Hybridization of Swarm for Features Selection to Modeling Heart Attack Data by Omar Shakir, Ibrahim Saleh

“…Predicting heart attacks using machine learning is an important topic. …”
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An attack resistant key predistribution scheme for wireless sensor networks by Priyanka Ahlawat, Mayank Dave

“…The proposed scheme aims to make the network more resistant against the node capture attacks. Adversary is assumed to be intelligent that tends to exploit different vulnerabilities present in network to build an attack matrix. …”
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Exploring presentation attack vulnerability and usability of face recognition systems by Heinz Hofbauer, Luca Debiasi, Susanne Kränkl, Andreas Uhl

“…While specifics of the systems cannot be gone in‐depth under test (due to NDAs), the results of the evaluation of liveness detection (or presentation attack detection) with different complexity levels and template comparison performance are presented. …”
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Preimage and collision attacks on reduced Ascon using algebraic strategies by Qinggan Fu, Ye Luo, Qianqian Yang, Ling Song

“…In addition, we construct different 2-round connectors using the linearization of the inverse of S-boxes and successfully extend the collision attack to 4 rounds and 5 rounds of Ascon-HASH with complexities of $$2^{18}$$ 2 18 and $$2^{41}$$ 2 41 , respectively. …”
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Towards distinguishing trust based attacks in an IoV network by Yingxun Wang, Adnan Mahmood, Mohamad Faizrizwan Mohd Sabri, Hushairi Zen

“…Nevertheless, trust-based attacks also present a formidable challenge. Therefore, in this paper, an IoV-based trust management heuristic has been envisaged that takes into account both direct trust and indirect trust to ascertain the behaviors of the vehicles vis-à-vis time in a bid to detect various trust-based attacks, i.e., zig-zag attacks, self-promoting attacks, on-off attacks, and opportunistic attacks, along with the attackers’ multiple attacking strategies. …”
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Gender differentiation in tactical options in defense and attack on beach handball by Konstantinos Gkagkanas, Dimitris Hatzimanouil, Vasilis Skandalis

“…The ꭓ2-test was used to compare the differences between the formations in defense and attack. …”
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Research of the aviation personnel vulnerability profile to social engineering attacks by A. K. Volkov, A. K. Volkov, L. I. Frolova

“…In this work, this negative phenomenon is considered from the point of view of the aviation personnel vulnerability to social engineering attacks. Such type of attack by an attacker involves a set of applied psychological and analytical techniques that facilitate the receipt of confidential information or the violation of information security rules by legitimate company employees. …”
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Backdoor Attack Against Dataset Distillation in Natural Language Processing by Yuhao Chen, Weida Xu, Sicong Zhang, Yang Xu

“…We employ several widely used datasets to assess how different architectures and dataset distillation techniques withstand our attack. …”
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LDoS attack detection method based on simple statistical features by Xueyuan DUAN, Yu FU, Kun WANG, Bin LI

“…Traditional low-rate denial of service (LDoS) attack detection methods were complex in feature extraction, high in computational cost, single in experimental data background settings, and outdated in attack scenarios, so it was difficult to meet the demand for LDoS attack detection in a real network environment.By studying the principle of LDoS attack and analyzing the features of LDoS attack traffic, a detection method of LDoS attack based on simple statistical features of network traffic was proposed.By using the simple statistical features of network traffic packets, the detection data sequence was constructed, the time correlation features of input samples were extracted by deep learning technology, and the LDoS attack judgment was made according to the difference between the reconstructed sequence and the original input sequence.Experimental results show that the proposed method can effectively detect the LDoS attack traffic in traffic and has strong adaptability to heterogeneous network traffic.…”
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Improved meet‐in‐the‐middle attacks on reduced‐round Joltik‐BC by Manman Li, Shaozhen Chen

“…Utilising the subtweakey difference cancellation, the freedom of the tweak and the differential enumeration, they attack on nine‐round Joltik‐BC‐64‐64 by constructing a precise six‐round meet‐in‐the‐middle distinguisher with 253 plaintext–tweak combinations, 252.91 Joltik‐BC blocks and 254.1 nine‐round Joltik‐BC‐64‐64 encryptions. …”
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A simple and efficient attack on the Merkle-Hellman knapsack cryptosystem. by Jingguo Bi, Lei Su, Haipeng Peng, Lin Wang

“…The most time-consuming part of Shamir's attack is to recover the critical intermediate parameters by solving an integer programming problem with a fixed number of variables, whose worst-case complexity is exponential of the number of variables. …”
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Goalie: Defending Against Correlated Value and Sign Encoding Attacks by Rongfei Zhuang, Ximing Fu, Chuanyi Liu, Peiyi Han, Shaoming Duan

“…In this paper, we propose a method, namely Goalie, to defend against the correlated value and sign encoding attacks used to steal shared data from data trusts. …”
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Investigating imperceptibility of adversarial attacks on tabular data: An empirical analysis by Zhipeng He, Chun Ouyang, Laith Alzubaidi, Alistair Barros, Catarina Moreira

“…Adversarial attacks are a potential threat to machine learning models by causing incorrect predictions through imperceptible perturbations to the input data. …”
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An evaluation of methods for detecting false data injection attacks in the smart grid by Sarita Paudel

“…In this paper, we analyze four different false data injection attacks on PMU measurements and investigate different methods to detect such attacks. …”
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A Neutrosophic Approach to Robust Web Security: Mitigating XSS Attacks by A. A. Salama, El-Said F. Aboelfotoh, Hazem M. El-Bakry, Hazem M. El-Bakry, Ahmed K. Essa, Ramiz Sabbagh, Doaa S. El-Morshedy

“…This way the system understands the different types of attacks and allows the system to act more effectively. …”
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On the Validity of Traditional Vulnerability Scoring Systems for Adversarial Attacks Against LLMs by Atmane Ayoub Mansour Bahar, Ahmad Samer Wazan

“…The results indicate that existing scoring systems yield vulnerability scores with minimal variation across different attacks, supporting the hypothesis that current vulnerability metrics are limited in evaluating AAs on LLMs, and highlighting the need for the development of more flexible, generalized metrics tailored to such attacks.…”
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Adversarial Attacks Defense Method Based on Multiple Filtering and Image Rotation by Feng Li, Xuehui Du, Liu Zhang

“…Furthermore, the fixed filtering parameters cannot effectively defend against the adversarial attack. This paper proposes a novel defense method based on different filter parameters and randomly rotated filtered images. …”
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Contrastive Learning Algorithm for Low-Resource Cryptographic Attack Event Detection by Peng Luo, Rangjia Cai, Yuanbo Guo

“…Thus, we propose a method CLAD: Contrastive Learning Algorithm for Detecting Low-resource Cryptographic Attack Event. By comparing similarities and differences between samples, richer feature representations can be extracted. …”
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Learning to Learn Sequential Network Attacks Using Hidden Markov Models by Timothy Chadza, Konstantinos G. Kyriakopoulos, Sangarapillai Lambotharan

“…The global surge of cyber-attacks in the form of sequential network attacks has propelled the need for robust intrusion detection and prediction systems. …”
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Investigating the Transferability of TOG Adversarial Attacks in YOLO Models in the Maritime Domain by Phornphawit Manasut, Md Saleh Ibtasham, Zeynep Yaradanakul, Sepinoud Azimi, Sebastien Lafond, Bogdan Iancu

“…This study investigates the transferability of one such adversarial attack type, the Targeted Objectness Gradient (TOG), on different variations of the YOLO architecture to formally assess its vulnerability under different scenarios in the maritime domain. …”
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