Risto Pantev

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The ever increasing number of vulnerabilities and reported attacks on Web systems clearly illustrate the need for better understanding of malicious cyber activities, which will allow better protection, detection, and service recovery in the cyberspace. In this paper we use three supervised machine learning methods, Support Vector Machines (SVM), and(More)
Web systems commonly face unique set of vulnerabilities and security threats due to their high exposure, access by browsers, and integration with databases. This study is focused on characterization and classification of malicious cyber activities aimed at Web systems. The empirical analysis is based on three datasets, each in duration of four to five(More)
The widespread use of Web applications, in conjunction with large number of vulnerabilities, makes them very attractive targets for malicious attackers. The increasing popularity of Web 2.0 applications, such as blogs, wikis, and social sites, makes Web servers even more attractive targets. In this paper we present empirical analysis of attackers activities(More)
The number of vulnerabilities and attacks on Web systems show an increasing trend and tend to dominate on the Internet. Furthermore, due to their popularity and users ability to create content, Web 2.0 applications have become particularly attractive targets. These trends clearly illustrate the need for better understanding of malicious cyber activities(More)
Web-based systems commonly face unique set of vulnerabilities and security threats due to their high exposure, access by browsers, and integration with databases. In this paper we present empirical analysis of attackers activities based on data collected by two high-interaction honeypots. The contributions of our work include: (1) Classification of the(More)
Malwares on the websites can be harmful for the host machine. It may result in security breach, data loss, or denial of service at the host end. Many approaches for malware prediction have been applied in the past. Supervised machine learning approaches are popular and efficient in terms of accuracy. These techniques can be very useful for malware(More)
The purpose of this work is to show that the Hitchin integrable system for a simple complex Lie group G is dual to the Hitchin system for the Langlands dual group G. In particular, the general fiber of the connected component Higgs0 of the Hitchin system for G is an abelian variety which is dual to the corresponding fiber of the connected component of the(More)
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