Gotowe bibliografie tematyczne / Vulnerability discovery model (VDM)

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Gotowa bibliografia na temat „Vulnerability discovery model (VDM)”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Vulnerability discovery model (VDM)"

Sharma, Ruchi, Ritu Sibal, and A. K. Shrivastava. "Vulnerability Discovery Modeling for Open and Closed Source Software." International Journal of Secure Software Engineering 7, no. 4 (2016): 19–38. http://dx.doi.org/10.4018/ijsse.2016100102.

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With growing concern for security, the researchers began with the quantitative modeling of vulnerabilities termed as vulnerability discovery models (VDM). These models aim at finding the trend of vulnerability discovery with time and facilitate the developers in patch management, optimal resource allocation and assessing associated security risks. Among the existing models for vulnerability discovery, Alhazmi-Malaiya Logistic Model (AML) is considered the best fitted model on all kinds of datasets. But, each of the existing models has a predefined basic shape and can only fit datasets followin

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Wang, Xiajing, Rui Ma, Binbin Li, Donghai Tian, and Xuefei Wang. "E-WBM: An Effort-Based Vulnerability Discovery Model." IEEE Access 7 (2019): 44276–92. http://dx.doi.org/10.1109/access.2019.2907977.

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Taib, Abidah Hj Mat, Wan Nor Ashiqin Wan Ali, and Nurul Sharidah Shaari. "ICMPV6 Vulnerability." International Journal of Mobile Computing and Multimedia Communications 5, no. 2 (2013): 78–100. http://dx.doi.org/10.4018/jmcmc.2013040106.

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Handling Internet Control Message Protocol version 6 (ICMPv6) vulnerabilities is among the challenges in securing the IPv6 deployment. Since ICMPv6 messages are crucial in IPv6 communications, this paper discusses the discovery of ICMPv6 vulnerabilities by producing a threat model of ICMPv6 vulnerabilities and proposing the use of Selective Filtering ICMPv6 Messages (SF-ICMP6) to handle some of the vulnerabilities. An experiment was conducted to verify the threat model by observing and discussing the usage of ICMPv6 threat model together with SF-ICMP6. The findings showed that the attack deriv

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Kansal, Yogita, P. K. Kapur, Uday Kumar, and Deepak Kumar. "User-dependent vulnerability discovery model and its interdisciplinary nature." Life Cycle Reliability and Safety Engineering 6, no. 1 (2017): 23–29. http://dx.doi.org/10.1007/s41872-017-0003-y.

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Johnston, Reuben, Shahryar Sarkani, Thomas Mazzuchi, Thomas Holzer, and Timothy Eveleigh. "Bayesian-model averaging using MCMCBayes for web-browser vulnerability discovery." Reliability Engineering & System Safety 183 (March 2019): 341–59. http://dx.doi.org/10.1016/j.ress.2018.11.030.

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Bhatt, Navneet, Adarsh Anand, V. S. S. Yadavalli, and Vijay Kumar. "Modeling and Characterizing Software Vulnerabilities." International Journal of Mathematical, Engineering and Management Sciences 2, no. 4 (2017): 288–99. http://dx.doi.org/10.33889/ijmems.2017.2.4-022.

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With the association of software security assurance in the development of code based systems; software developers are relying on the Vulnerability discovery models to mitigate the breaches by estimating the total number of vulnerabilities, before they’re exploited by the intruders. Vulnerability Discovery Models (VDMs) provide the quantitative classification of the flaws that exists in a software that will be discovered after a software is released. In this paper, we develop a vulnerability discovery model that accumulate the vulnerabilities due to the influence of previously discovered vulner

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Anand, Adarsh, Navneet Bhatt, and Deepti Aggrawal. "Modeling Software Patch Management Based on Vulnerabilities Discovered." International Journal of Reliability, Quality and Safety Engineering 27, no. 02 (2019): 2040003. http://dx.doi.org/10.1142/s0218539320400033.

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A software system deals with various security implications after its release in the market. Correspondingly, firm releases security patches to counter those flaws discovered in the software system. A vendor releases a patch only if a vulnerability has been discovered in a software. It is an important aspect that encompasses the prediction of potential number of patches to be released to maintain the stability of a software. Vulnerability Discovery Models (VDMs) help a software vendor to acknowledge the security trends, forecast security investments and to plan patches, but very few attempts ha

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Yuan, Xue, Guanjun Lin, Yonghang Tai, and Jun Zhang. "Deep Neural Embedding for Software Vulnerability Discovery: Comparison and Optimization." Security and Communication Networks 2022 (January 18, 2022): 1–12. http://dx.doi.org/10.1155/2022/5203217.

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Due to multitudinous vulnerabilities in sophisticated software programs, the detection performance of existing approaches requires further improvement. Multiple vulnerability detection approaches have been proposed to aid code inspection. Among them, there is a line of approaches that apply deep learning (DL) techniques and achieve promising results. This paper attempts to utilize CodeBERT which is a deep contextualized model as an embedding solution to facilitate the detection of vulnerabilities in C open-source projects. The application of CodeBERT for code analysis allows the rich and laten

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U. Rahane, Kavita, and A. B. Pawar. "A REVIEW ON CYBERSECURITY VULNERABILITY DISCOVERY AND MITIGATION MODEL IN SMART COMPUTING." International Journal of Engineering Applied Sciences and Technology 09, no. 05 (2024): 68–77. http://dx.doi.org/10.33564/ijeast.2024.v09i05.008.

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Smart computing links physical and digital objects which communicate online using sensors, software, and other technologies. It offers many advantages but lacks information security, it could potentially face serious problems. The number of smart computing devices are growing rapidly around the world, making them a target of many attackers, whose aim is to steal confidential data and threaten user's privacy. With features like confidentiality, access control, correctness, completeness, authentication, availability, and privacy. Data and services should be safeguarded in the ecosystem. It has p

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Narang, Swati, P. K. Kapur, D. Damodaran, and A. K. Shrivastava. "Bi-Criterion Problem to Determine Optimal Vulnerability Discovery and Patching Time." International Journal of Reliability, Quality and Safety Engineering 25, no. 01 (2018): 1850002. http://dx.doi.org/10.1142/s021853931850002x.

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In the last decade, we have seen enormous growth in software security related problems. This is due to the presence of bad guys who keep eye on the software vulnerabilities and create the security breach. Because of which software firms face huge loss. The problems of the software firms is two folded. One is to decide the optimal discovery time of the software vulnerability and another one is to determine the optimal patching time of those discovered vulnerability. Optimal discovery time of vulnerability is necessary as not disclosing the vulnerability on time may cause serious loss in the com

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Rozprawy doktorskie na temat "Vulnerability discovery model (VDM)"

Narciso, André Filipe Tarrucha. "Industrial IT security management supported by an asset management database." Master's thesis, 2019. http://hdl.handle.net/10071/22227.

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Managing the security of Information Technology (IT) systems and assets throughout their lifecycle is a very complex and important task for organisations, where the number of external threats and vulnerabilities in industrial systems continues to grow. Managing the complexity and having a clear system overview of all assets within industrial infrastructures are key challenges. Beyond that, there is no welldefined data structure to organize all data about IT assets from different industrial sources. This study describes a solution to support security management of industrial IT assets, deve

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Części książek na temat "Vulnerability discovery model (VDM)"

Anand, Adarsh, Navneet Bhatt, and Omar H. Alhazmi. "Vulnerability Discovery Models (VDMs)." In Software Vulnerability Discovery Process: Concepts and Applications. River Publishers, 2024. https://doi.org/10.1201/9781003605690-3.

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Zhou, Ke, Jieren Cheng, Hui Li, Yuming Yuan, Le Liu, and Xiulai Li. "SC-VDM: A Lightweight Smart Contract Vulnerability Detection Model." In Data Mining and Big Data. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7476-1_13.

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Du, Chunlai, Xingbang Tan, and Yanhui Guo. "A Gray-Box Vulnerability Discovery Model Based on Path Coverage." In Lecture Notes in Computer Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24268-8_1.

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Colvin, Robert J., and Roger C. Su. "Structural Operational Semantics for Functional and Security Verification of Pipelined Processors." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-98668-0_18.

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Abstract The design of computer microarchitectures is a challenging task, involving a trade-off between efficiency and security. In the literature, two concerns which are affected by the details of the microarchitecture – formal assembly semantics, and vulnerability discovery and mitigation – are often addressed separately. In this paper we provide a structural operational semantics for pipelined microprocessors (Arm, x86, RISC-V) that is based on a regular understanding of microarchitectural features (pipelines, branch prediction, caches, privilege checks), conforms to established memory cons

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Alauthman, Mohammad, Ammar Almomani, Samer Aoudi, Ahmad al-Qerem, and Amjad Aldweesh. "Automated Vulnerability Discovery Generative AI in Offensive Security." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-0832-6.ch013.

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This chapter investigates how generative AI techniques transform offensive security. It explores automated methods that identify software flaws, generate targeted exploits, and support penetration testers in analyzing systems. Emphasis is placed on large language models and generative adversarial networks, which accelerate fuzzing processes and code reviews, uncovering complex or obscure vulnerabilities. Case studies detail how these AI-driven approaches drastically reduce time and effort compared to traditional methods, while also highlighting ethical concerns related to model hallucinations,

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Zheng, Junjun, Hiroyuki Okamura, and Tadashi Dohi. "Pull-Type Security Patch Management in Intrusion Tolerant Systems: Modeling and Analysis." In Maintenance Management - Current Challenges, New Developments, and Future Directions. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.105766.

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In this chapter, we introduce a stochastic framework to evaluate the system availability of an intrusion tolerant system (ITS), where the system undergoes patch management with a periodic vulnerability checking strategy, i.e., pull-type patch management. In particular, a composite stochastic reward net (SRN) is developed to capture the overall system behaviors, including vulnerability discovery, intrusion tolerance, and reactive maintenance operations. Furthermore, two kinds of availability criteria, the interval availability and the steady-state availability of the system, are formulated by a

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Streszczenia konferencji na temat "Vulnerability discovery model (VDM)"

Narang, Swati, P. K. Kapur, D. Damodaran, and A. K. Shrivastava. "User-based multi-upgradation vulnerability discovery model." In 2017 6th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). IEEE, 2017. http://dx.doi.org/10.1109/icrito.2017.8342459.

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Shukla, Ankur, and Basel Katt. "Change Point Problem in Security Vulnerability Discovery Model." In 2019 International Conference on Software Security and Assurance (ICSSA). IEEE, 2019. http://dx.doi.org/10.1109/icssa48308.2019.00010.

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Jabeen, Gul, Luo Ping, Junaid Akram, and Akber Aman Shah. "An Integrated Software Vulnerability Discovery Model based on Artificial Neural Network." In The 31st International Conference on Software Engineering and Knowledge Engineering. KSI Research Inc. and Knowledge Systems Institute Graduate School, 2019. http://dx.doi.org/10.18293/seke2019-168.

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Wen Tang, Ai-Fen Sui, and Wolfgang Schmid. "A model guided security vulnerability discovery approach for network protocol implementation." In 2011 IEEE 13th International Conference on Communication Technology (ICCT). IEEE, 2011. http://dx.doi.org/10.1109/icct.2011.6157962.

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Shrivastava, A. K., Ruchi Sharma, and P. K. Kapur. "Vulnerability discovery model for a software system using stochastic differential equation." In 2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE). IEEE, 2015. http://dx.doi.org/10.1109/ablaze.2015.7154992.

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Yang, Shang yang, and Long yun Zhang. "Application of fuzzy variable set model to evaluation of agriculture drought vulnerability." In 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2010. http://dx.doi.org/10.1109/fskd.2010.5569201.

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Sorrentino, Julia, Priscila Silva, Gaspard Baye, Gokhan Kul, and Lance Fiondella. "Covariate Software Vulnerability Discovery Model to Support Cybersecurity Test & Evaluation (Practical Experience Report)." In 2022 IEEE 33rd International Symposium on Software Reliability Engineering (ISSRE). IEEE, 2022. http://dx.doi.org/10.1109/issre55969.2022.00025.

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Ensina, L. A., P. E. M. Karvat, E. C. de Almeida, and L. E. S. de Oliveira. "Fault Location in Transmission Lines based on LSTM Model." In Symposium on Knowledge Discovery, Mining and Learning. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/kdmile.2022.227805.

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Transmission lines are fundamental components of the electric power system, demanding special attention from the protection system due to the vulnerability of these lines. This paper presents a method for fault location in transmission lines using data for a single terminal without requiring explicit feature engineering by a domain expert. The fault location task provides an approximate position of the point of the line where the failure occurred, serving as information to the operators to dispatch a maintenance staff to this location to reclose the transmission line with better reliability an

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Melo, Eduardo, Elisa Tuler, and Leonardo Rocha. "Combining Data Mining Techniques to Analyse Factors Associated with Allocation of Socioeconomic Resources at IFMG." In Symposium on Knowledge Discovery, Mining and Learning. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/kdmile.2021.17465.

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The granting of socioeconomic assistance to students from Federal Education Institutions is one of the ways found to provide finantial support during their studies, focusing primarily on those who are more socially vulnerable. Institutions carry out selection processes to identify students with a profile of demand and appropriately distribute the grants according to the budget available for this purpose. This article applied Data Mining techniques to a set of information from students who applied to receive scholarships at IFMG - Campus Bambuí, seeking to identify the attributes associated wit

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Shekhawat, Deependra, and Siddharth Saboo. "Fortifying the Energy Frontier: Overcoming Cybersecurity Challenges in the Oil and Gas Industry Through Resilient Strategies and Innovative Solutions." In ADIPEC. SPE, 2024. http://dx.doi.org/10.2118/222471-ms.

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Abstract The oil and gas industry, a vital lifeline fueling the global economy, find itself at a pivotal juncture where the convergence of operational technology (OT) and information technology (IT) has ushered in unprecedented opportunities and challenges. As digital transformation sweeps across this sector, the imperative to fortify cybersecurity defenses against ever-evolving threats has become paramount. Innovative and forward-looking oil and gas organizations across the globe are adopting the Cloud in many forms because of their digital transformation initiatives. Data lakes, edge technol

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