Analysis of Urban Road Network Robustness under Different Attack Conditions by Shuang tan, Lu Zhang

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Research on the Model of Industrial Interconnection Intelligent Manufacturing Supply and Demand Network and Its Robustness by Jianjia He, Tianyuan Zheng

“…The experimental results show that under the four different attack algorithms, compared with the BA model, the two models proposed in this paper have stronger robustness. …”
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Energy Evolution Characteristics and Performance Parameter Degradation of Rubber-Mixed Concrete in Sulfate Attack Environment by Xiu-ling Chen

“…The degradation degree was measured from the effective porosity, relative dynamic elastic modulus, SO42− concentration, and SEM microstructure observation after different attack times. The energy analysis method is used to study the evolution law of total strain energy, elastic strain energy, and dissipated strain energy of NC and RC in the process of deformation and failure after different attack times, and the influence of sulfate attack on concrete is explored from the perspective of energy. …”
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Multi-stage detection method for APT attack based on sample feature reinforcement by Lixia XIE, Xueou LI, Hongyu YANG, Liang ZHANG, Xiang CHENG

“…Given the problems that the current APT attack detection methods were difficult to perceive the diversity of stage flow features and generally hard to detect the long duration APT attack sequences and potential APT attacks with different attack stages, a multi-stage detection method for APT attack based on sample feature reinforcement was proposed.Firstly, the malicious flow was divided into different attack stages and the APT attack identification sequences were constructed by analyzing the characteristics of the APT attack.In addition, sequence generative adversarial network was used to simulate the generation of identification sequences in the multi-stage of APT attacks.Sample feature reinforcement was achieved by increasing the number of sequence samples in different stages, which improved the diversity of multi-stage sample features.Finally, a multi-stage detection network was proposed.Based on the multi-stage perceptual attention mechanism, the extracted multi-stage flow features and identification sequences were calculated by attention to obtain the stage feature vectors.The feature vectors were used as auxiliary information to splice with the identification sequences.The detection model’s perception ability in different stages was enhanced and the detection accuracy was improved.The experimental results show that the proposed method has remarkable detection effects on two benchmark datasets and has better effects on multi-class potential APT attacks than other models.…”
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Multi-stage detection method for APT attack based on sample feature reinforcement by Lixia XIE, Xueou LI, Hongyu YANG, Liang ZHANG, Xiang CHENG

“…Given the problems that the current APT attack detection methods were difficult to perceive the diversity of stage flow features and generally hard to detect the long duration APT attack sequences and potential APT attacks with different attack stages, a multi-stage detection method for APT attack based on sample feature reinforcement was proposed.Firstly, the malicious flow was divided into different attack stages and the APT attack identification sequences were constructed by analyzing the characteristics of the APT attack.In addition, sequence generative adversarial network was used to simulate the generation of identification sequences in the multi-stage of APT attacks.Sample feature reinforcement was achieved by increasing the number of sequence samples in different stages, which improved the diversity of multi-stage sample features.Finally, a multi-stage detection network was proposed.Based on the multi-stage perceptual attention mechanism, the extracted multi-stage flow features and identification sequences were calculated by attention to obtain the stage feature vectors.The feature vectors were used as auxiliary information to splice with the identification sequences.The detection model’s perception ability in different stages was enhanced and the detection accuracy was improved.The experimental results show that the proposed method has remarkable detection effects on two benchmark datasets and has better effects on multi-class potential APT attacks than other models.…”
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Research of location privacy protection in wireless sensor network by Ren-ji HUANG, Qing YE, Qian WU

“…For deeply studying and solving the problems of location privacy protection in WSN,characteristics and models of location privacy protection were analyzed,schemes of location privacy protection were categorized by source,base station and the classification of their technologies.The merits and demerits in different attack types,security,efficiency and energy consumption were compared and the future research orientation was previewed.…”
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Cryptographic secrecy of steganographic matrix encoding by Jia-yong CHEN, Jiu-fen LIU, Yue-fei ZHU, Wei-ming ZHANG

“…Based on an information theory model,the cryptographic security of matrix encoding,which can be applied in steganographic codes or wet paper codes,under different attack conditions was studied.The cryptographic security about matrix encoding under the condition of known-cover attack with key equivocation,message equivocation and unicity distance of stego-key was presented.The result that n groups of differential equations could sufficiently recover the share key of matrix encoding under the condition of chosen-stego attack was pointed out.…”
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Attack signature generation by traceable dynamic taint analysis by Yu LIU, Mei-ning NIE, Pu-rui SU, Deng-guo FENG

“…Most of known attack signature generation systems took either black-box method or white-box method,both of which were limited in several aspects,such as costing a long time to capture sufficient samples,demanding arduous manual analysis and requiring source code of the vulnerable program.An attack signature generation method based on an innovative traceable dynamic taint analysis framework was proposed.By monitoring the vulnerable process execution,the executing trace and the constrain conditions exactly related to input data exploiting the vulnerability was extracted.Finally,by restoring the execution context and supplementing the determinant statements an executable Turing machine signature was attained.A prototype system was implemented and evaluated with different attack samples,which proved that the proposed method was able to generate accurate attack signature fast.…”
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Double reputation and multi-angle weight-based cooperative spectrum sensing method against SSDF attacks by Zhiguo SUN, Zhao WANG, Zengmao CHEN, Rongchen SUN

“…In order to improve the ability of cooperative spectrum sensing to withstand spectrum sensing data falsification (SSDF) attacks, a double reputation and multi-angle weight-based cooperative spectrum sensing (DRMW-CSS) method was proposed.Firstly, a scoring reputation was obtained by multiple iterations of historical local decision results, and an accuracy reputation was calculated on this basis.Secondly, secondary users (SU) were screened by double reputation and multiple reputation thresholds.Then, the impact of SSDF attacks on the screening method was judged and divided into three situations.Finally, the final global decision was made using the corresponding multi-angle weight data fusion decision method according to different situations.Simulation results show that the proposed method has good sensing accuracy when facing SSDF attacks with different attack strategies and probabilities, and has better anti-attack capability compared to traditional methods.…”
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Construction of VAE-GRU-XGBoost intrusion detection model for network security. by Yu Chen, Xiaohong Zheng, Nan Wang

“…In the confusion matrix experiment, the model achieved classification accuracy greater than 0.91 for different attack traffic samples in both the training and testing sets. …”
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Power analysis attack of HMAC based on SM3 by Zhi-bo DU, Zhen WU, Min WANG, Jin-tao RAO

“…The current power analysis attack of HMAC based on SM3 applies only to the object,on which there is the Hamming weight and Hamming distance information leakage at the same time.there is only a single information leakage mode on the attack object,then the attack methods don't work.To solve the limitations of the current attack methods,a novel method of the power analysis attack of HMAC based on SM3 was proposed.The different attack object and their related va-riables were selected in each power analysis attack.The attacks were implemented according to the Hamming distance mod-el or Hamming weight model of the intermediate variables.After several power analysis attacked on the first four rounds of SM3,the equations that consists of the results proposed of all the power analysis attacks were obtained.The ultimate attack object is derived by getting the solution of the equations.The experimental results show that the oposed attack method was effective.The method can be used universally because its being available for both the situation of co-exist of hamming weight with Hamming distance,and that of either the Hamming weight or choosing the Hamming distance model existence.…”
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LDoS attack detection method based on traffic classification prediction by Liang Liu, Yue Yin, Zhijun Wu, Qingbo Pan, Meng Yue

“…The experimental results show that the global LDoS attack traffic detection method based on the Hurst index and GBDT algorithm achieves better detection results under different attack rates.…”
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Defending Against Advanced Persistent Threats Using Game-Theory. by Stefan Rass, Sandra König, Stefan Schauer

“…Advanced persistent threats (APT) combine a variety of different attack forms ranging from social engineering to technical exploits. …”
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A Robust Method to Protect Text Classification Models against Adversarial Attacks by BALA MALLIKARJUNARAO GARLAPATI, Ajeet Kumar Singh, Srinivasa Rao Chalamala

“…The diversity and sparseness of adversarial perturbations of different attack methods challenge these approaches. This paper proposes an approach to correct adversarial samples for text classification tasks. …”
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Effective Proactive and Reactive Defense Strategies against Malicious Attacks in a Virtualized Honeynet by Frank Yeong-Sung Lin, Yu-Shun Wang, Ming-Yang Huang

“…In this paper, the attack-defense scenario is formulated as a mathematical model where the defender applies both proactive and reactive defense mechanisms against attackers with different attack strategies. In order to simulate real-world conditions, the attackers are assumed to have incomplete information and imperfect knowledge of the target network. …”
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Deep Learning Based DDoS Attack Detection by Xu Ziyi

“…The classification resulting from this model yielded high accuracy with robust results for different attack scenarios. Results reflect the potential superiority of the given model in detecting DDoS attacks. …”
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Simulated Adversarial Attacks on Traffic Sign Recognition of Autonomous Vehicles by Chu-Hsing Lin, Chao-Ting Yu, Yan-Ling Chen, Yo-Yu Lin, Hsin-Ta Chiao

“…In the Gaussian noise attack, Python 3.11.10 was used to add noise to the original image. Different attack methods interfered with the original machine learning model to a certain extent, hindering autonomous vehicles from recognizing traffic signs and detecting them accurately.…”
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Risk–Failure Interactive Propagation and Recovery of Sea–Rail Intermodal Transportation Network Considering Recovery Propagation by Qiuju Xiong, Bowei Xu, Junjun Li

“…The study quantifies the impact of the station on network resilience after different attack modes. In addition, the resilience metrics based on the station failure are established to accurately represent the resilience evolution of the network during propagation and recovery. …”
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Presentation Attack Detection using iris periocular visual spectrum images by Andrés Valenzuela, Juan E. Tapia, Violeta Chang, Christoph Busch

“…The analysis was carried out by evaluating the performance of five Convolutional Neural Networks (CNN) using both facial and periocular iris images for PAD with two different attack instruments. Additionally, we improved the CNN results by integrating the ArcFace loss function instead of the traditional categorical cross-entropy loss, highlighting that the ArcFace function enhances the performance of the models for both regions of interest, facial and iris periocular areas. …”
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RPKI Defense Capability Simulation Method Based on Container Virtualization by Bo Yu, Xingyuan Liu, Xiaofeng Wang

“…Finally, we propose a data collection and performance evaluation technique to evaluate BGP networks deploying RPKI under different attack scenarios and to explore the effectiveness of RPKI defense mechanisms at various deployment rates. …”
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