Byzantine attackers (BAs) forward incorrect local sensing results to mislead the fusion center on channel availability decisions. By using traditional voting rule, the cooperative spectrum sensing performance deteriorates significantly due to incorrect local sensing results. Then, reliability weight strategy becomes the popular solution to avoid incorrect sensing results from BAs and unreliable cognitive radio users (CRUs). However, it is very difficult to detect the attackers since they also occasionally provide correct sensing results to the fusion center for concealing the attack objective. Based on existing techniques, the BAs and CRUs may be assigned with low reliability weights or distinguished from the data fusion account. However, it is very difficult to detect the attackers since they also occasionally provide correct sensing results to the fusion center for concealing the attack objective. Then, existing techniques still suffer from BAs and negative impact of unreliable CRUs. In this paper, we propose the adaptive cooperative quality weight algorithm for mitigating the Byzantine attack issue by distinguishing the BAs and CRUs from the data fusion account while selecting only useful CRUs since the number of members in the account is also the important factor for cooperative spectrum sensing. In our proposed algorithm, we adopt a stable preference ordering towards ideal solution (SPOTIS) for determining the reliability of SUs which shows low computational complexity as compared to other reliability weight-based techniques. To achieve high sensing performance, our global decision threshold is adapted according to the reliability of reliable users. From the simulation results, our proposed algorithm significantly improves global detection probability and total error probability compared to the traditional votin
Voice is the king of communication in wireless cellular network (WCN). Again, WCNs provide two types of calls, i.e., new call (NC) and handoff call (HC). Generally, HCs have higher priority than NCs because call dropp...
详细信息
暂无评论