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IEEE Conference on Global Communications (GLOBECOM)

作者： Ítalo B. Brasileiro Iulisloi Zacarias André C. Drummond Antonio Napoli Admela Jukan Institute of Computer and Network Engineering Technische Universität Braunschweig Germany Department of Computer Science University of Brasília Brazil Infinera Munich Germany

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The next-generation mobile networks follow the 3GPP disaggregated Radio Access network (RAN) model, composed of three separate functional units: Centralized Unit (CU), Distributed Unit (DU), and Radio Unit (RU), and its interconnection network infrastructures, front-haul, between RU and DU and mid-haul, between DU and CU. The current focus has been extensively on the front-haul, proposing a myriad of networking technologies and resource allocation solutions. Mid-haul transport infrastructure has received comparably less attention. This paper explores the implementation and performance of optical multi-flow transponders in mobile mid-haul networks. It evaluates the performance of mid-haul mesh topologies with different DU placement methods. Numerical results show the achievable throughput and blocking performance. We also derive the number of Multi-flow optical transponders (MOTP) units deployed, as well as the related trade-offs.

关键词： Optical interconnections network topology Multiprocessor interconnection Throughput Optical network units Topology Transponders Resource management Next generation networking Radio access networks

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Research and Innovation in Next Generation Security and Privacy in Industry 5.0 Iot 6

Research and Innovation in Next Generation Security and Priv...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Navale, Geeta S. Madala, Ravikiran Managuli, Manjunath Jayalakshmi, N. Kadiravan, G. Rawat, Ruchira Sinhgad Institute of Technology and Science Department of Computer Engineering Maharashtra Pune India Ph.D Information Technology Network and Data Center Engineer University of Cumberlands DurhamNC United States KLS Gogte Institute of Technology Department of Electronics and Communication Engineering Karnataka Belagavi India PSNA College of Engineering and Technology Master of Computer Applications Tamilnadu Dindigul India KL Deemed to Be University Department of Computer Science and Information Technology Andhra Pradsh India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttrakhand Dehradun India

ISBN: (纸本)9798350304480

The objective of the newest manufacturing paradigm, known as 'Industry 5.0,'is to combine human intelligence with cutting-edge technology like the Internet of Things (IoT), artificial intelligence (AI), and robots to develop production systems that are incredibly effective and adaptable. But as we rely more on these technologies, we face additional privacy and security issues that might affect how dependable and trustworthy these systems are. In this report, we examine the most recent advancements in security and privacy for Industry 5.0 IoT and pinpoint the newest trends, obstacles, and possibilities. We also cover how these changes may affect manufacturing in the future and provide advice to scholars, practitioners, and policymakers. © 2023 IEEE.

关键词： artificial intelligence cyber-physical systems human-machine collaboration Industry 5.0 Internet of Things IoT manufacturing privacy robotics security

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Research on offset compensation of OFDM system based on Synchronization Algorithm 2

Research on offset compensation of OFDM system based on Sync...

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2022 2nd International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2022

作者： Guo, Haibo Zeng, Wei Yu, Zhen Fan, Tianfeng Mechanical and Electrical Engineering Chengdu University of Technology Sichuan Chengdu China Computer and Network Security Institute Chengdu University of Technology Sichuan Chengdu China

ISBN: (纸本)9783800760268

OFDM technology mainly relies on the orthogonality of sub-carriers to achieve stable and efficient data transmission. Once the orthogonality of sub-carriers is affected, it will directly affect the communication effect of the entire system. In order to solve the above problems, this paper uses improved timing synchronization algorithm, carrier frequency synchronization algorithm and sampling frequency synchronization algorithm to compensate three kinds of deviations in OFDM system: timing deviation, carrier frequency deviation, and sampling frequency deviation. Finally, the simulation results show that after all synchronization is completed, when the signal-to-noise ratio is 14dB, the bit error rate reaches 0.18;when Eb/N0 = 12dB, the demodulation error is 0 and the bit error rate is 0, which greatly reduces the OFDM system. The impact of the medium deviation problem. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Bit error rate

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Application of Image Similarity Detection based on Typical ITAI Servers 2022

Application of Image Similarity Detection based on Typical I...

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5th International Conference on Image and Graphics Processing, ICIGP 2022

作者： Chen, Su Wu, Zhimin Guo, Menghan Wang, Zhenyu National Computer Network Emergency Response Technical Team Coordination Center of China Beijing China Institute of Information Engineering Chinese Academy of Sciences China

ISBN: (纸本)9781450395465

In this paper, image detection algorithms based on traditional methods and deep-learning method are migrated from Intel X86 architecture ecosystem to X86 and ARM architectures on the typical localized servers and softwares in Information Technology Application Innovation (ITAI) catalog. By solving the adaptation problems as well as considering the different processor architectures of the localized server, targeted performance optimization methods are proposed, and large-scale performance testing on massive images have been experimented on physical machines, verifying the production capacity of current ITAI servers in image detection scenario. © 2022 ACM.

关键词： Deep learning

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Automated Security Response through Online Learning with Adaptive Conjectures

arXiv

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arXiv 2024年

作者： Hammar, Kim Li, Tao Stadler, Rolf Zhu, Quanyan Division of Network and Systems Engineering KTH Royal Institute of Technology Sweden Department of Electrical and Computer Engineering New York University United States

We study automated security response for an IT infrastructure and formulate the interaction between an attacker and a defender as a partially observed, non-stationary game. We relax the standard assumption that the game model is correctly specified and consider that each player has a probabilistic conjecture about the model, which may be misspecified in the sense that the true model has probability 0. This formulation allows us to capture uncertainty and misconception about the infrastructure and the intents of the players. To learn effective game strategies online, we design Conjectural Online Learning (COL), a novel method where a player iteratively adapts its conjecture using Bayesian learning and updates its strategy through rollout. We prove that the conjectures converge to best fits, and we provide a bound on the performance improvement that rollout enables with a conjectured model. To characterize the steady state of the game, we propose a variant of the Berk-Nash equilibrium. We present COL through an advanced persistent threat use case. Testbed evaluations show that COL produces effective security strategies that adapt to a changing environment. We also find that COL enables faster convergence than current reinforcement learning techniques. © 2024, CC BY-SA.

关键词： Nash equilibrium

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Research on air interface interference recognition in mobile communication networks based on LSTM autoencoder 5

Research on air interface interference recognition in mobile...

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5th International Conference on Signal Processing and computer Science, SPCS 2024

作者： Sun, Hongwei Hu, Mingwei Wang, Baoji Chen, Yue Fu, Jingwen Huang, Jia Jiangsu Automation Research Institute Lianyungang222006 China National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100094 China Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Beijing Sankuai Online Technology Co. Ltd. Beijing100102 China

ISBN: (数字)9781510686731

ISBN: (纸本)9781510686724

Due to the diverse nature of interference signals in mobile communication frequency bands, feature extraction is challenging, and the rapid and automated identification of behaviors such as illegal frequency usage and malicious interference are difficult. Moreover, evaluating the precise impact of interference signals on communication networks is challenging. In response to this problem, this paper proposes an air interface interference recognition technology for communication links based on base station measurement reporting data. It constructs an interference recognition model to achieve automatic interference identification and evaluates the accuracy of interference recognition. On the base station side, this paper utilizes channel measurement data such as signal strength, signal quality, and signal-to-noise ratio exported by the base station. It uses a Long Short-Term Memory (LSTM) autoencoder model to learn normal signal patterns for interference discrimination and evaluates the impact of interference on communication networks. This method achieves precise identification of fixed-frequency interference on the base station side and evaluates the impact of interference on communication networks. Experimental results show that the base station-side approach achieves an F1 score of 0.99 in identifying fixed-frequency interference, outperforming One-Class Support Vector Machine (OCSVM), Principal Component Analysis (PCA), and Isolation Forest (IForest) methods under similar conditions. © 2025 SPIE.

关键词： Base stations

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AHIP: An Adaptive IP Hopping Method for Moving Target Defense to Thwart network Attacks 26

AHIP: An Adaptive IP Hopping Method for Moving Target Defens...

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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Shi, Fengyuan Zhou, Zhou Yang, Wei Li, Shu Liu, Qingyun Bao, Xiuguo Institute of Information Engineering Chinese Academy of Sciences China National Engineering Research Center of Information Security School of Cyber Security University of Chinese Academy of Sciences China National Computer Network Emergency Response Technical Team Coordination Center of China China

ISBN: (纸本)9798350331684

In a static network, attackers can easily launch network attacks on target hosts which have long-term constant IP addresses. In order to defend against attackers effectively, many defense approaches use IP hopping to dynamically transform IP configuration. However, these approaches usually focus on one type of network attacks, scanning attacks or Denial of Service (DoS) attacks, and cannot sense network situations. This paper proposes AHIP, an adaptive IP hopping method for moving target defense (MTD) to defend against different network attacks. We use a trained lightweight one-dimensional convolutional neural network (1D-CNN) detector to judge whether there are no attacks, scanning attacks or DoS attacks in the network, which can adaptively trigger corresponding IP hopping strategy. We use specific hardware and software to create the software defined network (SDN) environment for experiments. The experiments prove that AHIP performs better to thwart network attacks and has lower system overhead. © 2023 IEEE.

关键词： Denial-of-service attack

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Cyber-Physical Systems Design in An Uncertain Environment with Time Uncertainty Concern 29

Cyber-Physical Systems Design in An Uncertain Environment wi...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Chen, Si Huang, Lida Xiao, Xiongren Liu, Yan Xie, Guoqi Li, Renfa Hunan University Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Changsha China Research Institute of Hunan University in Chongqing Center for Convergence of Automobile and Cyberspace Chongqing China

ISBN: (纸本)9798350330717

Multiple processors system on chip (MPSoC) has been the trend in cyber-physical systems (CPSs), and reasonable partitioning for MPSoC resources is a critical step in CPSs design. The uncertainties of environment and time are both important factors that need to be considered in the design, but none of the previous work pays attention to two uncertainties at the same time. The state-of-the-art work presented a detailed process of applying uncertain programming to solve the partitioning problem, which provides a solution for designing in an uncertain environment. However, this work only considers the bipartition scenario which cannot be directly applied to MPSoC, and it does not focus specifically on time uncertainty. In this paper, we propose a method for modeling the MPSoC partitioning problem in an uncertain environment, with the time uncertainty concern. We present the uncertain model that can be applied to the multiple optional resources scenario. We build the optimization model with the objective of minimizing time, analyze two different cases of minimizing the uncertain time, and finally prove a unified deterministic model to solve. We come up with three algorithms, including the heuristic algorithm, the genetic algorithm, and the exact algorithm, and experiments show that the heuristic algorithm and the genetic algorithm can obtain good approximate solutions compared with the exact algorithm. © 2023 IEEE.

关键词： Cyber-physical systems (CPSs) design multiple processors system on chip (MPSoC) partitioning time uncertainty uncertain environment

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Knowledge Graph Augmented network Towards Multiview Representation Learning for Aspect-Based Sentiment Analysis

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IEEE Transactions on Knowledge and Data engineering 2023年第10期35卷 10098-10111页

作者： Zhong, Qihuang Ding, Liang Liu, Juhua Du, Bo Jin, Hua Tao, Dacheng Wuhan University National Engineering Research Center for Multimedia Software Institute of Artificial Intelligence School of Computer Science Hubei Key Laboratory of Multimedia and Network Communication Engineering Hubei Wuhan430072 China Jd Explore Academy at *** Beijing100101 China Wuhan University Research Center for Graphic Communication Printing and Packaging Institute of Artificial Intelligence Hubei Wuhan430072 China Hospital of Kunming University of Science and Technology Kunming650032 China

Aspect-based sentiment analysis (ABSA) is a fine-grained task of sentiment analysis. To better comprehend long complicated sentences and obtain accurate aspect-specific information, linguistic and commonsense knowledge are generally required in this task. However, most current methods employ complicated and inefficient approaches to incorporate external knowledge, e.g., directly searching the graph nodes. Additionally, the complementarity between external knowledge and linguistic information has not been thoroughly studied. To this end, we propose a knowledge graph augmented network (KGAN), which aims to effectively incorporate external knowledge with explicitly syntactic and contextual information. In particular, KGAN captures the sentiment feature representations from multiple different perspectives, i.e., context-, syntax- and knowledge-based. First, KGAN learns the contextual and syntactic representations in parallel to fully extract the semantic features. Then, KGAN integrates the knowledge graphs into the embedding space, based on which the aspect-specific knowledge representations are further obtained via an attention mechanism. Last, we propose a hierarchical fusion module to complement these multi-view representations in a local-to-global manner. Extensive experiments on five popular ABSA benchmarks demonstrate the effectiveness and robustness of our KGAN. Notably, with the help of the pretrained model of RoBERTa, KGAN achieves a new record of state-of-the-art performance among all datasets. © 1989-2012 IEEE.

关键词： Semantics

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Resilient Routing Table Computation Based on Connectivity Preserving Graph Sequences 42

Resilient Routing Table Computation Based on Connectivity Pr...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Tapolcai, Janos Babarczi, Peter Ho, Pin-Han Ronyai, Lajos Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Telecommunications and Media Informatics BudapestH-1111 Hungary University of Waterloo Deptartment of Electrical and Computer Engineering Canada Institute for Computer Science and Control Eötvös Loránd Research Networkand Department of Algebra Hungary Institute of Mathematics Budapest University of Technology and Economics BudapestH-1111 Hungary

ISBN: (纸本)9798350334142

Fast reroute (FRR) mechanisms that can instantly handle network failures in the data plane are gaining attention in packet-switched networks. In FRR no notification messages are required as the nodes adjacent to the failure are prepared with a routing table such that the packets are re-routed only based on local information. However, designing the routing algorithm for FRR is challenging because the number of possible sets of failed network links and nodes can be extremely high, while the algorithm should keep track of which nodes are aware of the failure. In this paper, we propose a generic algorithmic framework that combines the benefits of Integer Linear Programming (ILP) and an effective approach from graph theory related to constructive graph characterization of k-connected graphs, i.e., edge splitting-off. We illustrate these benefits through arborescence design for FRR and show that (i) due to the ILP we have great flexibility in defining the routing problem, while (ii) the problem can still be solved very fast. We demonstrate through simulations that our framework outperforms state-of-the-art FRR mechanisms and provides better resilience with shorter paths in the arborescences. © 2023 IEEE.

关键词： Graph theory

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