Książki, monografie, podręczniki, rozdziały (WFTIiMS)
Stały URI dla kolekcjihttp://hdl.handle.net/11652/173
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Pozycja Integrating Anomaly Detection for Enhanced Data Protection in Cloud-Based Applications(Wydawnictwo Politechniki Łódzkiej, 2023) Czerkas, Konrad; Drozd, Michał; Duraj, Agnieszka; Lichy, Krzysztof; Lipiński, Piotr; Morawski, Michał; Napieralski, Piotr; Puchała, Dariusz; Kwapisz, Marcin; Warcholiński, Adrian; Karbowańczyk, Michał; Wosiak, PiotrIn this research, anomaly detection techniques and artificial neural networks were employed to address the issue of attacks on cluster computing systems. The study investigated the detection of Distributed Denial of Service (DDoS) and Partition attacks by monitoring metrics such as network latency, data transfer rate, and number of connections. Additionally, outlier detection algorithms, namely Local Outlier Factor (LOF) and COF, as well as ARIMA and SHESD models were tested for anomaly detection. Two types of neural network architectures, multi-layer perceptron (MLP) and recursive LSTM networks, were used to detect attacks by classifying events as “attack” or “no attack”. The study underscores the importance of implementing proactive security measures to protect cluster computing systems from cyber threats.Pozycja Prediction of Natural Image Saliency for Synthetic Images(Wydawnictwo Politechniki Łódzkiej, 2021) Rudak, Ewa; Rynkiewicz, Filip; Daszuta, Marcin; Sturgulewski, Łukasz; Lazarek, JagodaNumerous saliency models are being developed with the use ofneural networks and are capable of combining various features and predicting the saliency values with great results. In fact, it might be difficult to replace the possibilities of artificial intelligence applied to algorithms responsible for predicting saliency. However, the low-level features are still important and should not be removed completely from new saliency models. This work shows that carefully chosen and integrated features, including a deep learning based one, can be used for saliency prediction. The integration is obtained by using Multiple Kernel Learning. This solution is quite effective, as compared to a few other models tested on the same dataset.Pozycja Hand gestures as a method of interaction in virtual reality HOPA games(Wydawnictwo Politechniki Łódzkiej, 2021) Lamus, Monika; Wiśniewska, Aneta; Szrajber, RafałThe main objective of the study was to implement the intuitive gesture set for movement and interaction in a virtual HOPA game. A review and analysis of existing solutions using the Leap Motion device to track gestures and hand movements was conducted. Two sets of movement modes were created and subjected to a series of tests to determine the best optimal movement and interaction technique. The tests were verified in terms of speed and accuracy of task performance.