U ovom radu izvršena je analiza savremenih visokotehnoloških pretnji koje nastaju kao posledica sigurnosnih propusta u softveru i ranjivosti softverskih proizvoda. Ranjivosti u softverskim proizvodima često nastaju kao posledica primene metodologije brzog razvoja i predstavljaju pretnje koje napadači sa odgovarajućim znanjem i računarskim resursima mogu da iskoriste kako bi stekli neovlašćeni pristup računarskim sistemima i mrežama …
This paper presents a novel approach to the design of robust multimodal biometric cryptosystems. The design objectives behind the system are robustness, privacy of user’s biometric templates and stable cryptographic key generation. The framework presented in this paper employs two modalities and a look-up table …
This paper examines the performance of bare-metal hypervisors within the context of Quality of Service evaluation for Cloud Computing. Special attention is paid to the Linux KVM hypervisors’ different cache modes. The main goal was to define analytical models of all caching modes provided by hypervisor according to the general service time equation …
The research topic that this paper is focused on is intrusion detection in critical network infrastructures, where discrimination of normal activity can be easily corrected, but no intrusions should remain undetected. The IDS presented in this paper is based on SVM that classify unknown data instances according both to the feature values and weight factors that represent importance of features towards the classification …
The KDD Cup ’99 is commonly used dataset for training and testing IDS machine learning algorithms. Some of the major downsides of the dataset are the distribution and the proportions of U2R and R2L instances, which represent the most dangerous attack types, as well as the existence of R2L attack instances identical to normal traffic. This enforces minor category detection complexity and causes problems while building a machine learning model capable of detecting these attacks with sufficiently low false negative rate …
U ovom radu data je kritička analiza skupa podataka KDD Cup ’99 i metodologije istraživanja mašinskog
učenja u oblasti detekcije upada zasnovanih na skupu. Iako se ovaj skup najčešće koristi za obuku, validaciju i testiranje algoritama za mašinsko učenje u IDS sistemima, podaci u skupu nisu verodostojna reprezentacija saobraćaja realne računarske mreže …