In the era of rapid advancements in technology, the efficient digitization of paper-based documents remains a crucial challenge across various domains. The traditional approach to document scanning often struggles wit...
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This study introduces a novel method for Discrete Fourie Transform (DFT)-based interpolation for channel estimation through the application of multiple windows in the channel impulse response. Utilizing a genetic algo...
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Insider threat detection (ITD) presents a significant challenge in cybersecurity, particularly within large and complex organizations. Traditionally, ITD has been overshadowed by the focus of external threats, resulti...
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ISBN:
(纸本)9798350362480
Insider threat detection (ITD) presents a significant challenge in cybersecurity, particularly within large and complex organizations. Traditionally, ITD has been overshadowed by the focus of external threats, resulting in less attention and development in this critical area. Conventional ITD approaches often rely heavily on event-driven approaches. On top of that, researchers developed various rule-based methods to conquer the tasks. Based on that, we often ignore the intrinsic temporal relationships that are naturally built in between events that occur in different moments. For instance, we may easily understand events with causality such as one anomalous event followed by another specific event to complete a malicious action;however, may not be aware of events that occur around 9 am every morning during working hours. In our opinion, we attempt to re-consider the temporal behavior to extract the information hidden in cyberspace activities. Specifically, some effective sentence embeddings can assist us in providing informative internal representations to summarize temporal behaviors in the temporal activity sequences to make the right judgment on insider threat detection. In this paper, we propose a novel methodology for insider threat detection that emphasizes temporal relationship modeling on top of already-matured event sequence analysis to effectively catch insider threats. The proposed approach leverages contrastive sentence embeddings to learn users' intentions in sequences, followed by the deployment of a user-level and event-level Contrastive Learning (euCL) model to incorporate temporal behaviors with user behavior embeddings. To validate the proposed methodology, we conduct extensive analyses and experiments using the publicly available CERT dataset. The results demonstrate the effectiveness and robustness of the proposed method in detecting insider threats and identifying malicious scenarios, highlighting its potential for enhancing cybersecurity measur
Deep Learning refers to a subset of Machine Learning that utilizes deep neural networks to simulate the complex decision-making process of the human brain. In recent years, DL has made remarkable progress in addressin...
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Real-time video transmission via unmanned aerial vehicles (UAVs) is significantly impacted by latency issues. Using Region of Interest (ROI) tile segmentation methods, video streaming techniques can dynamically adjust...
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Trigeminal Neuralgia (TN) is a debilitating chronic pain disorder that significantly diminishes overall well-being, making diagnosis and therapy more challenging. The quick and precise categorization of TN severity is...
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Dementia is considered a Mild Cognitive Impairment (MCI), representing a blurred transition from normal cognitive function to dementia. MCI might be a precursor to dementia being caused by various neurodegenerative di...
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This paper proposed an SVC-DASH video streaming method over the vehicular environment based on the Multi-access Edge Computing (MEC) architecture. For the streaming concern, a control scheme using the Segment-Set-base...
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Traffic congestion is a growing problem in India, largely caused by the increasing number of vehicles. To address this, creating an adaptive traffic control system has become essential. To present a solution, this pap...
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Today social media is one of the most powerful and popular tool which is expanding rapidly in the world. Many tourism websites publish tourist places data for describing places in the form of Description. Over this da...
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