Abstract Due to the increasing sophistication of cyber‐attacks, intrusion detection systems need to be improved constantly. Each machine learning classifier has different advantages against intrusion detection and combining the advantages of different classifiers increases detection rates. In this study, we combine a machine learning classifier with a deep learning model to propose a new approach called GRU‐GBM. The LightGBM gradient boosting machine framework is used for feature selection, and each feature in the dataset is evaluated by a second LightGBM classifier to determine the optimal feature set using a novel threshold‐based approach. After the selection of the feature set, a gated recurrent unit is used for attack detection by a recurrent neural network model. Besides, different training/testing ratios (60/40–70/30) are chosen for comparison of GRU‐GBM accuracy. The proposed combined model achieved 76.61% and 93.65% overall accuracy in multi‐class experiments conducted with the UNSW‐NB15 and LITNET‐2020 datasets, respectively. Lastly, the GRU‐GBM model is compared to other machine learning models. The overall accuracy result is tested with a non‐parametric Friedman test to determine the significance of the results. The test result shows that there is enough evidence that the accuracy of the GRU‐GBM classifier is statistically significant.

Types and complexity of information security related vulnerabilities are growing rapidly and present numerous challenges to the enterprises. One of the key challenges is to identify the optimal set of precautions with limited budget. Despite the fact that majority of enterprises have a budget constraint for installing and maintaining the protection systems, the majority of the previous work only focus on prioritization of security targets and do not consider the preventative actions and budget constraints. This article presents a decision support system (DSS) based on analytical hierarchical process and mixed integer programming techniques for optimal selection of enterprise information security preventative actions. The proposed approach enables maximizing the amount of risk prevented for a fixed amount of budget by identifying the optimal set of precautions. The new DSS also assists enterprise decision-makers in determining the minimum enterprise information security budget for a given level of risk. The main contribution of the paper is that it provides a risk management method to identify a multi-level threat model and the corresponding optimal combination of preventative actions for an enterprise while considering the budget constraints. The treemap information visualization technique is also integrated into the proposed method to improve information security related management decisions.

Spatial hearing enables translation of an auditory scene into a perceived 3-D image by interpreting the acoustic cues related to the sounding objects, their locations, and the physical characteristics of the space. Spatial audio production requires multichannel audio signals in order to convey this information and increase the realism of a real or virtual environment for applications such as the home entertainment, virtual reality, and remote collaboration. As demand to spatial audio continues to expand, efficient coding of multichannel audio content becomes more and more important. This paper provides an overview of some well-known multichannel audio coding techniques and presents a new coding framework for improving the objective fidelity of the decoded signals. A closed-loop encoding system based on analysis-by-synthesis (AbS) principle applied on the MPEG surround (MPS) architecture is described. Comparison results are presented, which show that significant improvements can be achieved with a closed-loop system instead of the conventional open-loop system.

Delivery of 3D immersive entertainment to the home remains a highly challenging problem due to the large amount of data involved, and the need to support a wide variety of different displays. Support of such displays may require different numbers of views, delivered over time varying networks. This requires a delivery scheme featuring scalable compression to adapt to varying network conditions, and error resiliency to overcome disturbing losses in the 3D perception. Audio and video attention models can be used in designing an optimal content-aware compression and transmission scheme, by prioritizing the most visually important areas of the video. This paper gives an overview of a content-aware, scalable multi-view audiovisual entertainment delivery framework. Results are shown to evaluate the kinds of error robustness improvements that could be seen using such a system.

Free viewpoint video enables the visualisation of a scene from arbitrary viewpoints and directions. However, this flexibility in video rendering provides a challenge in 3D media for achieving spatial synchronicity between the audio and video objects. When the viewpoint is changed, its effect on the perceived audio scene should be considered to avoid mismatches in the perceived positions of audiovisual objects. Spatial audio coding with such flexibility requires decomposing the sound scene into audio objects initially, and then synthesizing the new scene according to the geometric relations between the A/V capturing setup, selected viewpoint and the rendering system. This paper proposes a free viewpoint audio coding framework for 3D media systems utilising multiview cameras and a microphone array. A real-time source separation technique is used for object decomposition followed by spatial audio coding. Binaural, multichannel sound systems and wave field synthesis systems are addressed. Subjective test results shows that the method achieves spatial synchronicity for various viewpoints consistently, which is not possible by conventional recording techniques.

Digital waveguide mesh (DWM) models are time-domain numerical methods providing computationally simple solutions for wave propagation problems. They have been used in various acoustical modeling and audio synthesis applications including synthesis of musical instrument sounds and speech, and modeling of room acoustics. A successful model of room acoustics should be able to account for source and receiver directivity. Methods for the simulation of directional sources in DWM models were previously proposed. This paper presents a method for the simulation of directional microphones in DWM-based models of room acoustics. The method is based on the directional weighting of the microphone response according to the instantaneous direction of incidence at a given point. The direction of incidence is obtained from instantaneous intensity that is calculated from local pressure values in the DWM model. The calculation of instantaneous intensity in DWM meshes and the directional accuracies of different mesh topologies are discussed. An intensity-based formulation for the response of a directional microphone is given. Simulation results for an actual microphone with frequency-dependent, non-ideal directivity function are presented.

This article presents a technique that uses the intensity vector direction exploitation (IVDE) method for exhaustive separation of convolutive mixtures. While only a four-element compact sensor array is used, multiple channels for all possible source directions are produced by exhaustive separation. Singular value decomposition (SVD) is then applied to determine the signal subspace and the directions of the local maxima of the signal energy. This information is then used to select the channels containing the individual sources. While the original IVDE method requires the prior knowledge of the directions of sources for separation, the present method eliminates this need and achieves fully blind separation. Performing SVD at a post-processing stage also improves the sound quality. The method has been tested for convolutive mixtures of up to four sources and typical separation performances are given.

Digital waveguide mesh (DWM) models are numerical solvers for the wave equation in -dimensions. They are used for obtaining the traveling-wave solution in practical acoustical modeling applications. Although unstructured meshes can be used with DWMs, regular mesh topologies are traditionally used due to their implementation simplicity. This letter discusses the accuracy of first-order approximations to numerical derivatives on more general unstructured mesh topologies. The results are applied to structured, regular mesh topologies as used in DWM modeling. A comparison of 2-D and 3-D DWM topologies with respect to the accuracy of first-order approximations to numerical derivatives is presented.

Various techniques have previously been proposed for the separation of convolutive mixtures. These techniques can be classified as stochastic, adaptive, and deterministic. Stochastic methods are computationally expensive since they require an iterative process for the calculation of the demixing filters based on a separation criterion that usually assumes that the source signals are statistically independent. Adaptive methods, such as the adaptive beamformers, also exploit signal properties in order to optimize a multichannel filter structure. However, these algorithms need initialization and time to converge. Deterministic methods, on the other hand, provide a closed-form solution based on the deterministic aspects of the problem, such as the channel characteristics and the source directions. This paper presents a technique that exploits the intensity vector statistics to achieve a nearly closed-form solution for the separation of the convolutive mixtures as recorded with a coincident microphone array. No assumptions are made on the signals, but it is assumed that the source directions are known a priori. Directivity functions based on von Mises functions are designed for beamforming depending on the circular statistics of the calculated intensity vectors. Numerical evaluation results were presented for various speech and instrument sounds and source positions in two reverberant rooms.

Digital waveguide mesh (DWM) models offer a simple, accurate, time-domain, numerical solution of the wave equation. A specific case where such accurate and computationally simple solutions are needed is the acoustical modeling of open or closed volumes. It is possible to model 3-D propagation of waves in enclosures such as rooms using DWM models. Generally, idealized omnidirectional sources are used for obtaining the impulse response in the DWM. However, real-life sound sources are never completely isotropic, causing wavefronts with directional properties. This paper presents two methods to simulate analytical and empirical directivities in 3-D DWM models in the far-field. The first method is based on the direct excitation of the mesh with the velocity component of the directional source and is used to simulate analytical sources. The second method is based on the weighting of velocity components generated by an omnidirectional source at different octave-bands and is used to simulate sources with frequency-dependent empirical directivity functions. A simple interpolation method for obtaining a closed-form description of the directivity function from incomplete directivity data is also proposed. Simulation results are presented for two sources in an acoustical model of a rectangular room.

Fractional-delay filter is the general name given to filters modelling non-integer delays. Such filters have a flat phase delay for a wide frequency band, with the value of the phase delay approximating the fractional delay. A maximally-flat delay IIR fractional-delay filter can be obtained by the Thiran approximation. A simple and efficient method for obtaining filters modelling intermediate fractional delays from two Thiran fractional-delay filters is proposed. The proposed method allows continuously modifying the fractional delay. Computational complexity of the proposed method is discussed. A practical application of the method in model-based sound synthesis is given as an example