Thematische Bibliographien / Network-hardening

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Auswahl der wissenschaftlichen Literatur zum Thema „Network-hardening“

Autor: Grafiati

Veröffentlicht am 29. Juni 2021

Zuletzt aktualisiert am 17. Februar 2022

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Zeitschriftenartikel zum Thema "Network-hardening"

Zhao, Chao, Huiqiang Wang, Junyu Lin, Hongwu Lv und Yushu Zhang. „A Generation Method of Network Security Hardening Strategy Based on Attack Graphs“. International Journal of Web Services Research 12, Nr. 1 (Januar 2015): 45–61. http://dx.doi.org/10.4018/ijwsr.2015010104.

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Analyzing attack graphs can provide network security hardening strategies for administrators. Concerning the problems of high time complexity and costly hardening strategies in previous methods, a method for generating low cost network security hardening strategies is proposed based on attack graphs. The authors' method assesses risks of attack paths according to path length and the common vulnerability scoring system, limits search scope with a threshold to reduce the time complexity, and lowers cost of hardening strategies by using a heuristic algorithm. The experimental results show that the authors' method has good scalability, and significantly reduces cost of network security hardening strategies with reasonable running time.

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Manzanares, Antonio Izquierdo. „Hardening Network Infrastructure: Not Suitable for Everyone“. IEEE Distributed Systems Online 8, Nr. 10 (Oktober 2007): 4. http://dx.doi.org/10.1109/mdso.2007.4384584.

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Wang, Lingyu, Steven Noel und Sushil Jajodia. „Minimum-cost network hardening using attack graphs“. Computer Communications 29, Nr. 18 (November 2006): 3812–24. http://dx.doi.org/10.1016/j.comcom.2006.06.018.

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Pan, Zhong Feng, Gui Cheng Wang, Chong Lue Hua und Hong Jie Pei. „Research and Development of LM Neural Network Prediction System for Grind-Hardening“. Key Engineering Materials 416 (September 2009): 248–52. http://dx.doi.org/10.4028/www.scientific.net/kem.416.248.

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An improved neural network based on L-M algorithm has been applied to the prediction of the grind-hardening parameters against to the slow convergence rate of conventional BP neural network. And the the neural network model for grind-hardening is established. The neural network prediction system for grind-hardening process has been developed based on L-M algorithm. The functions of system is analyzed, particularly and some pivotal technology to realize the system are put forward.

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Borbor, Daniel, Lingyu Wang, Sushil Jajodia und Anoop Singhal. „Surviving unpatchable vulnerabilities through heterogeneous network hardening options“. Journal of Computer Security 26, Nr. 6 (30.10.2018): 761–89. http://dx.doi.org/10.3233/jcs-171106.

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Myung, David, Wongun Koh, Jungmin Ko, Yin Hu, Michael Carrasco, Jaan Noolandi, Christopher N. Ta und Curtis W. Frank. „Biomimetic strain hardening in interpenetrating polymer network hydrogels“. Polymer 48, Nr. 18 (August 2007): 5376–87. http://dx.doi.org/10.1016/j.polymer.2007.06.070.

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Lambiase, F., A. M. Di Ilio und A. Paoletti. „Prediction of Laser Hardening by Means of Neural Network“. Procedia CIRP 12 (2013): 181–86. http://dx.doi.org/10.1016/j.procir.2013.09.032.

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Bouzid, Mehdi, und Emanuela Del Gado. „Network Topology in Soft Gels: Hardening and Softening Materials“. Langmuir 34, Nr. 3 (18.10.2017): 773–81. http://dx.doi.org/10.1021/acs.langmuir.7b02944.

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Wu, Xiao Ling, und Fei Ren. „Research on the Prediction Model of Laser Surface Hardening Index on Cylinder Liner Based on RBF“. Advanced Materials Research 148-149 (Oktober 2010): 215–18. http://dx.doi.org/10.4028/www.scientific.net/amr.148-149.215.

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Based on the data obtained from the perpendicular experiment of laser surface hardening on HT150 cylinder liner of a certain motor engine, a Radial Basis Function (RBF) neural network prediction model of laser surface hardening index about HT150 cylinder liner is established by Matlab neural network toolbox in this paper. The parameters of input layer are affirmed by analyzing influential factors of the hardened index ,and the best form of the network is affirmed by selecting suitable spread in function-newrb( ),and as a result, the prediction accuracy and the adaptability of the network are improved. The result of testing the model indicates that the model based on RBF neural network has a good generalizing capability. Compared with traditional Back-Propagation Network (BP network), the result indicates that RBF has better accuracy and adaptability.

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Kemp, R., G. A. Cottrell, H. K. D. H. Bhadeshia, G. R. Odette, T. Yamamoto und H. Kishimoto. „Neural-network analysis of irradiation hardening in low-activation steels“. Journal of Nuclear Materials 348, Nr. 3 (Februar 2006): 311–28. http://dx.doi.org/10.1016/j.jnucmat.2005.09.022.

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Dissertationen zum Thema "Network-hardening"

Pekkanen, Peter, und David Söderman. „Network Hardening of Multilayer Switch“. Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54674.

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In today’s computer networking and industrial networking, security holds a significant role in keeping the entire network safe from malicious users or attackers from remote locations. Using vulnerability scanners and a port scanner it is possible to detect vulnerabilities on the network equipment before an attacker finds the vulnerability and exploits it. In this thesis network hardening has been conducted through a case study on a multilayer switch, with the intent to discover vulnerabilities related to gaining unauthorized access to the device during operation. The tools included in this process involves vulnerability scanner Nessus, Metasploit project and Nmap to cover a wide scope of known vulnerabilities detectable with these tools. The results gathered from the vulnerability scans detects vulnerabilities on the device of various types that could assist an attacker, as they tried to breach the device, this method to approach network hardening shows that different types of vulnerabilities can be detected on the device. To be able to detect more in-depths vulnerabilities and being able to track distinct attacks such as Denial of Service (DoS) additional tools needs to be added to cover a wider scope of attack vectors on the device. With further enhancements to the set of tools to detect vulnerabilities, it will be able to cover a much larger scope of different attack vectors and contribute more towards finding vulnerabilities.

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Elwing-Malmfelt, Linus, und Oscar Keresztes. „Semi-automated hardening of networks based on security classifications“. Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-21793.

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Conducting risk assessments is a vital part of securing information systems. The task of conducting risk assessments is a time-consuming and costly task for organizations. Thus different security control frameworks have been created to assist in the process. These security control frameworks consists of information about what the organization is supposed to implement to achieve a level of security in their information system. To understand what network hardening solution to use and in what part of the system, an analyst needs to manually use the implementation details gathered from the framework. A security control can be split into different security tiers depending on the amount of security the implementation achieves. The security tiers are defined by the authors of the security control framework. An organization can reduce their cost and time spent on implementing the security by having a tool that parses the information system and creates guidelines based on security controls and parsed data. In this research, we will compare different security controls and based on the findings, investigate hardware, software and configurations that are being used when conducting network hardening. We will evaluate to which extent it is possible to generate guidelines that meet the given security tier, whether it is feasible to apply them and present a prototype that is able to generate guidelines. The different security controls will be compared by analyzing the contents of each control in the frameworks. A comprehensive mapping will be created and based on the information gathered in the mapping, network-hardening implementations will be investigated based on the devices in our experiment environment. With implementations at hand, a tool will be proposed that parses information systems and outputs guidelines that integrate the implementations in a readable format. Experts within the field of system hardening then evaluate the created guidelines in terms of achieving defined security levels. For the comparison, a total of 148 different controls were identified to be related in some way. With 148 controls at hand, the prototype can output 111 different guidelines with different security tier associations. According to the comments from the experts, the proposed guidelines were able to satisfy each security tier. Our prototype displayed that we were able to create guidelines that can meet a given security tier. Although the implementation of each guideline is not automated, identifying what network-hardening implementation should be used is done in an automated fashion and thus allowing organizations to put their spending and time into other organizational interests. \newline
Att utföra riskbedömningar är en nödvändig process när ett informations-system ska säkras. Uppgiften med att utföra riskbedömningar är för organisationer en tidskrävande och dyr process. Därför har olika ramverk för säkerhetskontroller tagits fram för att underlätta denna uppgift. Dessa ramverk innehåller information över vad en organisation behöver implementera för att erhålla en specifik nivå av säkerhet i deras informations-system. Den här säkerhetsnivån varierar beroende på hur mycket säkerhet en implementation tillför. De olika nivåerna definieras av ramverksförfattarna. För att förstå vilka nätverkshärdningar organisationen ska använda samt för vilken del i systemet dessa härdningar ska appliceras, behöver en analytiker manuellt gå igenom implementerings-lösningar i ramverken tillsammans med systemet och på så vis ta fram korrekt härdningsåtgärd för en specifik del i systemet. Syftet med arbetet är att jämföra olika säkerhetskontroller och baserat på resultatet undersöka hur hårdvara, mjukvara och konfigurationer kan användas för att härda nätverket. Vi kommer att utvärdera i vilken utsträckning det är möjligt att generera riktlinjer, huruvida det är möjligt att applicera riktlinjerna och ta fram en prototyp som kan generera riktlinjer. De olika ramverken kommer att jämföras genom att innehållet i deras säkerhetskontroller analyseras. En omfattande mappning kommer att tas fram baserat på analysen och utifrån mappningen kommer ytterliggare implementationer rörande nätverkshädrning analyseras. Med hjälp av implementationerna kommer ett verktyg att föreslås vilket analyserar ett informations-system och som producerar riktlinjer som integrerar implementationerna till ett läsbart format. Dessa riktlinjer undersöks sedan av experter gällande hur väl riktlinjerna uppnår definerade säkerhetsnivåer. Under arbetet identifierades totalt 148 olika säkerhets-kontroller som påvisade likhet med varandra. Med dessa 148 kontroller tillgodo klarade vår prototyp av att producera 111 olika riktlinjer tillhörande olika säkerhetsnivåer beroende på systemet som matades in. Enligt kommentarerna ur granskningen som experterna utförde gick följande att konstatera: riktlinjerna som tas fram genom prototypen kunde upprätthålla varje säkerhetsnivå. Vår prototyp påvisade att det var möjligt att skapa riktlinjer som uppnår en efterfrågad säkerhetsnivå. Även om implementering för varje producerad riktlinje inte är automatiserad så kunde vår prototyp automatisera processen av att avgöra vilken nätverks-härdnings implementation som skulle användas för var riktlinje. Detta tillåter organisationer att lägga mer tid och investeringar i andra organisatoriska intressen.

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Simons, William R. „The challenges of network security remediation at a regional university“. [Johnson City, Tenn. : East Tennessee State University], 2005. http://etd-submit.etsu.edu/etd/theses/available/etd-0209105-075524/unrestricted/SimonsW022105f.pdf.

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Thesis (M.S.)--East Tennessee State University, 2005.
Title from electronic submission form. ETSU ETD database URN: etd-0209105-075524 Includes bibliographical references. Also available via Internet at the UMI web site.

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Yildiz, Ersan. „Lateral Pressures On Rigid Retaining Walls : A Neural Network Approach“. Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1264415/index.pdf.

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Lateral pressures on non-yielding walls due to surface strip loads were investigated considering the non-linear stress-strain behaviour of the soil by finite element analyses. Data obtained from the finite element analyses were used to train neural networks in order to obtain a solution to assess the total lateral thrust and its point of application on a non-yielding wall due to a strip load. A 2-layered backpropogation type neural network was used. An artificial neural network solution was obtained, as a function of six parameters including the shear strength parameters of the soil ( cohesion and angle of friction ). The effects of each input parameter on the lateral thrust and point of application were summarized and the results were compared with the conventional linear elastic solution.

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Islam, Tania. „A heuristic approach to network hardening using attack graphs“. Thesis, 2009. http://spectrum.library.concordia.ca/976518/1/MR63037.pdf.

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In defending against multi-step attacks, network hardening answers the following important question: Which vulnerabilities must be removed from a network in order to prevent attackers from compromising critical resources while minimizing the implied cost in terms of availability or administrative efforts. Existing approaches to network hardening derive a logic proposition to represent the negation of the attack goal in terms of initially satisfied security conditions. In the disjunctive normal form (DNF) of the logic proposition, each disjunction then provides a viable solution to network hardening. However, such solutions suffer from an exponential time complexity. In this thesis, we study heuristic methods for solving this important problem with reasonable complexity. We evaluate our proposed solutions through extensive experiments. The results show that our solution can achieve reasonably good network hardening results in significantly less time than the optimal solution would require. Also, for scenarios where additional cost constraints may render a perfectly secure network hardening solution impossible, we extend our heuristic methods to partial hardening solutions. Such solutions can provide best possible improvement in terms of security under given cost constraints.

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Bücher zum Thema "Network-hardening"

Wang, Lingyu, Massimiliano Albanese und Sushil Jajodia. Network Hardening. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04612-9.

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Albanese, Massimiliano (Computer scientist), author und Jajodia Sushil author, Hrsg. Network hardening: An automated approach to improving network security. Cham: Springer, 2014.

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Hardening network infrastructure: [bulletproof your systems before you are hacked!]. New York: McGraw-Hill/Osborne, 2004.

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John, Mallery, Hrsg. Hardening network security. New York: McGraw-Hill/Osborne, 2005.

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Kenyon, Brian. Security Sage's Guide to Hardening the Network Infrastructure. Syngress, 2004.

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Security Sage's Guide to Hardening the Network Infrastructure. Elsevier, 2004. http://dx.doi.org/10.1016/b978-1-931836-01-2.x5000-3.

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Buchteile zum Thema "Network-hardening"

Wang, Lingyu, Massimiliano Albanese und Sushil Jajodia. „Introduction“. In Network Hardening, 1–4. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04612-9_1.

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Wang, Lingyu, Massimiliano Albanese und Sushil Jajodia. „Related Work“. In Network Hardening, 5–13. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04612-9_2.

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Wang, Lingyu, Massimiliano Albanese und Sushil Jajodia. „Attack Graph and Network Hardening“. In Network Hardening, 15–22. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04612-9_3.

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Wang, Lingyu, Massimiliano Albanese und Sushil Jajodia. „Minimum-Cost Network Hardening“. In Network Hardening, 23–38. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04612-9_4.

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Wang, Lingyu, Massimiliano Albanese und Sushil Jajodia. „Linear-Time Network Hardening“. In Network Hardening, 39–58. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04612-9_5.

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Wang, Lingyu, Massimiliano Albanese und Sushil Jajodia. „Conclusion“. In Network Hardening, 59–60. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04612-9_6.

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Camp, L. Jean. „Hardening the Network from the Friend Within“. In Information Security and Privacy, 249. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02620-1_17.

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Kwon, Young-Woo, Eli Tilevich und Taweesup Apiwattanapong. „DR-OSGi: Hardening Distributed Components with Network Volatility Resiliency“. In Middleware 2009, 373–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10445-9_19.

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Bopche, Ghanshyam S., und Babu M. Mehtre. „Exploiting Domination in Attack Graph for Enterprise Network Hardening“. In Communications in Computer and Information Science, 342–53. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22915-7_32.

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Cheng, Chih-Hong. „Safety-Aware Hardening of 3D Object Detection Neural Network Systems“. In Lecture Notes in Computer Science, 213–27. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54549-9_14.

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Konferenzberichte zum Thema "Network-hardening"

Jun-chun, Ma, und Sun Ji-yin. „Optimal Network Hardening Model Based on Parallel Genetic Algorithm“. In 2012 International Conference on Industrial Control and Electronics Engineering (ICICEE). IEEE, 2012. http://dx.doi.org/10.1109/icicee.2012.150.

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Gang, Liu, Ma Yingge, Wang Kejun und Huang Shaobin. „A Domain Security Ontology Network Constructing and Hardening Technology“. In 2014 Fourth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC). IEEE, 2014. http://dx.doi.org/10.1109/imccc.2014.167.

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Man, Dapeng, Yang Wu und Yongtian Yang. „A Method Based on Global Attack Graph for Network Hardening“. In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2008. http://dx.doi.org/10.1109/wicom.2008.1086.

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Albanese, Massimiliano, Sushil Jajodia und Steven Noel. „Time-efficient and cost-effective network hardening using attack graphs“. In 2012 42nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, 2012. http://dx.doi.org/10.1109/dsn.2012.6263942.

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Yigit, Beytullah, Gurkan Gur und Fatih Alagoz. „Cost-Aware Network Hardening with Limited Budget Using Compact Attack Graphs“. In 2014 IEEE Military Communications Conference (MILCOM). IEEE, 2014. http://dx.doi.org/10.1109/milcom.2014.31.

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Chen, Feng, Lingyu Wang und Jinshu Su. „An Efficient Approach to Minimum-Cost Network Hardening Using Attack Graphs“. In 2008 Fourth International Conference on Information Assurance and Security (IAS). IEEE, 2008. http://dx.doi.org/10.1109/ias.2008.38.

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Chao, Zhao, Wang Huiqiang, Guo Fangfang, Zhou Mo und Zhang Yushu. „A Heuristic Method of Attack Graph Analysis for Network Security Hardening“. In 2014 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). IEEE, 2014. http://dx.doi.org/10.1109/cyberc.2014.18.

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Islam, Tania, und Lingyu Wang. „A Heuristic Approach to Minimum-Cost Network Hardening Using Attack Graph“. In 2008 New Technologies, Mobility and Security (NTMS). IEEE, 2008. http://dx.doi.org/10.1109/ntms.2008.ecp.9.

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Zhang, Hangsheng, Haitao Liu, Jie Liang, Ting Li, Liru Geng, Yinlong Liu und Shujuan Chen. „Defense Against Advanced Persistent Threats: Optimal Network Security Hardening Using Multi-stage Maze Network Game“. In 2020 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2020. http://dx.doi.org/10.1109/iscc50000.2020.9219722.

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Morovati, Vahid, Mohammad Ali Saadat und Roozbeh Dargazany. „Modelling Stress Softening and Necking Phenomena in Double Network Hydrogels“. In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-12253.

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Abstract Double network (DN) gels are three-dimensional polymer matrices formed by interpenetrating networks. In contrast to the conventional single-network gels, DN gels have significant toughness, which makes them a promising material for different biomedical and biological applications. However, DN gels show complicated inelastic behavior including the Mullins effect and necking instability. Despite extensive efforts on modelling different aspects of the damage process in gels, the micro-mechanical modelling of the mechanisms that lead to necking in DN gels remains to be a challenging task. Here, a constitutive model is proposed to understand and describe the mechanical behavior of DN gels based on statistical micro-mechanics of interpenetrating polymer networks. DN gels behavior is divided into three parts including pre-necking, necking, and hardening. The first network is dominant in the response of the gel in the pre-necking stage. The breakage of the first network to smaller network fractions (clusters) induces the stress softening observed in this stage. The interaction of both networks and the second network are also considered as main contributors to the response of gel in necking and hardening stages, respectively. The contribution of clusters decreases during the necking as the second network starts hardening. The numerical results of the proposed model are validated and compared by uni-axial cyclic tensile experimental data of DN gels.

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