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Gotowe bibliografie tematyczne / Network layer (OSI)

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Gotowa bibliografia na temat „Network layer (OSI)”

Autor: Grafiati

Data publikacji: 29 lipca 2024

Data aktualizacji: 30 lipca 2024

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Artykuły w czasopismach na temat "Network layer (OSI)"

1

Ivanov, Valeriy, i Maxim Tereshonok. "Cross-Layer Methods for Ad Hoc Networks—Review and Classification". Future Internet 16, nr 1 (16.01.2024): 29. http://dx.doi.org/10.3390/fi16010029.

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The OSI model used to be a common network model for years. In the case of ad hoc networks with dynamic topology and difficult radio communications conditions, gradual departure is happening from the classical kind of OSI network model with a clear delineation of layers (physical, channel, network, transport, application) to the cross-layer approach. The layers of the network model in ad hoc networks strongly influence each other. Thus, the cross-layer approach can improve the performance of an ad hoc network by jointly developing protocols using interaction and collaborative optimization of multiple layers. The existing cross-layer methods classification is too complicated because it is based on the whole manifold of network model layer combinations, regardless of their importance. In this work, we review ad hoc network cross-layer methods, propose a new useful classification of cross-layer methods, and show future research directions in the development of ad hoc network cross-layer methods. The proposed classification can help to simplify the goal-oriented cross-layer protocol development.

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Tsuchiya, P. F. "An architecture for network-layer routing in OSI". ACM SIGCOMM Computer Communication Review 17, nr 5 (październik 1987): 185–90. http://dx.doi.org/10.1145/55483.55501.

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Susilawati Susilawati, Marcel Ade Satria, Khaila Mardina, Juniwan Juniwan i Didik Aribowo. "Implementasi Teknologi Komunikasi Data Menggunakan Open System Interconnection (OSI) Untuk Berkirim Pesan Antar Perangkat". Venus: Jurnal Publikasi Rumpun Ilmu Teknik 2, nr 3 (17.05.2024): 124–29. http://dx.doi.org/10.61132/venus.v2i3.307.

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Currently, the development of communication networks has influenced how humans communicate and exchange information. Data communications technology reflects the rapid evolution in the way humans communicate and exchange information. Data communication is the process of exchanging information between two or more devices via a transmission medium, such as cables, radio waves, or other network infrastructure. The goal of data communications is to transfer data from one location to another quickly, efficiently, and accurately. The method used is to look for references from several internet sources such as Google. The OSI model has 7 layers, namely Application Layer, Presentation layer, Session Layer, Transport layer, Network layer, data link layer, physical layer

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Sudaryanto, Sudaryanto. "THE EFFECT OF MULTI LAYER SWITCHING FOR DATA TRANSFER SPEEDS ON COMPUTER NETWORK". Compiler 7, nr 2 (29.10.2018): 85. http://dx.doi.org/10.28989/compiler.v7i2.372.

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The need for efficient, stable, fast and reliable network access is influenced by network quality, one of the factors influencing network quality is the management of network devices, while the network devices that are enforced are the Lancard, cable, Switch, Router, Wifi Access Point and Compuitary System . In this study researchers will focus on the influence of Multilayer Switch network devices for data transfer speeds on computer networks. Data transfer speed at layer 2 text data, image data, video data faster 0,85 % than for speed tranfers on layer 3 text data, image data, video data.Keyword: Network, Switch Multilayer, Data Tranfer, Osi Layer

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Agrawal, Nitin Kumar, Shaamshad Alam i Harshit Raghav. "Osi Model: The Basics Structure of Network Communication". International Journal of Recent Technology and Engineering 9, nr 5 (30.01.2021): 66–69. http://dx.doi.org/10.35940/ijrte.d4991.019521.

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In the present time, if we see around the world we can realize that information transfer through one place to another is very easy. A person lives in America easy do business with the person live far away from it. All this can be achieved by the phenomenon known as Networking. And the device through which the information are transferred are called interconnected device. As we know, in present time our need is not only transfer or sharing of information but in a secure way. So with the help of this we are not just transferring the information but in a secure manner To understand the whole phenomenon of this networking, the basic requirement is OSI LAYER Model. This is not just a model but a complete frame which gives us whole information of its working as well as link between them. So through this paper we give some basics concept building of OSI LAYER which help in understanding the Networking

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Karbowski, Andrzej. "Distributed asynchronous algorithms in the Internet – new routing and traffic control methods". Journal of Telecommunications and Information Technology, nr 3 (30.09.2005): 29–36. http://dx.doi.org/10.26636/jtit.2005.3.328.

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The paper presents several new algorithms concerning the third (network) and the fourth (transport) layer of ISO/OSI network model. For the third layer two classes of the shortest paths algorithms – label correcting and auction algorithms – are proposed. For the fourth layer an application of price decomposition to network optimization and Internet congestion control is suggested.

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Mohammed Abdul, Azeem, i Syed Umar. "Attacks of Denial-of-Service on Networks Layer of OSI Model and Maintaining of Security". Indonesian Journal of Electrical Engineering and Computer Science 5, nr 1 (1.01.2017): 181. http://dx.doi.org/10.11591/ijeecs.v5.i1.pp181-186.

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<p>The emergence of wireless sensor networks as one of the technology trends in the coming years, and some special tests of safety. The event will be thousands of tiny sensors that cheap devices, memory, radio and make, in most cases, no access to the production and energy. Some great challenges of sensor networks are different; we focus on security in the form of wireless sensor networks. To some network wireless sensor network in order to optimize use of the sensor, so that the network can be as long as possible. But the management of the important mission of the sensor network, denial of service (DoS) attacks against the destruction of the efficient use of network resources and the vital functions of the network. DoS attacks can be one of the greatest threats to security threats be considered. In fact, there are many different layers of the OSI-DOS.</p>

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Jiang, Jian Feng, Jian Feng Jiang, Xian Zhang i Jin Xia Sun. "Complementary QoS Strategy Research and Application in Large-Scale Switched Networks". Advanced Materials Research 712-715 (czerwiec 2013): 2664–70. http://dx.doi.org/10.4028/www.scientific.net/amr.712-715.2664.

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Large-scale switched networks based on hierarchical architecture put forward higher requirements for the quality of service. This paper analyzes the advantages, disadvantages and the application environment of the traditional QoS architecture based on business according to the second layer and the third layer of the OSI reference model. Then a complementary strategy model integrating Differentiated service model with Integrated service model is designed to enhance the QoS of a large-scale switched network. Simulation results prove that the model can improve the networks QoS in many aspects such as transmission delay, packet loss rate, delay jitter and network throughput.

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Kanaris, Loizos, Charalampos Sergiou, Akis Kokkinis, Aris Pafitis, Nikos Antoniou i Stavros Stavrou. "On the Realistic Radio and Network Planning of IoT Sensor Networks". Sensors 19, nr 15 (24.07.2019): 3264. http://dx.doi.org/10.3390/s19153264.

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Planning and deploying a functional large scale Wireless Sensor Network (WSN) or a Network of Internet of Things (IoTs) is a challenging task, especially in complex urban environments. A main network design bottleneck is the existence and/or correct usage of appropriate cross layer simulators that can generate realistic results for the scenario of interest. Existing network simulators tend to overlook the complexity of the physical radio propagation layer and consequently do not realistically simulate the main radio propagation conditions that take place in urban or suburban environments, thus passing inaccurate results between Open Systems Interconnection (OSI) layers. This work demonstrates through simulations and measurements that, by correctly passing physical information to higher layers, the overall simulation process produces more accurate results at the network layer. It is demonstrated that the resulting simulation methodology can be utilized to accomplish realistic wireless planning and performance analysis of the deployed nodes, with results that are very close to those of real test-beds, or actual WSN deployments.

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Chandnani, Manali, Mukesh Kumar Khandelwal i Meeta Sharma. "A Survey on Synchronization Approach in MAC Layer Protocols". International Journal of Business Data Communications and Networking 13, nr 1 (styczeń 2017): 9–27. http://dx.doi.org/10.4018/ijbdcn.2017010102.

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The Open Systems Interconnection (OSI) model describes the layered approach for communication between two networked systems. The Data link layer of OSI model consists of a sub layer known as MAC layer for achieving coordination among the communicating nodes to access the shared channel. This channel is shared between multiple nodes in a communication network and the packets transmitted at same time by different nodes collide with each other. This situation leads to loss of data and bandwidth gets wasted. To avoid this situation, MAC layer supports various protocols: TDMA, ALOHA, CSMA/CD, CSMA/CA and many hybrid techniques which employ their own criteria of synchronization for minimizing the collisions. In this paper the authors discuss about the MAC layer and the multiple access protocols which it supports for achieving synchronization among the nodes in the channel.

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Rozprawy doktorskie na temat "Network layer (OSI)"

1

Lasorso, Daniel. "Watershed Security Telemetry Network Protocol for Reliability Assurance". University of Cincinnati / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1258576929.

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Barthel, Alexander. "Analysis, Implementation and Enhancement of Vendor dependent and independent Layer-2 Network Topology Discovery". Master's thesis, Universitätsbibliothek Chemnitz, 2005. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200500455.

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This work shows and implements possibilities of OSI Layer-2 Network Topology Discovery based on information from Cisco Discovery Protocol, Spanning Tree Protocol and Switches' Filtering Databases
Diese Arbeit zeigt und implementiert Möglichkeiten zur OSI Layer-2 Netzwerk Topologie Erkennung basierend auf Informationen des Cisco Discovery Protocol, Spanning Tree Protocol und Switch Filter Datenbanken

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Van, Wyk Jacobus Leendert. "Comparing network coding implementations on different OSI layers / Jacobus Leendert van Wyk". Thesis, North-West University, 2010. http://hdl.handle.net/10394/8430.

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Network coding is a technique used to increase the capacity of a network by combining messages sent over the network. The combined messages could be separated by using sufficient original messages which were used to combine the messages. Network coding can be implemented in different layers of the 051 stack, but to date a complete comparison between different implementations of network coding has not been done. The goal of this dissertation is to implement a wireless node model with network coding in the MAC layer and evaluate the performance characteristics of reference networks that implement the new node model. This will serve as the first step of a greater goal, namely finding the most favourable position in the 051 stack to implement network coding. The characteristics of the different implementations of network coding are presented in this dissertation. Simulations were done in OPNET® to find further attributes concerning the implementation of network coding in the MAC layer. The simulation process used is presented and explained, and the results from the simulations are analysed. Network coding in the simulations was implemented opportunistically. The results show that the more often different nodes send frames to the coding node, the better network coding performs. The work contributes to finding the best layer for implementing network coding for its increased throughput. A benchmark network was created so that network coding could be implemented in all the layers of the 051 stack, and then be compared to each other. An implementation of network coding in the MAC layer was simulated and analyzed. We conclude that, because there are so many different purposes for which networks are used, a single instance of network coding is unlikely to be similarly beneficial to all purposes. There still remains work to find the most favourable position for network coding in the 051 stack for all the different types of network coding.
Thesis (M. Ing. (Computer and Electronical Engineering))--North-West University, Potchefstroom Campus, 2011

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Holappa, M. (Mikko). "Performance comparison of LTE eNodeB OSI layer 2 implementations:preemptive partitioned scheduling vs. non-preemptive global scheduling". Master's thesis, University of Oulu, 2013. http://urn.fi/URN:NBN:fi:oulu-201312021941.

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Radio access networks are constantly evolving into a more data intensive direction, emphasizing lower latencies and higher data rates. The growing number of mobile data users and the amount of data they consume requires more data processing capacity from mobile base stations than ever before. As radio access networks evolve according to 3GPP’s plans, so do base station hardware and software. This thesis presents a method for estimating data-link layer processing latencies in an LTE base station. Estimation helps base station manufacturers identify technical performance bottlenecks. It also provides an indication of what level of capacity can be offered to customers. Customers require capacity specifications before products are even implemented so that they can start planning their networks based on these estimated capacity limits. Knowing the capacity limits of new products before they are implemented is a key selling point when the products are being marketed towards network operators. A performance comparison of three different data-link layer implementations of an LTE base station is also presented. Measurement-based worst-case execution time estimation methods are used to create a parameterized model of each implementation. Modeling is done by relating changes in input parameters to changes in the observed execution times using statistical modeling techniques. Measurements are conducted using designed experiments. The resulting models are verified and validated, after which they can be used to estimate processing latencies for different parameter configurations, and to estimate capacity limits of future base station products
Radioliityntäverkkojen kehityksessä on viime aikoina keskitytty viiveiden lyhentämiseen ja tiedonsiirtonopeuksien kasvattamiseen. Mobiilidatan käyttäjien ja heidän käyttämänsä datan kasvava määrä vaatii tukiasemilta enemmän tiedonkäsittelykapasiteettia kuin koskaan aiemmin. Kun radioliityntäverkkoja kehitetään 3GPP:n kehityssuunnitelmien mukaan, samalla kehittyvät myös verkon tukiasemien laitteistot ja ohjelmistot. Tässä työssä esitetään menetelmä, jonka avulla voidaan ennustaa LTE -tukiaseman siirtoyhteyskerroksen latensseja. Ennustaminen auttaa tukiasemavalmistajia tunnistamaan teknisiä suorituskyvyn pullonkauloja. Ennusteet myös tarjoavat mahdollisuuden arvioida, kuinka paljon kapasiteettia uudet tuotteet voivat tukea. Verkko-operaattorit vaativat tietoa uusien tuotteiden kapasiteettirajoituksista jo ennen kuin tuotteet ovat vielä valmiita. He käyttävät tätä tietoa verkkosuunnittelunsa tukena. Kapasiteettirajoitusten tunteminen jo ennen tuotteiden toteutusta on tärkeä myyntivaltti, kun uusia tukiasematuotteita markkinoidaan operaattoreille. Tässä työssä esitetään myös kolmen erilaisen LTE-tukiaseman siirtoyhteyskerroksen toteutuksen suorituskykyvertailu. Mittauksiin perustuvia huonoimman suoritusajan arviointimenetelmiä käytetään luomaan parametrimalli kustakin toteutuksesta. Mallinnus toteutetaan suhteuttamalla parametrien arvojen muutokset niistä aiheutuvien siirtoyhteyskerroksen käsittelylatenssien muutoksiin käyttäen tilastollisia mallinnusmenetelmiä. Mittaukset toteutetaan käyttäen suunniteltuja kokeita. Tuloksena saatavat mallit todennetaan, minkä jälkeen niitä voidaan käyttää ennustamaan käsittelylatensseja eri parametriyhdistelmille. Malleja voidaan käyttää myös ennustamaan tulevien toteutusten tukemaa kapasiteettia ja suorituskykyä

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Spencer, Logan Lemuella C. "Changing from the silo model to the horizontal layers model in public policy regulations : the implications and potential for the telecommunications industry /". Thesis, Available online, Georgia Institute of Technology, 2005, 2005. http://etd.gatech.edu/theses/available/etd-11282005-192311/.

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Muharish, Essa Yahya M. "PACKET FILTER APPROACH TO DETECT DENIAL OF SERVICE ATTACKS". CSUSB ScholarWorks, 2016. https://scholarworks.lib.csusb.edu/etd/342.

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Denial of service attacks (DoS) are a common threat to many online services. These attacks aim to overcome the availability of an online service with massive traffic from multiple sources. By spoofing legitimate users, an attacker floods a target system with a high quantity of packets or connections to crash its network resources, bandwidth, equipment, or servers. Packet filtering methods are the most known way to prevent these attacks via identifying and blocking the spoofed attack from reaching its target. In this project, the extent of the DoS attacks problem and attempts to prevent it are explored. The attacks categories and existing countermeasures based on preventing, detecting, and responding are reviewed. Henceforward, a neural network learning algorithms and statistical analysis are utilized into the designing of our proposed packet filtering system.

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Lai, Hsin-Kai, i 賴莘凱. "Implementation of An OSI Layer 7 Network Packet Filter Based on FPGA Embedded System". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/40434612360841035512.

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碩士
樹德科技大學
資訊工程系碩士班
98
Each internet application can produce a specific type of strings in the packets. Checking these strings on the network is able to block a particular type of internet communication software to achieve the purposes of internet filtering and controlling. The study applies the method of the packet filter on the application layer of OSI (Open Systems Interconnection) to achieve the functions of filtering and controlling for a particular type of internet application. Firstly, a NET-Start!-IXP board is used to design the layer 7 network packet filter, and then the proposed design is transplanted to FPGA embedded system development board. The proposed design possesses the advantages of low cost and high performance. Moreover, the system has web server providing GUI interface in order to facilitate internet management

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Giambene, G., M. Muhammad, D. K. Luong, M. Bacco, A. Gotta, N. Celandroni, Esua K. Jaff i in. "Network coding applications to high bit-rate satellite networks". 2015. http://hdl.handle.net/10454/9155.

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No
Satellite networks are expected to support multimedia traffic flows, offering high capacity with QoS guarantees. However, system efficiency is often impaired by packet losses due to erasure channel effects. Reconfigurable and adaptive air interfaces are possible solutions to alleviate some of these issues. On the other hand, network coding is a promising technique to improve satellite network performance. This position paper reports on potential applications of network coding to satellite networks. Surveys and preliminary numerical results are provided on network coding applications to different exemplary satellite scenarios. Specifically, the adoption of Random Linear Network Coding (RLNC) is considered in three cases, namely, multicast transmissions, handover for multihomed aircraft mobile terminals, and multipath TCP-based applications. OSI layers on which the implementation of networking coding would potentially yield benefits are also recommended.

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Książki na temat "Network layer (OSI)"

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Hemrick, Christine. The OSI Network Layer Addressing scheme, its implications, and considerations for implementation. [Washington, D.C.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1985.

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Hemrick, Christine. The OSI Network Layer Addressing scheme, its implications, and considerations for implementation. [Washington, D.C.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1985.

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Hemrick, Christine. The OSI Network Layer Addressing scheme, its implications, and considerations for implementation. [Washington, D.C.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1985.

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Congress, Library of, i Library of Congress. Network Development and MARC Standards Office., red. Standard Network Interconnection protocols: Specification of the protocol layers for Open Systems Interconnection. Washington: Library of Congress, 1986.

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Lakshman, N. Porting of the lower four OSI layers on to Intel's PCLINK2 ethernet controller card. Bangalore: Dept. of Electrical Communication Engineering, Indian Institute of Science, 1991.

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Bianconi, Ginestra. Structural Correlations of Multiplex Networks. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0007.

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Multiplex networks encode relevant information in their correlated structure, including interlayer degree correlation, link overlap, weight–topology correlations in weighted multiplex networks and activity of the nodes. Interlayer degree correlations among a pair of layers indicates for instance whether or not the hub nodes of one layer are also hub nodes in the other. Link overlap indicates that a finite fraction of nodes are connected in more than one layer. Weight–topology correlations of weighted complex networks reveal that the weight of the links is not random, but often correlated with the link overlap. Finally, the nodes of a multiplex network might be connected only in a subset of the network, leading to a heterogeneity node activity. This chapter identifies the main multiplex network measures for characterizing these correlations, and evaluates their significance using statistical and information theory methods and novel multiplex network measures, including multilinks and multidegrees.

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Congress, Library of. Standard Network Interconnection Protocols: Specification of the Protocol Layers for Open Systems Interconnection. Library of Congress, 1987.

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Bianconi, Ginestra. Classical Percolation, Generalized Percolation and Cascades. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0012.

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This chapter characterizes the robustness of multiplex and multilayer networks using classical percolation, directed percolation and antagonistic percolation. Classical percolation determines whether a finite fraction of nodes of the multilayer networks are connected by any type of connection. Classical percolation can be affected by multiplexity since the degree correlations among different layers can modulate the robustness of the entire multilayer network. Directed percolation describes the propagation of a disease requiring cooperative infection from different layers of the multiplex network. It displays a rich phase diagram including both continuous and discontinuous phase transitions. Antagonist percolation on a duplex network describes the competition between two layers and can give rise to hysteresis loops corresponding to phases that either one layer or the other can percolate Avalanches generated by the generalized Sandpile Model and Watts–Strogatz Model are also discussed, emphasizing their relevance for studying the stability of power grids and financial systems.

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Bianconi, Ginestra. Complex Systems as Multilayer Networks. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0001.

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Chapter 1 constitutes Part I of the book: ‘Single and Multilayer Networks’. This chapter introduces multilayer networks as an important new development of Network Science that allows a more comprehensive understanding of Complex Systems. It identifies the main motivations driving the research activity in this field of multilayer networks and emphasizes the benefits of taking a multilayer network perpective to characterize network data. The main advantages of a multilayer network approach with respect to the more traditional single layer characterization of complex networks are broadly discussed, focusing on the information gain resulting from the analysis of multilayer networks, the non-reducibility of a multilayer network to a large single network and the rich interplay between structure and function in multilayer networks.

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Bianconi, Ginestra. The Structure of Single Networks. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0002.

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Chapters 2–3 constitute Part II of the book, ‘Single Networks’, and provide a reference point for the rest of the book devoted exclusively to Multilayer Networks, making the book self-contained. This chapter provides the relevant background on the network structure of complex networks formed by just one layer (single networks). Here the basic definitions of network structure are given, the major network universalities are presented and methods to extract relevant information from network structure including centrality measures and community detection methods are discussed. Finally, modelling frameworks are introduced including random graphs, growing network models (including notably the Barabasi–Albert Model) and network ensembles.

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Części książek na temat "Network layer (OSI)"

1

Saha, Shilpi, Debnath Bhattacharyya i Tai-hoon Kim. "OSI Layer Wise Security Analysis of Wireless Sensor Network". W Communications in Computer and Information Science, 275–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17641-8_33.

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Howser, Gerry. "The OSI Seven Layer Model". W Computer Networks and the Internet, 7–32. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34496-2_2.

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Howser, Gerry. "The OSI Upper Layers". W Computer Networks and the Internet, 89–104. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34496-2_6.

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Young, Charles E. "OSI Transport and Session Layers". W Computer Network Architectures and Protocols, 349–76. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-0809-6_12.

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Bartoli, Paul D. "OSI Presentation and Application Layers". W Computer Network Architectures and Protocols, 377–98. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-0809-6_13.

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Singhal, Saurabh, i Manju. "Security Metric for Information Network". W IoT-enabled Sensor Networks: Architecture, Methodologies, Security, and Futuristic Applications, 117–24. BENTHAM SCIENCE PUBLISHERS, 2024. http://dx.doi.org/10.2174/9789815049480124060011.

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Given that dislodged working conditions are in play, system administrators are tasked with handling security solutions that, in turn, impact most of the working layers of the OSI model. This comprehensive approach depicts a situation in which the originator perceives that their data is traversing through a specified encryption process at every stage/layer, starting from the top layer (i.e., Application Layer) and gradually proceeding down to the last one (i.e., Physical Layer). Similarly, the decryption process takes place at every stage/layer at the destination end.

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Chambers, A. M. "The Open Systems Interconnection (OSI) Network Layer". W Communications Standards, 11–28. Elsevier, 1986. http://dx.doi.org/10.1016/b978-0-08-034092-0.50006-5.

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A. Jency Priyadharshany, Dr. "IOT COMMUNICATION TECHNOLOGIES". W Futuristic Trends in IOT Volume 3 Book 2, 345–54. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3biio2ch27.

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This chapter consists about the communication of IOT devices and the connectivity of different IOT devices in the network. The IOT communication is based on a framework called open-source interconnection which is comprised of seven layers. Those are physical layer, datalink layer, network layer, transport layer, session layer, presentation layer, application layer. Further, The connectivity of IOT devices in the network with the help of different technologies. In which the technologies are established by different organizations to connect the different types of IOT devices by applying the OSI model of different layers.

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L., Kavisankar, Chellappan C. i Poovammal E. "Against Spoofing Attacks in Network Layer". W Advances in Digital Crime, Forensics, and Cyber Terrorism, 41–56. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0193-0.ch003.

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In the context of network security, a spoofing attack is a condition in which one person or a program successfully masquerades as another. This is done by providing counterfeit data with the malicious intention of gaining an illegitimate advantage. Spoofing attack which may be generated in various layer of Open Systems Interconnection model (OSI model) is discussed in this chapter. The chapter ends with discussing about the possible spoofing attacks in network layer and the relevant defense mechanism of the same. The detailed analysis and discussion is made on the spoofing attack over the Network layer because, Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) attacks more devastating while using network protocol like Internet Protocol (IP) which have become more of a threat than ever for the past few years.

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S, Mayukha, i Vadivel R. "Various Possible Attacks and Mitigations of the OSI Model Layers Through Pentesting – An Overview". W New Frontiers in Communication and Intelligent Systems, 799–809. Wyd. 2023. Soft Computing Research Society, 2023. http://dx.doi.org/10.52458/978-81-95502-00-4-78.

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The OSI model is the traditional way to transmit data from one computer node to another. The transmission distance can differ from the node being in the next cubicle or to the next continent or anywhere in the world. The data is transmitted and received by the nodes that are connected to the internet. Even offline versions of transmission happen within a closed network of wired or wireless connectivity. Whatever the case may be OSI Model plays the most vital role in the transmission of data. The OSI Model has been passed down from generations of computer systems. This is the foundation of data transmission where the security should be at the maximum. The approach in this paper is to provide an eagle's view on the attacks and security at each layer and the methods to mitigate those threats through penetration testing. Preventing an attack before it happens is the smartest move in the cyber field. Routine checks on the mitigation process will prevent a lot of data theft and save face in the future and protect the data and the network. The structure of this paper involves a short OSI model description and its layers. The attacks can be launched by any malicious hacker in each of the layers which can be mimicked through penetration testing. The mitigation process if any, can be performed for these types of attacks. If a system is armed up with security measures at each layer level, the penetration of that node or network would be next to impossible. This is not an easy feat to achieve and would require a whole lot of creative ideas and foolproof systems in place. Security is one of the top concerns in every area of the personal or professional front. Creating a foolproof system for the transmission of data from layer 1 through to layer 7 of the OSI model implemented among computer nodes can guarantee to be an impossible challenge for hackers to crack at. Over time these security measures can become a guideline or a protocol that would be implemented in the OSI Model. Awareness is the first line of defense or offense that can be initiated for mitigating any kind of attack in the cyber world. Only with knowledge of the attack, an enterprise can protect itself from the outside world. This is the first step towards that long road of awareness and mitigation process of attacks performed on the various layers of the OSI Model.

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Streszczenia konferencji na temat "Network layer (OSI)"

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Tsuchiya, P. F. "An architecture for network-layer routing in OSI". W the ACM workshop. New York, New York, USA: ACM Press, 1988. http://dx.doi.org/10.1145/55482.55501.

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Lawniczak, Anna T. "OSI Network-layer Abstraction: Analysis of Simulation Dynamics and Performance Indicators". W SCIENCE OF COMPLEX NETWORKS: From Biology to the Internet and WWW: CNET 2004. AIP, 2005. http://dx.doi.org/10.1063/1.1985388.

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Nikolchev, Kyryl, Kostiantyn Herasymenko, Olena Starkova i Mykola Yastrebov. "Development of Recommendations for the Implementation of Integrated Security in the Corporate Network at the OSI Data Link Layer". W 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T). IEEE, 2020. http://dx.doi.org/10.1109/picst51311.2020.9468014.

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Kim, Myung Soo, i Clark C. Guest. "Opto-neural system for pattern classification". W OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.mjj3.

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An optoneural system, which is a combination of an optical processor and a neural network, is developed for pattern classification. The system takes advantages of the two-dimensional processing capability of optics and the mapping capability of neural networks. The optical processor consists of a binary phase-only filter, and the neural network consists of three nonlinear mapping layers: the input layer, a hidden layer, and the output layer. Correlation outputs of the optical processor are used as inputs to the neural network. Binary phase in the binary phase-only filter and weights of the neural network are simultaneously trained with a simulated annealing algorithm. Gray-tone texture patterns that are not easily classified with annealed binary phase-only filters are well classified with the trained optoneural system.

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Yang, Xiang Y., Francis T. S. Yu i Don A. Gregory. "Optical implementation of the Hamming net". W OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.tuk3.

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The Hamming net is a neural network implementation of the optimum image classifier.1 It is essentially a two-layer neural network. The first layer calculates the Hamming distance between the input pattern and each exemplar, i.e., classes. The second layer, known as MAXNET, selects the node with the maximum output. We have developed a modified Hamming net model in which the effect of the Hamming distance is enlarged. The modified model alleviates the dynamic range requirement to the spatial light modulators and reduces the iteration cycles in the MAXNET. The optical Hamming net is constructed based on an architecture using a lenslet array and inexpensive liquid crystal televisions (LCTVs).2 The input patterns as well as the interconnection weight matrices (IWMs) in both layers are bipolar signals in the Hamming net. To accomplish the bipolar multiplication optically, the IWMs and the input patterns are area modulated before being displayed on the LCTVs. The experimental results have shown that the optical Hamming net has a larger information capacity than other previously reported optical neural networks.2

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Riant, Isabelle, Jean-Marc Verdiell i Mario Dagenais. "Sensitivity of two-layer antireflection coating of semiconductor laser amplifiers". W OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.wu8.

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Direct amplification of light using semiconductor traveling wave amplifiers (TWAs) is expected to play an important role in future optical communication networks. A TWA is obtained by depositing an antireflection (AR) coating on the semiconductor laser facets. High performances require a reflectivity below 10-4 and a large bandwidth covering the whole semiconductor laser spectrum (30-40 nm for AlGaAs devices). Today, the control of the coating parameters, especially the refractive index, remains difficult. In particular, for single-layer coatings, which typically use nonstoichimetric materials, this poor control can drastically increase the reflectivity. To alleviate this problem, we are proposing two-layer coatings, using stable stoichimetric materials. In our analysis, we have investigated the sensitivity of a large number of two-layer coatings to the wavelength, refractive indices, and thicknesses of the different layers. The simulation was carried out for both a plane-wave and a guided-wave model. It was found that the AR coatings can be grouped in several classes, depending on the value of the index and the order of the layers. The combination of TiO2 and MgF2 exhibits a bandwidth close to 30 nm. However, the tolerance of this coating in the value of the upper layer index is tight. This sensitivity can be reduced at the expense of the bandwidth and the tolerance in the value of the lower layer index by using ZrO2 and MgF2.

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Qiao, Yong, i Demetri Psaltis. "Optical two-layer neural network for handwritten-character recognition alphabet". W OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.mjj2.

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We describe a two-layer optical neural network. The system uses photorefraction holograms to implement synaptic interconnections and liquid-crystal light valves (LCLV's) to perform nonlinear thresholding operations. Kanerva's sparse, distributed memory was implemented using this system, and its ability to recognize a handwritten-character alphabet (A-Z) has been demonstrated experimentally in Kanerva's model; the first layer has fixed, random weights of interconnections, and the second layer is trained according to an outer-product scheme. A total of 104 handwritten-character patterns, with four patterns from each class, were used to train the network. When a character pattern is presented at the input of the trained network, one of the 26 output neurons is switched on, indicating which character the input pattern is. For this network to solve more complicated problems, it is desirable to make both layers adaptive. We propose a new local learning rule that trains both layers based only on local information and a global, scalar error signal. This learning rule is much easier to implement than the back-error-propagation algorithm, which requires the backpropagation of error signals through the network, but it still guarantees that the network is trained by energy descent.

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Uang, Chii-Maw, Shizhuo Yin i Francis T. S. Yu. "A two-layer high-content addressable optical neural network". W OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.mt1.

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A two-layer high-content addressable memory, based on the K-nearest neighbor and the winner take all networks, as applied to autoassociation and the heteroassociation models, is given. The architecture is an efficient neural network in which pattern classification can be obtained very easily. In this two-layer model, the total number of interconnections is Ni* M + No* M, where Ni and No are the input neurons and the output neurons respectively, and M is the number of exemplars, which is less than the conventional CAMs. Since the storage capacity can be as high as 2 Ni , the neural network needs only one feedforward training time, such that no feedback iteration is required. Fast convergence is therefore an apparent feature, and the noise performance is better than that of the Hopfield model and the inter-pattern association (IPA) model. Since this network would converge to the nearest exemplar, it would not produce spurious outputs. Computer simulation and experimental results confirm our findings and are provided.

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Savant, Gajendra, Liping Wang i Jay Hirsh. "Dynamic erasable dye-polymer for all-optical neural networks". W OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.thmm9.

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Thus far, neural network models have mostly been implemented on computers and electronic hardware. Although there is a potential for optics to offer high density parallel interconnects at high speeds, optical neural network implementation has been limited to single layer machines confined to solving only a very narrow range of pattern recognition problems. Multilayer neural networks are much more powerful than the single layer machines, because they represent a class of universal approximators; however, no practical implementation has yet been reported. The primary reason for this slow progress in the optical implementation of neural networks is the lack of suitable materials that can provide dense, modifiable synaptic interconnections. As a result of broad material research efforts in organic/polymer media, we have developed a new dynamic holographic erasable dye-polymer material. Using this material, high efficiency polarization holograms can be recorded, selectively enhanced or erased in real time, so that dense, modifiable neural interconnects can be implemented.

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Mu, Guogang, Ying Sun, Yanxin Zhang i Xiangping Yang. "Optoelectronically implemented three-layer neural network for pattern recognition". W OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.tud2.

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A three-layer optoelectronic neural network for recognizing multiplex 3-D objects from arbitrary perspective views is demonstrated. Every kind of object is transformed into its feature codes and then classified by an associative memory of the codes. The experimental system is composed of two stages of different neural networks. The first network is implemented optically, and a bank of SDF filters are used as the interconnection weights. The optical system performs a hetero-association that encodes the projective images into a set of codes. Four kinds of aircraft are chosen as the examples, and 252 training images, which are obtained from different perspective views, are selected for each object. The four kinds of aircraft include airliner, fighter, bomber, and rocket. The experimental results show that the system can recognize correctly most of the projective images, including those outside the training set and partially hidden.

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Raporty organizacyjne na temat "Network layer (OSI)"

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Katz, D. The PPP OSI Network Layer Control Protocol (OSINLCP). RFC Editor, listopad 1992. http://dx.doi.org/10.17487/rfc1377.

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Hagens, R. A., N. E. Hall i M. T. Rose. Use of the Internet as a subnetwork for experimentation with the OSI network layer. RFC Editor, luty 1989. http://dx.doi.org/10.17487/rfc1070.

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Hardcastle-Kille, S. E. Encoding Network Addresses to Support Operation over Non-OSI Lower Layers. RFC Editor, listopad 1991. http://dx.doi.org/10.17487/rfc1277.

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