Common web application attack types and security using ASP.NET

Jovičić, Bojan; Simić, Dejan

doi:10.2298/csis0602083j

Cited by 10 publications

(4 citation statements)

References 4 publications

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“…Privilege escalation [40], password attack [41], advanced persistent threat [42], cryptojacking attack [43], web application attack [41], and so on critical security systems, and which adds to the additional security [3] type of method that identifies the deviations of protocol state. This approach is similar to the anomaly-based method, however, it uses predetermined universal profiles of benign protocol activity [54].…”

Section: Othersmentioning

confidence: 99%

AI-Driven Cybersecurity: An Overview, Security Intelligence Modeling and Research Directions

Furhad²,

2021

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Artificial intelligence (AI) is one of the key technologies of the Fourth Industrial Revolution (or Industry 4.0), which can be used for the protection of Internet-connected systems from cyber threats, attacks, damage, or unauthorized access. To intelligently solve today's various cybersecurity issues, popular AI techniques involving machine learning and deep learning methods, the concept of natural language processing, knowledge representation and reasoning, as well as the concept of knowledge or rule-based expert systems modeling can be used. Based on these AI methods, in this paper, we present a comprehensive view on "AI-driven Cybersecurity" that can play an important role for intelligent cybersecurity services and management. The security intelligence modeling based on such AI methods can make the cybersecurity computing process automated and intelligent than the conventional security systems. We also highlight several research directions within the scope of our study, which can help researchers do future research in the area. Overall, this paper's ultimate objective is to serve as a reference point and guidelines for cybersecurity researchers as well as industry professionals in the area, especially from an intelligent computing or AI-based technical point of view.

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Section: Othersmentioning

confidence: 99%

AI-Driven Cybersecurity: An Overview, Security Intelligence Modeling and Research Directions

Furhad²,

2021

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“…[26]; • Zero-day attack is considered as the term that is used to describe the threat of an unknown security vulnerability for which either the patch has not been released or the application developers were unaware [4] [28]. Besides these attacks mentioned above, privilege escalation [29], password attack [30], insider threat [31], man-in-the-middle [32], advanced persistent threat [33], SQL injection attack [34], cryptojacking attack [35], web application attack [30] etc. are well-known as security incidents in the field of cybersecurity.…”

Section: Cyberattacks and Risksmentioning

confidence: 99%

Cybersecurity Data Science: An Overview from Machine Learning Perspective

Sarker¹

2020

Preprint

111

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In a computing context, cybersecurity is undergoing massive shifts in technology and its operations in recent days, and data science is driving the change. Extracting security incident patterns or insights from cybersecurity data and building corresponding data-driven model, is the key to make a security system automated and intelligent. To understand and analyze the actual phenomena with data, various scientific methods, machine learning techniques, processes, and systems are used, which is commonly known as data science. In this paper, we focus and briefly discuss cybersecurity data science, where the data is being gathered from relevant cybersecurity sources, and the analytics complement the latest data-driven patterns for providing more effective security solutions. The concept of cybersecurity data science allows making the computing process more actionable and intelligent as compared to traditional ones in the domain of cybersecurity. We then discuss and summarize a number of associated research issues and future directions. Furthermore, we provide a machine learning-based multi-layered framework for the purpose of cybersecurity modeling. Overall, our goal is not only to discuss cybersecurity data science and relevant methods but also to focus the applicability towards data-driven intelligent decision making for protecting the systems from cyber-attacks.

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“…Beside these attacks mentioned above, privilege escalation [29], password attack [30], insider threat [31], man-in-the-middle [32], advanced persistent threat [33], SQL injection attack [34], cryptojacking attack [35], web application attack [30] etc. are wellknown as security incidents in the field of cybersecurity.…”

Section: Cyberattacks and Security Risksmentioning

confidence: 99%

Cybersecurity data science: an overview from machine learning perspective

et al. 2020

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In a computing context, cybersecurity is undergoing massive shifts in technology and its operations in recent days, and data science is driving the change. Extracting security incident patterns or insights from cybersecurity data and building corresponding data-driven model, is the key to make a security system automated and intelligent. To understand and analyze the actual phenomena with data, various scientific methods, machine learning techniques, processes, and systems are used, which is commonly known as data science. In this paper, we focus and briefly discuss on cybersecurity data science, where the data is being gathered from relevant cybersecurity sources, and the analytics complement the latest data-driven patterns for providing more effective security solutions. The concept of cybersecurity data science allows making the computing process more actionable and intelligent as compared to traditional ones in the domain of cybersecurity. We then discuss and summarize a number of associated research issues and future directions. Furthermore, we provide a machine learning based multi-layered framework for the purpose of cybersecurity modeling. Overall, our goal is not only to discuss cybersecurity data science and relevant methods but also to focus the applicability towards data-driven intelligent decision making for protecting the systems from cyber-attacks.

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Common web application attack types and security using ASP.NET

Cited by 10 publications

References 4 publications

AI-Driven Cybersecurity: An Overview, Security Intelligence Modeling and Research Directions

AI-Driven Cybersecurity: An Overview, Security Intelligence Modeling and Research Directions

Cybersecurity Data Science: An Overview from Machine Learning Perspective

Cybersecurity data science: an overview from machine learning perspective

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