Research of the aviation personnel vulnerability profile to social engineering attacks by A. K. Volkov, A. K. Volkov, L. I. Frolova

“…In the complex of aviation cybersecurity threats, which include deliberate attacks, errors of third-party companies, system errors, natural phenomena, the human factor occupies an important place. …”
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Event-triggered synchronization control for neural networks against DoS attacks by Yawei Liu, Guangyin Cui, Chen Gao

“…By choosing a suitable piecewise Lyapunov-Krasovskii functional and using several free-weighting matrices, sufficient conditions were established to ensure the exponential stability of the synchronization error system in the occurrence of DoS attacks. Furthermore, a co-design method was provided to acquire the desired non-fragile output-feedback control gain and event-triggering parameter. …”
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APT attack threat-hunting network model based on hypergraph Transformer by Yuancheng LI, Yukun LIN

“…To solve the problem that advanced persistent threat (APT) in the Internet of things (IoT) environment had the characteristics of strong concealment, long duration, and fast update iterations, it was difficult for traditional passive detection models to quickly search, a hypergraph Transformer threat-hunting network (HTTN) was proposed.The HTTN model had the function of quickly locating and discovering APT attack traces in IoT systems with long time spans and complicated information concealment.The input cyber threat intelligence (CTI) log graph and IoT system kernel audit log graph were encoded into hypergraphs by the model, and the global information and node features of the log graph were calculated through the hypergraph neural network (HGNN) layer, and then they were extracted for hyperedge position features by the Transformer encoder, and finally the similarity score was calculated by the hyperedge, thus the threat-hunting of APT was realized in the network environment of the Internet of things system.It is shown by the experimental results in the simulation environment of the Internet of things that the mean square error is reduced by about 20% compared to mainstream graph matching neural networks, the Spearman level correlation coefficient is improved by about 0.8%, and improved precision@10 is improved by about 1.2% by the proposed HTTN model.…”
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Pilot spoofing attack detection and channel estimation for secure massive MIMO by Delong Liu, Wei Wang, Yang Huang

“…Abstract Pilot spoofing attack (PSA) is an active eavesdropping attack in massive multiple‐input multiple‐output systems, where the eavesdroppers transmit the same pilot sequence as the legitimate user does to the base station to confuse the normal channel estimation during the uplink channel training phase. …”
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Collaborative filtering recommendation using fusing criteria against shilling attacks by Li Li, Zhongqun Wang, Chen Li, Linjun Chen, Yong Wang

“…Malicious users use a single method to perform shilling attacks. Intuitively, fusing multiple criteria to construct CFR can effectively resist shilling attacks. …”
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Generating Automatically Print/Scan Textures for Morphing Attack Detection Applications by Juan E. Tapia, Maximilian Russo, Christoph Busch

“…This paper presents two methods based on texture transfer techniques for the automatic generation of digital print and scan facial images, which are utilized to train a Morphing Attack Detection algorithm. Our proposed methods achieve an Equal Error Rate (EER) of 3.84% and 1.92% on the FRGC/FERET database when incorporating our synthetic and texture-transferred print/scan images at 600 dpi alongside handcrafted images, respectively.…”
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On the generalisation capabilities of Fisher vector‐based face presentation attack detection by Lázaro J. González‐Soler, Marta Gomez‐Barrero, Christoph Busch

“…A Bona Fide Presentation Classification Error Rate 100 under 17% together with an area under the receiving operating characteristic curve of over 98% can be achieved in the presence of unknown attacks. …”
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Big Data-Driven Deep Learning Ensembler for DDoS Attack Detection by Abdulrahman A. Alshdadi, Abdulwahab Ali Almazroi, Nasir Ayub, Miltiadis D. Lytras, Eesa Alsolami, Faisal S. Alsubaei

“…Our ensemble was tested on IoT-23, APA-DDoS, and additional datasets created from popular DDoS attack tools. Simulations demonstrate a recognition rate of 98.99% on IoT-23 with a 0.11% false positive rate and 99.05% accuracy with a 0.01% error on APA-DDoS, outperforming SVM, ANN-GWO, GRU-RNN, CNN, LSTM, and DBN baselines. …”
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Audio Watermarking Algorithm Against Speed Attack based on Amplitude Rearrangement by WANG Xin, HUANG Ying, NIU Baoning, WU Shiqiang, LAN Fangpeng, GUAN Hu

“…[Results] Experimental results show that the algorithm can improve the robustness against speed-up attacks while maintaining the imperceptibility of audio watermarking, with an average bit error rate less than 0.02.…”
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Detection of Emulation Attacks in Cognitive Radio Networks using Heuristic Techniques by Jabbar Mahmood, Rahim Ali Qamar, Shahzad Latif

“…The research focuses on detecting PUEAs using the time difference of arrivals (TDOA) to detect the attacker and reduce detection errors using heuristic techniques. …”
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A New QIM-Based Watermarking Method Robust to Gain Attack by Yevhen Zolotavkin, Martti Juhola

“…According to the concept some samples in predefined positions are ignored even though this produces errors in the initial stage of watermark embedding. …”
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Reasons for the increase in cyber attacks: analysis of technical and non-technical factors by A. V. Vasilyev

“…This article presents an analysis of both technical and non-technical factors contributing to the growth in volume and diversity of cyber attacks. Social interaction on the Internet contributes to the increased frequency of cyber attacks and exacerbates destructive consequences that extend beyond technical aspects, impacting societal and personal realms. …”
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Influenza infection rates, measurement errors and the interpretation of paired serology. by Simon Cauchemez, Peter Horby, Annette Fox, Le Quynh Mai, Le Thi Thanh, Pham Quang Thai, Le Nguyen Minh Hoa, Nguyen Tran Hien, Neil M Ferguson

“…After correction for measurement errors, we find that the proportion of individuals with 2-fold rises in antibody titers was too large to be explained by measurement errors alone. …”
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A New Mechanism to Improve the Detection Rate of Shilling Attacks in the Recommender Systems by javad nehriri, sasan hosseinali zadeh

“…In this paper, we use profile-based and item-based algorithms to provide a new mechanism to significantly reduce the detection error for shilling attacks.…”
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Mitigating Impact of Data Poisoning Attacks on CPS Anomaly Detection with Provable Guarantees by Sahar Abedzadeh, Shameek Bhattacharjee

“…Anomaly-based attack detection methods depend on some form of machine learning to detect data falsification attacks in smart living cyber–physical systems. …”
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Toward Secure Electronic Voting: A Survey on E-Voting Systems and Attacks by Riccardo Barelli, Mario D'Onghia, Stefano Longari

“…The trend of electronic voting has risen in recent years as an alternative to paper ballot elections, bringing meaningful benefits in terms of efficiency and error proneness. However, real-world applications have demonstrated significant vulnerabilities and susceptibility to software errors that could be exploited by malicious entities. …”
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Observer Design for Cyber-Physical Systems With State Delay and Sparse Sensor Attacks by Man Zhang, Chong Lin, Yadong Li, Bing Chen

“…The system model we studied is a class of discrete-time systems with state delay and sparse sensor attacks. In the design of the observer, a Projection Operator is utilized to determine the correct attack set, and the gain matrix will be switched accordingly. …”
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Autonomous Aircraft Tactical Pop-Up Attack Using Imitation and Generative Learning by Joao P. A. Dantas, Marcos R. O. A. Maximo, Takashi Yoneyama

“…The performances of these models were evaluated in terms of Root Mean Squared Error (RMSE), coefficient of determination (R2), training time, and inference time. …”
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Improving Face Presentation Attack Detection Through Deformable Convolution and Transfer Learning by Shakeel Muhammad Ibrahim, Muhammad Sohail Ibrahim, Shujaat Khan, Young-Woong Ko, Jeong-Gun Lee

“…The method achieves a half total error rate (HTER) of 0.0% on both the Replay-Attack and Replay-Mobile datasets, 1.26% on ROSE-Youtu, 4.88% on SiW-Mv2, and an ACER of 0.208% on OULU-NPU, outperforming several existing methods. …”
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Secure and Reliable IPTV Multimedia Transmission Using Forward Error Correction by Chi-Huang Shih, Yeong-Yuh Xu, Yao-Tien Wang

“…The proposed secure FEC utilizes the characteristics of FEC including the FEC-encoded redundancies and the limitation of error correction capacity to protect the multimedia packets against the malicious attacks and data transmission errors/losses. …”
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