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检索条件"任意字段=2nd International Conference on Security in Computer Networks and Distributed Systems, SNDS 2014"

共 309 条记录，以下是51-60 订阅

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Internet of Things-Based Middleware Against Cyber-Attacks on Smart Homes using Software-Defined Networking and Deep Learning 2

Internet of Things-Based Middleware Against Cyber-Attacks on...

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2nd international conference on Computational Methods in Science and Technology, ICCMST 2021

作者： Tawfik, Mohammed Al-Zidi, Nasser M. Alsellami, Belal Al-Hejri, Aymen M. Nimbhore, Sunil Dr. Babasaheb Ambedkar Marathwada University Department of Computer Science & It Aurangabad India Albaydha University Faculty of Administrative and Computer Sciences Albaydha Yemen

ISBN: (纸本)9781665458665

Internet of Things (IoT) devices are expected to number about 3.5 billion by 2023.;a tremendous amount of Internet of Things (IoT) data that is generating (IoT) devices is estimated to exceed 79.4 zettabytes by 2025. security challenges will become an increasingly significant issue, especially in smart homes that depend entirely on IoT devices. Due to the weak infrastructure of the IoT, it is vulnerable to various types of cyber-attacks. The most common IoT attacks are distributed denial of service (DDoS). Most traditional security solutions, like intrusion detection systems (IDS), cannot detect most attacks. Complexity is being hidden by a new paradigm that recently arose, called the software-defined system that is brings a significant change to the networking industry, a great solution for mitigation of attacks that can adopt deep learning technique to encounter cyber-attacks based on the attack behavior and by filtering normal and attack traffic by using well-defined rules. This paper proposed a system by suggesting middleware that can help mitigate or prevent various attacks on IoT on smart home environment. Machine learning has included in the middleware to provide automatic protection against cyber-attacks on IoT networks. A promising approach to protecting real-time, highly accurate attacks on SDN-managed IoT networks has been proposed. This middleware allows IoT devices to efficiently handle evolving security threats dynamically and adaptively without impacting the IoT devices. © 2021 IEEE.

关键词： Internet of things

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A review of cyber securities in smart grid technology 2

A review of cyber securities in smart grid technology

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2nd international conference on Computation, Automation and Knowledge Management, ICCAKM 2021

作者： Kawoosa, Asif Iqbal Prashar, Deepak Lovely Professional University Department of Computer Applications Punjab India

ISBN: (纸本)9781728194912

A Smart Grid (SG) is an electrical infrastructure much like legacy power grid with scalable and pervasive two-way communications, timely control capabilities, large scale integration of distributed resources and efficient use of resources. The SG provides the features of pervasive smart monitoring technologies, automatic equipment fault sensing and self-healing. The features like 'Wireless Automatic Meter Reading' (WAMR), monitoring of power system stability, distributed energy resources optimization and applications of Demand Response system makes it intelligent infrastructure. Given some of these salient features, SGs without any doubt are the future power infrastructure of energy world. A smart grid has ability to connect millions of consumers and devices in a network which demand it to be highly robust, reliable and secure. security is considered as one of the major challenges in the present-day smart grid systems because of its long-range communication on open networks. Cybercriminals, hackers, terrorists are trying to attack this national infrastructure due to their malicious intensions or to get control on the automated energy monitoring and remote controlling for personal gains. This review paper offers a comprehensive survey of understanding of Smart Grids, architecture of SGs, methodologies used, the communication protocols but the focus is mainly on the cyber-attacks carried out and solutions recommended on the smart grids. We finally discuss the various challenges in cyber security, the issues that still exist in the literature and current solution space with future research gap. © 2021 IEEE.

关键词： Network security

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Classification of Internet of Things Cybersecurity Attacks Using a Hybrid Deep Learning Approach 2nd

Classification of Internet of Things Cybersecurity Attacks U...

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2nd international conference on Innovations of Intelligent Informatics, Networking and Cybersecurity, 3INC 2024

作者： Kareem, Eman Karkawi Manaa, Mehdi Ebady Department of Information Networks College of IT University of Babylon Babylon Iraq Intelligent Medical Systems Department College of Sciences Al-Mustaqbal University Babylon51001 Iraq College of Information Technology University of Babylon Babylon Iraq

ISBN: (纸本)9783031810640

IoT devices play an integral part of our digital life today, yet pose significant security risks. These risks allow attackers to carry out various cyberattacks, mainly distributed denial of service (DDoS) attacks. To address these challenges, this paper proposes a hybrid deep learning approach that uses deep neural networks (DNNs) and long short-term memory (LSTM) networks to classify IoT cybersecurity attacks. The binary classification technique of LSTM is applied, whereby the models indicated sufficient results in terms of accuracy and performance, with the LSTM model showing an accuracy of 0.999 and the DNN model showing an accuracy of 0.999. To enhance detection capabilities, we used a comprehensive approach that includes 15 different attack categories. Although the DNN model equals the LSTM model with an accuracy of 0.95 in some scenarios, the hybrid model, which integrates the DNN feature outputs and the LSTM-derived features, showed an overall accuracy of 95.36. We further conducted extensive tests on the Edge-IIoT dataset to validate the effectiveness of our hybrid model. The proposed solution effectively exploits the strengths of the DNN and LSTM architectures, providing a robust framework for detecting and classifying DDoS attacks within IoT networks. These results contribute to a promising approach to mitigate the risks associated with IoT vulnerabilities. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cyber attacks

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Comparative Analysis of Communication Protocols in Blockchain-IoT systems for Optimizing IoT Data Flow Efficiency

Comparative Analysis of Communication Protocols in Blockchai...

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Advanced Innovations in Smart Cities (ICAISC), international conference on

作者： Mnar Alnaghes Hong Shen School of Computer Science University of Adelaide Adelaide Australia

ISBN: (数字)9798331506995

ISBN: (纸本)9798331507008

The Internet of Things (IoT) is considered an evolving technology, consisting of different types of connected devices that have sensors, specialized hardware, and software. However, considerable challenges related to user data privacy, security, and device integrity are presented by this swift expansion, with digital identity being identified as a significant concern in the online landscape. Established by the World Wide Web Consortium (W3C) [2], Decentralized Identifiers (DIDs) represent a standardized format for defining identity. A peer-to-peer model for managing identity and credentials through self-sovereign identity is facilitated by DIDs, in conjunction with blockchain technology and public-key cryptography. The development of verifiable credentials is enabled by the combination of DIDs and blockchain technology, allowing for the verification of the identities of transacting parties through distributed identity registration and the identification of cryptographic keys necessary for validating electronic authentication during transactions. This integrated framework is regarded as both reliable and trusted. Device registration, verification, and credential revocation are enabled by it. In addition, security is ensured, the privacy of participating nodes is respected, and data integrity is upheld to address several existing challenges, such as data scalability and confidentiality. Trusted management and transaction of IoT data are ensured by the presented IoT data platform. Blockchain, decentralized identifiers, and public key cryptography are integrated by the authors to develop this platform. Self-sovereign identity is granted to each participating device, and dynamic changes in components like consensus algorithms and databases are supported by key features. Different IoT communication protocols are evaluated within a decentralized blockchain infrastructure for identity verification by the authors, focusing on interactions between IoT devices and networked se

关键词： Wireless communication Data privacy Wireless sensor networks Protocols W3C Public key cryptography Blockchains Peer-to-peer computing Internet of Things Optimization

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IA&AI: Interference Analysis in Multi-core Embedded AI systems 2nd

IA&AI: Interference Analysis in Multi-core Embedded AI Syst...

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2nd international conference on Data Science and Artificial Intelligence, DSAI 2024

作者： Oliveira, Afonso Moreira, Gonçalo Costa, Diogo Pinto, Sandro Gomes, Tiago Centro ALGORITMI/LASI Universidade do Minho Braga Portugal

ISBN: (纸本)9789819797929

Significant advances in Artificial Intelligence (AI) over the past decade have opened new aisles of exploration for industries such as automotive and industrial robotics, leading to the widespread adoption of AI. To meet the demands of modern applications, embedded platforms have evolved into highly heterogeneous designs, transitioning from simple microcontroller-based systems to intricate platforms with multiple processor units and hardware accelerators. Driven by Size, Weight, Power, and Cost (SWAP-C) constraints, both industry and academia have focused on consolidating systems with different criticality levels, referred to as mixed-criticality systems (MCS), onto a single hardware platform. However, the co-existence of heterogeneous designs can still raise several safety and security issues, which can be addressed through secure computer architectures and hypervisor technologies that provide spatial and temporal isolation features. This paper discusses the impact of MCS consolidation on AI-based applications. The setup uses the Bao hypervisor to deploy two virtual machines (VMs): one VM hosting TensorFlow Lite to run AI workloads on a Linux system, and the other supporting a bare-metal memory-intensive application. The study involves running Convolutional Neural networks (CNNs) and Deep Neural networks (DNNs) machine learning models (ML), based on two widely used classification datasets: MNIST and CIFAR-10, while assessing the impact of sharing platform resources with a memory-intensive application. Empirical results show that contention on last-level cache and system bus can significantly impact the inference process of an ML model up to 6.39x. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep neural networks

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security for Wireless Sensor networks : Bibliometric Analysis

Security for Wireless Sensor Networks : Bibliometric Analysi...

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Computing, Analytics and networks (Indo-Taiwan ICAN), Indo – Taiwan 2nd international conference on

作者： Durga Shankar Baggam Shalli Rani Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Science & Engineering Gandhi Engineering College(GECBhubaneswar) Odisha India

ISBN: (纸本)9781665499453

Wireless sensor networks are mostly popular in a wide variety of applications and is used without any restrictions, that leads to serious security implications. Major concerns are localization, security, data aggregation, data integration, data calibration, fault tolerance and distributed denial of service attacks. It is important to explore the articles that are published by researchers about their concerns and the adopted methods used to solve the problem space. This paper includes a comprehensive bibliometric analysis to explore any uncovered areas. In recent days’ bibliometric analysis using R based bibliometric package is the most popular approach used in this research study. This research presents a) Annual Scientific Production, b) Annual Citations per Year c) Three-Fields Plot d) Most Relevant Sources e) Source H-Index f) Most Relevant Authors and their production over time g) Co-occurrence Network from trendy topic frequency h) Thematic Map. It is a quantitative research conducted on security for wireless sensor networks using dataset retrieved from Scopus database, it is all about the articles published during the period: 2002 and up-to the first quarter of 2022. A collection of 1654 articles are filtered using Search protocol and the same is based on PRISMA approach. After bibliometric analysis authors observations are that during the last two decades this being an interesting topic, there is a contributed growth of around 27.69% articles represents the demand. This survey paper provides a research roadmap for intended researchers.

关键词： Location awareness Wireless sensor networks Fault tolerance Protocols Bibliometrics Fault tolerant systems Data integration

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Wireless network security technology and application in colleges and universities

Wireless network security technology and application in coll...

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The 2nd international conference on distributed Sensing and Intelligent systems (ICDSIS 2021)

作者： W. Wang G. Wang X. He Z. Guo Z. Lin Z. Wang Airport Management College Guangzhou Civil Aviation College Guangzhou 510403 Guangdong China

The rapid development of computer technology has penetrated into all areas of people's work and life. At the same time, with the rapid development of wireless network technology, colleges and universities have become the biggest beneficiaries of the later development of wireless network technology. At the same time, the problem of wireless network security technology and application in colleges and universities is an unavoidable problem in the current Internet era, and the development of network security technology is also changing with each passing day. The purpose of this article is to study wireless network security technology and applications in colleges and universities. This research summarizes and analyzes the current status of wireless network security and the development trends and key technologies in this field. Through case investigation and case analysis, the current wireless network security characteristics and network security technology applications in universities are investigated and analyzed, and the university is summarized Wireless network security features and applications. Combining the current mainstream wireless network security protection technology and security protection strategy, research and design a multi-level, multi-measure university wireless network security protection program to ensure the network security of colleges and universities. Taking a university as an example, the research and application of the wireless network security event detection method and application scheme using data fusion technology designed and proposed in this study for the wireless network security technology of universities and colleges have been verified through actual security technology application and effect testing the effectiveness and applicability of the proposed algorithm and scheme. The survey results show that for a sensor network with 1250 nodes, the efficiency of the algorithm proposed in this study is 2.1%, while the efficiency of this protoc

关键词： computer network security data fusion educational institutions Internet radio networks

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DDoS Attack Detection in IoT networks Using Deep Learning Models Combined with Random Forest as Feature Selector 2nd

DDoS Attack Detection in IoT Networks Using Deep Learning Mo...

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2nd international conference on Advances in Cyber security, ACeS 2020

作者： Farukee, Minhaz Bin Shabit, M. S. Zaman Haque, Md. Rakibul Sattar, A. H. M. Sarowar Department of Computer Science and Engineering Rajshahi University of Engineering and Technology Rajshahi Bangladesh

ISBN: (纸本)9789813368347

Due to the major advancements and finesse earned in technology, the internet and communication fields have seen a ground-breaking breakthrough by incorporating themselves with "things" which as a result have created connected systems and have given multiple utilities to a single device. But due to the digitization of technologies and always online and connected features, they are becoming more prone to cyberattacks, mostly due to the widespread distributed Denial of Services (DDoS) attacks. Since DDoS attacks create multiple agents to attack a victim network, the always-connected Internet of Things (IoT) devices that communicate over various communication protocols gives the perfect platform for such attacks and these sort of the attacks are on the rise day by day. So, the advent of an efficient and highly precise DDoS attack detection model needs to be addressed. Being motivated by the increasing amount of DDoS attacks, the vulnerability of IoT devices to such attacks, and to tackle this situation, two deep learning-based models have been proposed. The models are based on the combination of Random Forest as a feature selector and 1D Convolutional Neural Network and Multilayer Perceptron methods for DDoS attack detection. The main objective behind the proposed models is to detect DDoS attacks accurately and as early as possible. The models have been evaluated using the CICIDS2017 dataset which resulted in high accuracy of 99.63% in the case of RF-1DCNN and 99.58% in the RF-MLP model. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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6g access network for intelligent internet of healthcare things: Opportunity, challenges, and research directions 2nd

6g access network for intelligent internet of healthcare thi...

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2nd international conference on Trends in Computational and Cognitive Engineering, TCCE 2020

作者： Kaiser, M. Shamim Zenia, Nusrat Tabassum, Fariha Mamun, Shamim Al Rahman, M. Arifur Islam, Md. Shahidul Mahmud, Mufti Institute of Information Technology Jahangirngar University Savar Dhaka1342 Bangladesh Department of EECE Military Institute of Science and Technology Dhaka Bangladesh Department of Physics Jahangirngar University Savar Dhaka1342 Bangladesh Department of Computer Science Nottingham Trent University NottinghamNG11 8NS United Kingdom

ISBN: (纸本)9789813346727

The Internet of Healthcare Things (IoHT) demands massive and smart connectivity, huge bandwidth, lower latency with ultra-high data rate and better quality of healthcare experience. Unlike the 5G wireless network, the upcoming 6G communication system is expected to provide Intelligent IoHT (IIoHT) services everywhere at any time to improve the quality of life of the human being. In this paper, we present the framework of 6G cellular networks, its aggregation with multidimensional communication techniques such as optical wireless communication network, cell-free communication system, backhaul network, and quantum communication, as well as distributed security paradigm in the context of IIoHT. Such low latency and ultra-high-speed communication network will provide a new paradigm for connecting homes to hospitals, healthcare people, medical devices, hospital infrastructure, etc. Also, the requirements of 6G wireless networking, other key techniques, challenges and research direction of deploying IIoHT are outlined in the article. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Machine learning

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distributed Trust-Based Monitoring Approach for Fog/Cloud networks 1

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2nd international conference on Computing, Communications and Data Engineering (CCODE)

作者： Ben Daoud, Wided Meddeb-Makhlouf, Amel Zarai, Faouzi Obaidat, Mohammad S. Univ Sfax NTSCom Res Unit ENETCOM Sfax Tunisia Nazarbayev Univ Dept ECE Astana Kazakhstan Univ Jordan Amman Jordan

ISBN: (数字)9789811501357

ISBN: (纸本)9789811501357;9789811501340

The fog computing paradigm presents an extension of the cloud computing in order to more ensure the requirements of Internet of things (IoT). Hence, the growth of fog-IoT system and their openness to their socioeconomic environment has led to new needs in terms of security. There are many damages resulting from security breaches and violations. In order to address these challenges, this article proposes a novel framework to further enhance the data security and privacy and the system performance, for the IoT users trying to connect to fog network. In fact, a trust-based monitoring strategy is suggested to avoid system's damages and attacks, and also to maintain low latency, because it is easier to avoid damage resulting from security breaches than to wait for a violation and to try to restore and repair the damage caused. The findings of our evaluation indicate that the proposed monitoring process is an efficient solution for system supervision, and detection and prevention attacks, with a fast processing time.

关键词： Access control IoT Fog computing security Monitoring Trust Risk

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