Cyber ranges: survey and perspective by ZOU Xing, HU Ning, GU Zhaoquan, JIA Yan

“…Various cyber attacks occurred frequently. Increasing attention has been being paid to cyber security by many countries. …”
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Method for Detecting Manipulated Compilation of Sensing Reports in Wireless Sensor Networks by Hae Young Lee

“…The existing solutions are vulnerable to such a type of security attacks, called manipulated compilation attacks (MCAs), since they assume that CHs are uncompromised. …”
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Réponse à certaines critiques sur l’approche neurolinguistique (ANL) by Claude Germain

“…In 2022 appeared the first in a series of articles (Antier, 2022a, 2022b, 2023) indiscriminately criticizing in a scathing manner the authors of the neurolinguistic approach (NLA) as well as their promoters, in particular attacking my work on NLA (Germain, 2017). This article is intended as a personal reaction to these attacks. …”
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Postfire Burnt-Wood Management Affects Plant Damage by Ungulate Herbivores by Jorge Castro

“…I analyze the effect of post-fire burnt wood management on herbivore attack on a woody plant species (Ulex parviflorus). …”
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Building an African Counter-Terrorism Architecture by Jolaade Omede, Arinze Ngwube

“… Following September 11, 2001, terrorist attacks in the world trade centre in the United States of America, the phenomenon of terrorism has attracted increasing global attention. …”
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Overview of detection techniques for malicious social bots by Rong LIU, Bo CHEN, Ling YU, Ya-shang LIU, Si-yuan CHEN

“…The attackers use social bots to steal people’s privacy,propagate fraud messages and influent public opinions,which has brought a great threat for personal privacy security,social public security and even the security of the nation.The attackers are also introducing new techniques to carry out anti-detection.The detection of malicious social bots has become one of the most important problems in the research of online social network security and it is also a difficult problem.Firstly,development and application of social bots was reviewed and then a formulation description for the problem of detecting malicious social bots was made.Besides,main challenges in the detection of malicious social bots were analyzed.As for how to choose features for the detection,the development of choosing features that from static user features to dynamic propagation features and to relationship and evolution features were classified.As for choosing which method,approaches from the previous research based on features,machine learning,graph and crowd sourcing were summarized.Also,the limitation of these methods in detection accuracy,computation cost and so on was dissected.At last,a framework based on parallelizing machine learning methods to detect malicious social bots was proposed.…”
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An Adaptive Multilevel Security Framework for the Data Stored in Cloud Environment by Sudha Devi Dorairaj, Thilagavathy Kaliannan

“…Any common multiple method for all data becomes vulnerable when the common security pattern is identified at the event of successful attack on any information and also encourages more attacks on all other data. …”
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Household transmission of SARS-CoV-2 in five US jurisdictions: Comparison of Delta and Omicron variants. by Julia M Baker, Jasmine Y Nakayama, Michelle O'Hegarty, Andrea McGowan, Richard A Teran, Stephen M Bart, Lynn E Sosa, Jessica Brockmeyer, Kayla English, Katie Mosack, Sanjib Bhattacharyya, Manjeet Khubbar, Nicole R Yerkes, Brooke Campos, Alina Paegle, John McGee, Robert Herrera, Marcia Pearlowitz, Thelonious W Williams, Hannah L Kirking, Jacqueline E Tate

“…Overall transmission risk was similar in households with Omicron (attack rate = 47.0%) compared to Delta variant (attack rate = 48.0%) circulation. …”
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PermGuard: A Scalable Framework for Android Malware Detection Using Permission-to-Exploitation Mapping by Arvind Prasad, Shalini Chandra, Mueen Uddin, Taher Al-Shehari, Nasser A. Alsadhan, Syed Sajid Ullah

“…The increasing reliance on mobile devices significantly raises the risk of malware attacks, especially for non-technical users who often grant permissions without thorough evaluation, leading to potentially devastating effects. …”
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Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

“…The dataset used for evaluation, the Industrial Control System (ICS) Cyber Attack Dataset (Power System Dataset) consists of various FDIA scenarios simulated in a smart grid environment. …”
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Boosting Cyberattack Detection Using Binary Metaheuristics With Deep Learning on Cyber-Physical System Environment by Alanoud Al Mazroa, Fahad R. Albogamy, Mohamad Khairi Ishak, Samih M. Mostafa

“…Cyberattack detection employing deep learning (DL) contains training neural networks to identify patterns indicative of malicious actions within system logs or network traffic, allowing positive classification and mitigation of cyber-attacks. By leveraging the integral ability of DL methods to learn complex representations, this technique enhances the accuracy and efficiency of detecting diverse and growing cyber-attacks. …”
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Temporal Convolutional Network Approach to Secure Open Charge Point Protocol (OCPP) in Electric Vehicle Charging by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, Muhammad Sheraz, Teong Chee Chuah

“…In this study, we propose a novel temporal convolutional network (TCN) to enhance EVCS security by rapidly detecting Open Charge Point Protocol (OCPP) attacks. Our model was trained and tested on the latest CICEVSE2024 dataset, which encompasses attacks targeting EVCS communication protocols, including OCPP and ISO15118, during charging and idle states. …”
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The hidden cost of digital learning: a cross-sectional study assessing the prevalence of computer vision syndrome (CVS) among medical students in Jordan by Hazim Alkousheh, Yara Alkousheh, Rana Qawaqzeh, Layan Al Juneidi, Lina Al-Zerikat, Ayat Hussain, Motasem Al-latayfeh

“…Moderate positive correlations were found between the number of symptoms and the frequency of monthly symptom attacks and between the duration and frequency of symptom attacks (p<0.001).Conclusion Our study found a 56.3% prevalence of CVS among Jordanian medical students, with over 80% having ocular and extraocular symptoms. …”
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Deep learning-based encryption scheme for medical images using DCGAN and virtual planet domain by Manish Kumar, Aneesh Sreevallabh Chivukula, Gunjan Barua

“…The robustness against key sensitivity, noise, cropping attacks, and adversarial attacks are shown in Figs. 15–18, 22–23, and 24. …”
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Ketahanan dan Kualitas Visual Watermarked Image Menggunakan Integer Wavelet Transform (IWT) dan Chinese Remainder Theorem (CRT) by Bambang Harjito, Eka Tri Kustanti

“…This paper proposes a digital watermarking method using a combination of Integer Wavelet Transform (IWT) and Chinese Remainder Theorem (CRT) to produce watermarking with good visual quality and resistance from several attacks. The results obtained that Peak Signal-to-Noise Ratio (PSNR)  values are close to 1 and Normalized Correlation Coefficient (NCC)  equal to 0.71337. shows the IWT and CRT methods are able to produce watermarked images with good visual quality or imperceptibility and are able to provide image resistance to several attacks such as gaussian, salt & pepper and JPEG2000 compression but are not resistant to rotation and contrast attacks because the NCC value is below 0.5 …”
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An Efficient and Lightweight Source Privacy Protecting Scheme for Sensor Networks Using Group Knowledge by Zhiqiang Ruan, Wei Liang, Decai Sun, Haibo Luo, Fanyong Cheng

“…We analyze the ability of our proposed scheme to withstand different attacks and demonstrate its efficiency in terms of overhead and functionality when compared to existing works.…”
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EAP-Based Group Authentication and Key Agreement Protocol for Machine-Type Communications by Rong Jiang, Chengzhe Lai, Jun Luo, Xiaoping Wang, Hong Wang

“…Detailed security analysis has shown that the proposed EG-AKA protocol is secure in terms of user and group identity protection and resistance to several attacks. Furthermore, formal verification implemented in AVISPA proves that the proposed protocol is secure against various malicious attacks. …”
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DETECTING WEB-BASED BOTNETS USING A WEB PROXY AND A CONVOLUTIONAL NEURAL NETWORK by Trần Đắc Tốt, Phạm Tuấn Khiêm, Phạm Nguyễn Huy Phương

“…Botnets are increasingly becoming the most dangerous threats in the field of network security, and many different approaches to detecting attacks from botnets have been studied. Whatever approach is used, the evolution of the botnet's nature and the set of defined rules for detecting botnets can affect the performance of botnet detection systems. …”
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Tophaceous Gout and Renal Insufficiency: A New Solution for an Old Therapeutic Dilemma by Anne-Kathrin Tausche, Carsten Wunderlich, Martin Aringer

“…Monthly polyarthritis attacks were accompanied by subcutaneous tophi. Serum uric acid levels were constantly above 600 μmol/L (10 mg/dL). …”
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A fuzzy logic-based risk evaluation and precaution level estimation of explosive, flammable, and toxic chemicals for preventing damages by Abdul Aziz, Md Masum Suzon, Rakib Hasan

“…Chemical industries are highly vulnerable to accidental events or terrorist attacks due to their processing, storage, and transportation of explosive, flammable, and toxic materials. …”
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