A Secure RFID Authentication Protocol Adopting Error Correction Code by Chien-Ming Chen, Shuai-Min Chen, Xinying Zheng, Pei-Yu Chen, Hung-Min Sun

“…Compared with other lightweight protocols, the proposed protocol provides stronger resistance to tracing attacks, compromising attacks and replay attacks. …”
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Prediction of Future Terrorist Activities Using Deep Neural Networks by M. Irfan Uddin, Nazir Zada, Furqan Aziz, Yousaf Saeed, Asim Zeb, Syed Atif Ali Shah, Mahmoud Ahmad Al-Khasawneh, Marwan Mahmoud

“…Or what type of weapon is going to be used in the attack? Or what type of attack is going to be carried out? …”
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Risk factors for loss to follow-up in patients with gout: A Korean prospective cohort study. by Hyunsue Do, Chang-Nam Son, Hyo Jin Choi, Ji Hyoun Kim, Min Jung Kim, Kichul Shin, Sang-Hyon Kim, Byoongyong Choi, You-Jung Ha, Joong Kyong Ahn, Hyun-Ok Kim, Sung Won Lee, Chang Hoon Lee, Ran Song, Kyeong Min Son, Seung-Geun Lee, Ki Won Moon

“…Logistic regression identified frequent gout attacks, concerns about attacks, anxiety, impaired mobility, and EQ-5D scores as significant predictors of LTFU.…”
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Enhanced Grey Wolf Optimization (EGWO) and random forest based mechanism for intrusion detection in IoT networks by Saad Said Alqahtany, Asadullah Shaikh, Ali Alqazzaz

“…These connected devices pose a challenge to cybersecurity systems due attacks in network communications. Such attacks have continued to threaten the operation of systems and end-users. …”
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Improved integral cryptanalysis of SPNbox in digital rights management systems by Jun Liu, Dachao Wang, Yupu Hu, Jie Chen, Baocang Wang

“…On this basis, we propose new competitive 3‐round key recovery attacks with lower complexities. Particularly, the improved attack on 3‐round SPNbox‐32 only requires 232 chosen plaintexts, whereas the current best attack necessitates 262 chosen plaintexts. …”
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Enhancing Industrial Cybersecurity: Insights From Analyzing Threat Groups and Strategies in Operational Technology Environments by Mukund Bhole, Thilo Sauter, Wolfgang Kastner

“…We aim to provide relevant stakeholders (manufacturers, asset owners and system integrators), including Chief Information Security Officers, with information on emerging threat groups, attack victims and their locations, the origins of attacks, the tools and types of tools used, and the motivations behind these attacks. …”
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A sector fast encryption algorithm for color images based on one-dimensional composite sinusoidal chaos map. by Ye Tao, Wenhua Cui, Shanshan Wang, Yayun Wang

“…The algorithm can also resist some common attacks and accidents, such as exhaustion attack, differential attack, noise attack, information loss and so on.…”
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ARCS: Adaptive Reinforcement Learning Framework for Automated Cybersecurity Incident Response Strategy Optimization by Shaochen Ren, Jianian Jin, Guanchong Niu, Yang Liu

“…The increasing sophistication and frequency of cyber attacks necessitate automated and intelligent response mechanisms that can adapt to evolving threats. …”
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Analisis Kinerja Intrusion Detection System Berbasis Algoritma Random Forest Menggunakan Dataset Unbalanced Honeynet BSSN by Kuni Inayah, Kalamullah Ramli

“…The model classifies 10 (ten) classifications, namely Benign, Information Leak, Malware, Trojan Activity, Information Gathering, APT, Exploit, Web Application Attack, Denial of Service (DoS), and other types of attacks. …”
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The Female Body as a Site of Patriarchal Power Play: by Liton Chakraborty Mithun

“…The victims of sexual attacks undergo psychological trauma during and after the war. …”
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Method based on contrastive learning for fine-grained unknown malicious traffic classification by Yifeng WANG, Yuanbo GUO, Qingli CHEN, Chen FANG, Renhao LIN

“…In order to protect against unknown threats and evasion attacks, a new method based on contrastive learning for fine-grained unknown malicious traffic classification was proposed.Specifically, based on variational auto-encoder (CVAE), it included two classification stages, and cross entropy and reconstruction errors were used for known and unknown traffic classification respectively.Different form other methods, contrastive learning was adopted in different classification stages, which significantly improved the classification performance of the few-shot and unknown (zero-shot) classes.Moreover, some techniques (e.g., re-training and re-sample) combined with contrastive learning further improved the classification performance of the few-shot classes and the generalization ability of model.Experimental results indicate that the proposed method has increased the macro recall of few-shot classes by 20.3% and the recall of unknown attacks by 9.1% respectively, and it also has protected against evasion attacks on partial classes to some extent.…”
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Channel-space endogenous anti-jamming method based on multi-reconfigurable intelligent surface by Yonggang ZHU, Yifu SUN, Fuqiang YAO, Cheng LI, Wenlong GUO, Kang AN

“…In view of the concern that the traditional anti-jamming method based on jamming recognition is challenging to defend against both the unknown and the intelligent jamming attacks, a dynamic, heterogeneous, and redundant channel-space anti-jamming technique was proposed by adopting multiple reconfigurable intelligent surface (RIS), which facilitated the exploitation of channels’ resources for combating with the unknown jamming attacks.To elaborate, a channel-space endogenous anti-jamming method was proposed by leveraging the optimization of both the RIS’ coefficients and the multiple RIS’ on-off status.Firstly, after decoupling the tightly coupled variables, the optimal closed-form solutions of transmit precoder, RIS’ coefficients, and receive decoder could be derived under the alternative optimization framework.Then, the greedy algorithm was adopted to optimize the multiple RIS’ on-off status for obtaining better anti-jamming communications, and the convergence and the computation complexity of the proposed method was analyzed.Theoretical analysis and simulation results show that the proposed method can effectively defend against the uncertain jamming attacks.…”
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Black Turpentine Beetle, Dendroctonus terebrans (Olivier) (Insecta: Coleoptera: Curculionidae: Scolytinae) by Albert E. Mayfield, John L. Foltz

“…Light attacks may kill only localized sections of phloem tissue, but numerous attacks per stem result in tree mortality. …”
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Method of constructing an anonymous graph based on information loss estimation by Jie SU, Shuai LIU, Zhi-yong LUO, Guang-lu SUN

“…A potential attack based on degree information by re-identifying target vertexes from a sequence of published graphs was analyzed.To deal with this kind of attack,a k-anonymous graph stream constructing method based on information loss estimation was provided.Information loss caused by re-constructing graph was controlled by using the method of attributes generalization of nodes and the structure generalization of sub-graph.The disturbance in sub-graph was forbidden to prevent the attack.The method of measuring the information loss of nodes and structures during the anonymous process due to re-construction of graph was defined.A k-anonymity cluster algorithm based on greedy clustering algorithm was build,which realized anonymous partition according to the information loss.Finally,a method of constructing anonymous social network for the evolving social network with the least information loss was provided.The experiments on medical diagnostic data set show that the algorithm of constructing anonymous graph based on the information loss estimation can be used to control the loss of information.…”
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Secure Multicast Routing Algorithm for Wireless Mesh Networks by Rakesh Matam, Somanath Tripathy

“…Existing secure routing protocols that address different active attacks are still vulnerable due to subtle nature of flaws in protocol design. …”
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Black Turpentine Beetle, Dendroctonus terebrans (Olivier) (Insecta: Coleoptera: Curculionidae: Scolytinae) by Albert E. Mayfield, John L. Foltz

“…Light attacks may kill only localized sections of phloem tissue, but numerous attacks per stem result in tree mortality. …”
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A Novel k-out-of-n Oblivious Transfer Protocol from Bilinear Pairing by Jue-Sam Chou

“…In most cases, they are treated as cryptographic primitives and are usually executed without consideration of possible attacks that might frequently occur in an open network, such as an impersonation, replaying, or man-in-the-middle attack. …”
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Research on distributed identity authentication mechanism of IoT device based on blockchain by Chen TAN, Meijuan CHEN, Ebenezer ACKAH Amuah

“…Aiming to solve problems of the low compatibility and weak anti-attack ability of the Internet of things (IoT) centralized platform in the device identity authentication process,a blockchain-based distributed IoT device identity authentication architecture was proposed.The digital identity and related information were stored in the new block data structure,and a distributed IoT device identity authentication mechanism was proposed based on the cryptography related knowledge.At the same time,a device digital certificate issuance process and a detailed process of the identity authentication were designed.The security analysis of the proposed mechanism were carried out from the aspects of power constraints,device privacy protection,and ability to resist attacks among various entities.The performance of three aspects,which were security attributes,computational overhead and storage overhead,were compared and analyzed.The results show that the proposed identity authentication mechanism can resist a variety of malicious attacks,achieve highly secure distributed IoT identity authentication,and has certain advantages in the performance.…”
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Exact Recovery for System Identification With More Corrupt Data Than Clean Data by Baturalp Yalcin, Haixiang Zhang, Javad Lavaei, Murat Arcak

“…We emphasize that the attack vectors are allowed to be correlated with each other in this work. …”
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Developing an Intelligent System for Efficient Botnet Detection in IoT Environment by Ramesh Singh Rawat, Manoj Diwakar, Umang Garg, Prakash Srivastava

“…Smart technological instruments and Internet of Things (IoT) systems are now targeted by network attacks because of their widespread rising use. Attackers can take over IoT devices via botnets, and pre-configured attack vectors, and use them to do harmful actions. …”
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