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Data Security Defense System based on Computer network Technology

Data Security Defense System based on Computer Network Techn...

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2023 International conference on Integrated Intelligence and Communication systems, ICiiCS 2023

作者： Yingli, Huangfu Qinghai Provincial Armed Police Corps Qinghai Xining China

ISBN: (纸本)9798350315455

With the rapid development of the internet, network security threats are also increasing, so establishing an effective data security defense system has become crucial. The system designed in this paper is based on Netfilter/Iptables technology, which is a powerful tool for packet filtering, forwarding and network address translation in Linux operating system. By using Netfilter/Iptables, the research can flexibly control and manage the data packets entering and leaving the network, so as to achieve the purpose of data security defense. Specifically, the system designed in this paper will make use of Netfilter/Iptables for the following aspects of data security defense: First, the system will set inbound and outbound filtering rules to prevent unauthorized access and insecure network connections. Second, the system will implement network address translation (NAT) functions to hide the real IP address of the internal network and provide an additional layer of protection. In addition, port forwarding rules will be set to ensure that only authenticated users can access specific network services. To enhance the security of the system, this paper will also introduce other data security technologies such as intrusion detection systems (IDS) and intrusion prevention systems (IPS). IDS will be responsible for monitoring network traffic and identifying potential intrusions, while IPS will proactively intercept and block malicious traffic based on IDS alerts. Finally, the study will evaluate the performance and effect of the designed system through experiments. Using Netfilter/Iptables framework, a data security defense system is designed and tested to ensure the security and stability of the *** attack scenarios are simulated and evaluated with appropriate performance indicators to verify the feasibility and effectiveness of the system. To sum up, the Netfilter/Iptables based data security defense system designed in this paper is expected to provide a powerful and

关键词： data security defense netfilter system design

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Time Synchronization in Communication networks: A Comparative Study of Quantum Technologies 25

Time Synchronization in Communication Networks: A Comparativ...

引用

IEEE Wireless Communications and networking conference (IEEE WCNC)

作者： Nande, Swaraj Shekhar Garbugli, Andrea Bassoli, Riccardo Fitzek, Frank H. P. Tech Univ Dresden Deutsch Telekom Chair Commun Networks Dresden Germany Ctr Tactile Internet Human In The Loop CeTI Cluster Excellence Dresden Germany Tech Univ Dresden Quantum Commun Networks QCNets Res Grp Dresden Germany Univ Bologna Bologna Italy

ISBN: (纸本)9798350303582;9798350303599

Time synchronization is crucial in the architecture of modern communication networks, supporting numerous high-stakes applications like financial transactions, autonomous vehicle control, and data center operations. While traditional time synchronization protocols, specifically the network Time Protocol (NTP) and Precision Time Protocol (PTP), are reliable for various applications, they fall short in scenarios requiring ultra-high precision and resilience. To address these limitations, this paper provides a comprehensive comparative analysis of two emerging quantum technologies, namely Time-Correlated Entangled Photons (TCEP) and Optical Lattice Clocks (OLC). Using Monte Carlo simulations, we examined the synchronization in terms of the accuracy of these technologies under various noise conditions, revealing that while TCEP works perfectly in low-noise environments, its efficacy diminishes significantly with increasing noise levels. On the contrary, OLCs demonstrate consistent performance across various noise levels, making them more versatile for diverse application scenarios. This study is foundational for integrating quantum technologies in time synchronization for communication networks and sheds light on their merits and challenges. Our findings open new avenues for research in scalability, environmental resilience, and the development of hybrid quantum-classical timekeeping systems. Integrating quantum-enhanced time synchronization into a communication network will be the key step for achieving full-fledged Quantum internet and quantum-enhanced communication networks.

关键词： Time Synchronization Entanglement Optical Lattice Clock Communication networks

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Introspection of 2D Object Detection using Processed Neural Activation Patterns in Automated Driving systems

Introspection of 2D Object Detection using Processed Neural ...

引用

IEEE/CVF International conference on Computer Vision (ICCV)

作者： Yatbaz, Hakan Yekta Dianati, Mehrdad Koufos, Konstantinos Woodman, Roger Univ Warwick WMG Warwick England Queens Univ Belfast Sch Elect Elect Engn & Comp Sci EEECS Belfast Antrim North Ireland

ISBN: (纸本)9798350307443

While deep neural network (DNN) models have become extremely popular for object detection in automated driving systems (ADS), the dynamic and varied nature of the road traffic environment can still lead to model failures. To address this issue, researchers have recently explored introspection mechanisms, a.k.a, self-assessment, for monitoring the quality of perception in ADS. Subsequently, depending on the situation, these mechanisms can either hand over control to the human driver in SAE Level 3, or initiate a minimum risk maneuver in SAE Level 4 ADS. State-of-the-art introspection mechanisms for ADS train a neural network to learn the relationship between the raw neural activation patterns of the underlying DNN-based perception function per frame and the calculated mean average precision. In this paper, we show that the use of raw activation patterns may contain misleading information for introspecting 2D object detection in ADS. To this end, we investigate how to optimally pre-process these patterns for improving the error detection performance. We evaluate the developed mechanism with and without pre-processing of the raw neural activation patterns and compare its performance with a state-of-the-art algorithm highlighting that for the Berkeley Deep Drive (BDD) dataset, pre-processing reduced the ratio of missed errors by 14% and improved the overall detection performance by 3%.

关键词： automated driving system introspection neural network object detection run time monitoring safety

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Smart Home Security Enhancements with Cisco Packet Tracer 1

Smart Home Security Enhancements with Cisco Packet Tracer

引用

1st IEEE International conference on Computing and Data Science, ICCDS 2024

作者： Nanthini, N. Lakshmi Priya, S. Jeslene Sugee, A.G. Sathyabama Institute of Science and Technology Department Of Computer Science and Engineering Chennai India

ISBN: (数字)9798350365337

ISBN: (纸本)9798350365337

Modern households are increasingly adopting smart home devices powered by the internet of Things (IoT). From smart thermostats and security systems to voice assistants, connected IoT devices enable seamless and responsive control through Wi-Fi, Bluetooth and other wireless technologies Whena home appliance a intelligent consumption is accelerating, driven by its undeniable benefits, the need for robust security solutions becomes paramount. This paper delves into the potential of EIGRP (Enhanced Interior Gateway Routing Protocol) as a powerful tool for securing smart homes. While challenges remain to ensure compatibility with all smart devices to improve network performance, EIGRP capabilities offer promising prospects for the coming years of smart home security If received greater adoption of this policy along with other security measures, can pave the way for more secure and connected smart home products to reap the full benefits, and find peace in your digital paradises. © 2024 IEEE.

关键词： internet of things

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Scalable Reinforcement Learning for Dynamic Overlay Selection in SD-WANs 22

Scalable Reinforcement Learning for Dynamic Overlay Selectio...

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22nd International-Federation-for-Information-Processing (IFIP) networking conference (IFIP networking)

作者： Botta, Alessio Canonico, Roberto Navarro, Annalisa Stanco, Giovanni Ventre, Giorgio Univ Napoli Federico II DIETI Dept Naples Italy

ISBN: (纸本)9783903176577

SD-WAN promises distributed enterprises to satisfy their dynamic communication requirements over the public internet with a substantial cost reduction and enhanced performance compared to dedicated lines. It builds interconnections between users or applications in remote sites by exploiting all available transport connections (e.g. internet, MPLS,...), but how to combine them to enhance communication performance is still an open challenge. Previous work investigated the use of Reinforcement Learning in the SD-WAN control logic to solve this problem, but they only considered simple scenarios consisting of two sites connected by two paths. In this paper we move a step forward and pose the question of whether such a promising approach can scale to WANs spanning multiple distributed sites connected through several paths. We first conduct an analytical study of the complexity of Reinforcement Learning that considers the increase of action and state spaces when the number of sites and paths grows. We then propose a solution based on Multi-Agent Reinforcement Learning (MARL) that helps reducing the overall complexity by leveraging an agent for each site. Finally, we show the effectiveness of our solution with real experiments in an emulated environment, showing that not only it is viable, but it also achieves a reduction in network policy violations, latency, and transit costs in a multi-site scenario.

关键词： SDN SD-WAN Traffic Engineering Reinforcement Learning Scalability

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Revolutionizing Indoor Air Quality: An Intelligent IoT Solution for Pollution Detection 5

Revolutionizing Indoor Air Quality: An Intelligent IoT Solut...

引用

5th International conference on High performance Big Data and Intelligent systems, HDIS 2023

作者： Hong, Weiqi Moussa, Karim H. School of Internet of Things Xi’an Jiaotong-liverpool University Suzhou China

ISBN: (纸本)9798350394160

Indoor air pollution is a persistent and significant issue with detrimental effects on human health, including respiratory problems, allergies, carcinogenic risks, and impacts on the nervous and cardiovascular systems. The presence of harmful gases resulting from human activities further exacerbates these health concerns, leading to reduced productivity, increased morbidity, and economic losses. This paper aims to address the current challenges of indoor air pollution by proposing a practical internet of Things (IoT)-based online monitoring system. The system comprises three key components: (1) the design and implementation of sensor-based data collection for indoor air quality using Raspberry Pi, (2) the development of network protocols and data storage utilizing the Ali cloud platform, and (3) the creation of user-friendly web visualization and UI design. By integrating IoT technology, the poposed air quality control system can achieve enhanced intelligence and performance, making it a valuable tool for improving indoor air quality. ©2023 IEEE.

关键词： Digital storage

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Efficient IoT Intrusion Detection: Integrating Random Forest Feature Selection with MLP Model Pruning 1st

Efficient IoT Intrusion Detection: Integrating Random Forest...

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1st International conference on Electrical systems and Smart Technologies, ICESST 2024

作者： Bella, Kamal Mohy-Eddine, Mouaad Guezzaz, Azidine Benkirane, Said Azrour, Mourade Technology Higher School Essaouira Cadi Ayyad University Marrakesh Morocco ENSAM Hassan II University Casablanca Morocco IDMS Team Faculty of Sciences and Technics Moulay Ismail University of Meknès Mekens Morocco

ISBN: (纸本)9783031867040

The proliferation of the internet of Things (IoT) has revolutionized various industries, offering enhanced connectivity and automation. However, this rapid expansion has also introduced significant security vulnerabilities, making IoT networks prime targets for cyber-attacks. Intrusion Detection systems (IDS) are crucial for safeguarding these networks, providing real-time detection and response to potential threats. Machine learning-based IDS have emerged as effective solutions, offering the ability to analyze large volumes of network data and identify malicious activities with high accuracy. In this paper, we present a novel IDS model utilizing a Multi-Layer Perceptron (MLP), combined with Random Forest-based feature selection, to optimize detection performance while reducing model complexity. We evaluated the MLP model using four distinct feature sets (10, 20, 30, and 40 features) derived from the Ton-IoT dataset to assess the impact of feature selection on accuracy and efficiency. Subsequently, model pruning was applied to reduce the model size, ensuring its suitability for deployment in resource-constrained IoT environments. Our results demonstrate that the proposed approach effectively balances detection performance with resource efficiency, making it a robust solution for securing IoT networks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： network intrusion

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Design and Deployment of Resilient control Execution Patterns: A Prediction, Mitigation Approach 23

Design and Deployment of Resilient Control Execution Pattern...

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14th ACM/IEEE International conference on Cyber-Physical systems (ICCPS) part of CPS-IoT Week

作者： Koley, Ipsita Adhikary, Sunandan Sain, Arkaprava Dey, Soumyajit Indian Inst Technol Kharagpur Dept CSE Kharagpur W Bengal India

ISBN: (纸本)9798400700361

Modern Cyber-Physical systems (CPSs) are often designed as networked, software-based controller implementations which have been found to be vulnerable to network-level and physical-level attacks. A number of research works have proposed CPS-specific attack detection schemes as well as techniques for attack-resilient controller design. However, such schemes also incur platform-level overheads. In this regard, some recent works have leveraged the use of skips in control execution to enhance the resilience of a CPS against false data injection (FDI) attacks. However, skipping the control executions may degrade the performance of the controller. In this paper, we provide an analytical discussion on when and how skipping a control execution can improve the system's resilience against FDI attacks while maintaining the control performance requirement. Our proposed method i) synthesizes a library of such optimal control execution patterns offline, and ii) executes one of them in run-time judging the intent of the attacker. To the best of our knowledge, no previous work has provided any quantitative analysis about the trade-off between attack resilience and control performance for such aperiodic control execution. Finally, we evaluate the proposed method on several safety-critical CPS benchmarks.

关键词： CPS control execution skips security attack resilient system control performance

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Smart and Adaptive Routing Architecture: An internet-of-Things Traffic Manager Based on Artificial Neural networks

Smart and Adaptive Routing Architecture: An Internet-of-Thin...

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1st IEEE International conference on Software Services Engineering (IEEE SSE)

作者： Amiri, Amirali Zdun, Uwe Univ Vienna Software Architecture Grp Doctoral Sch Comp Sci Vienna Austria Univ Vienna Software Architecture Grp Vienna Austria

ISBN: (纸本)9798350340754

Many studies have been performed on integrating the internet of Things (IoT) with cloud services. As these systems become widely used, quality metrics are of concern. For example, users might specify access control to restrict their sensitive data being processed in the cloud. Routers, e.g., API gateways, message brokers, or sidecars, can provide this access control by blocking or routing device data to a specific cloud service. However, a static routing application might not suit the dynamic behavior of IoT applications well. For example, in a centralized schema, where all device data is routed to a component for control checking, performance can be an issue. On the other hand, distributed routing can harm the reliability of a system, as device data might be lost due to an unresponsive service. We present the Smart and Adaptive Routing (SAR) architecture that creates an optimal reconfiguration solution using a deep neural network based on the quality metrics of an IoT application. To design our architecture, we give a background of the published studies and a review of the gray literature, e.g., practitioner blogs, to categorize the knowledge in the domain of IoT-cloud traffic management. We systematically evaluate our approach in an extensive evaluation of 4500 cases and compare SAR with an empirical data set of 1200 hours. The results show that our approach significantly improves quality-of-service measures by adapting the IoT-cloud system at runtime.

关键词： Self-Adaptive systems Dynamic Routing Architectures internet of Things Reliability and performance Trade-Offs IoT-Cloud Traffic Management Artificial Neural networks

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Research on Fault Diagnosis of control System Based on Multi-sensor Data Fusion Algorithm 13th

Research on Fault Diagnosis of Control System Based on Multi...

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13th International conference on Computer Engineering and networks (CENet)

作者： Li, Ziyi Zhai, Xuhua Ma, Liyao Army Acad Armored Forces Changchun Sergeant Sch Changchun Peoples R China Univ Jinan Sch Elect Engn Jinan Peoples R China

ISBN: (纸本)9789819992454;9789819992430;9789819992423

With the progress of science and technology nowadays and the enhancements in control system optimization field, system fault diagnosis has become a hot topic in the industry, and many models of fault diagnosis using various artificial intelligence algorithms have emerged. However, with the increasing complexity of fault, the accuracy of fault diagnosis from a single data source gradually declines. Based on this, this paper proposal an intelligent diagnosis model innovationally basing on multi-sensor intelligent fusion algorithm, which uses BP neural network, a typical artificial intelligence algorithm, to generate evidence from multi-sensor data, on this basis, D-S evidence theory is used for data fusion to improve the accuracy of fault diagnosis and the performance of fault diagnosis algorithm in multi-type control systems.

关键词： Pattern recognition Fault diagnosis Information fusion Artificial intelligence D-S evidence theory

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