Showing 1,661 - 1,680 results of 9,720 for search '"security"', query time: 0.08s Refine Results
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    Singapore Government Securitization Measures against Transboundary Haze Pollution as a Non-Traditional Security Threat by Muhammad Ramli

    Published 2025-01-01
    “…It can be inferred that the government possesses complete authority to secure the smog issue. The community's response is critical in determining the success of haze securitization. …”
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  7. 1667

    Quantum secure patient login credential system using blockchain for electronic health record sharing framework by M. Natarajan, A. Bharathi, C. Sai Varun, Shitharth Selvarajan

    Published 2025-02-01
    “…This study proposes a secure Patient Login Credential System (PLCS) for EHRS. …”
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  8. 1668

    Intelligent Beam-Hopping-Based Grant-Free Random Access in Secure IoT-Oriented Satellite Networks by Zhongliang Deng, Yicheng Liao

    Published 2025-01-01
    “…This research presents an intelligent beam-hopping-based grant-free random access (GFRA) architecture designed for secure Internet of Things (IoT) communications in Low Earth Orbit (LEO) satellite networks. …”
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    Determinants of food security indicators in Bahir Dar City, Ethiopia: a focus on female-headed households by Getenet Ewunetu Tegegne, Arega Bazezew Berlie, Demsew Mengistie, Abiy Yigzaw

    Published 2025-01-01
    “…This study aims to identify the determinants of food security among female-headed households across three sub-cities and six kebele administrations in Bahir Dar. …”
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    Towards Secure Internet of Things: A Coercion-Resistant Attribute-Based Encryption Scheme with Policy Revocation by Yuan Zhai, Tao Wang, Yanwei Zhou, Feng Zhu, Bo Yang

    Published 2025-01-01
    “…Moreover, the scheme employs attribute-based encryption to secure IoT data, enabling fine-grained access control and dynamic user access management, providing a secure and flexible solution for vast IoT data. …”
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    Security Risk Analysis of Active Distribution Networks with Large-Scale Controllable Loads under Malicious Attacks by Jiaqi Liang, Yibei Wu, Jun’e Li, Xiong Chen, Heqin Tong, Ming Ni

    Published 2021-01-01
    “…First, we analyze the security threats faced by industrial controllable load, civil controllable load, and the gains and losses of attacks on the distribution networks. …”
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    Autonomous security analysis and penetration testing model based on attack graph and deep Q-learning network by Cheng FAN, Guoqing HU, Taojie DING, Zhanhua ZHANG

    Published 2023-12-01
    “…With the continuous development and widespread application of network technology, network security issues have become increasingly prominent.Penetration testing has emerged as an important method for assessing and enhancing network security.However, traditional manual penetration testing methods suffer from inefficiency,human error, and tester skills, leading to high uncertainty and poor evaluation results.To address these challenges, an autonomous security analysis and penetration testing framework called ASAPT was proposed, based on attack graphs and deep Q-learning networks (DQN).The ASAPT framework was consisted of two main components:training data construction and model training.In the training data construction phase, attack graphs were utilized to model the threats in the target network by representing vulnerabilities and possible attacker attack paths as nodes and edges.By integrating the common vulnerability scoring system (CVSS) vulnerability database, a “state-action”transition matrix was constructed, which depicted the attacker’s behavior and transition probabilities in different states.This matrix comprehensively captured the attacker’s capabilities and network security status.To reduce computational complexity, a depth-first search (DFS) algorithm was innovatively applied to simplify the transition matrix, identifying and preserving all attack paths that lead to the final goal for subsequent model training.In the model training phase, a deep reinforcement learning algorithm based on DQN was employed to determine the optimal attack path during penetration testing.The algorithm interacted continuously with the environment, updating the Q-value function to progressively optimize the selection of attack paths.Simulation results demonstrate that ASAPT achieves an accuracy of 84% in identifying the optimal path and exhibits fast convergence speed.Compared to traditional Q-learning, ASAPT demonstrates superior adaptability in dealing with large-scale network environments, which could provide guidance for practical penetration testing.…”
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    A secure and robust color image watermarking method using SVD and GAT in the multiresolution DCHWT domain by Boubakeur Latreche, Hilal Naimi, Slami Saadi

    Published 2023-11-01
    “…In this approach, the pre-processing phase employs successive generalized Arnold transforms to encrypt the RGB watermark layers, significantly enhancing the security of the watermarking algorithm. Subsequently, the blue layer of the host image undergoes R-level 2D-DCHWT processing. …”
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