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The COVID-19 pandemic has induced dramatic effects in all areas of society worldwide. It has led to drastic restrictions on academic exchanges and caused research projects to be put on hold. The need to maintain social distancing has severely affected the research communities that rely on in-person studies. In particular, Quality of Experience (QoE) research relies heavily on user studies and in-person subjective tests as means of obtaining ground truths for system designs. In this position paper, we focus on the impact of COVID-19 on conducting subjective tests for digital media quality assessment. An overview of the related discussions that take place in associated research communities is provided. A number of challenges are posed in terms of hygiene, ethics, standardization, and research quality issues. Opportunities for consolidating QoE research under COVID-19 and beyond are put forward, including alternative experimental designs and adaptation of research methodologies. Numerous enablers are suggested and discussed, revealing various avenues that can be followed to assist in conducting subjective tests under pandemic conditions. We believe that this position paper will be helpful for researchers and practitioners relying on in-person studies to keep abreast about the potential measures that support coming out of the COVID-19 pandemic strong and being prepared for future endeavors. © 2021 IEEE.

The paper presents the research of the stability of the system with a redundancy of communication channels. For this, two prototypes have been developed that are built (1) according to the classical circuit-switched scheme and (2) with an aggregation of several virtual channels. Prototyping, installation on various vehicles and measurements of the stability of the entire system as a whole were carried out. The paper also presents structural diagrams, hardware, and a list of problems and difficulties that the authors encountered during the practical implementation and implementation of these systems. In the future, it is planned to expand the study of these systems when working with high-level channel virtualization and the search for methods to accelerate its work. © 2020 IEEE., This scientific work was partially supported by RAMECS and self-determined research funds of CCNU from the colleges’ primary research and operation of MOE (CCNU19TS022). open access

The paper presents the research of the stability of the system with a redundancy of communication channels. For this, two prototypes have been developed that are built (1) according to the classical circuit-switched scheme and (2) with an aggregation of several virtual channels. Prototyping, installation on various vehicles and measurements of the stability of the entire system as a whole were carried out. The paper also presents structural diagrams, hardware, and a list of problems and difficulties that the authors encountered during the practical implementation and implementation of these systems. In the future, it is planned to expand the study of these systems when working with high-level channel virtualization and the search for methods to accelerate its work. © 2020 IEEE., This scientific work was partially supported by RAMECS and self-determined research funds of CCNU from the colleges’ primary research and operation of MOE (CCNU19TS022). open access

The paper presents the research of the stability of the system with a redundancy of communication channels. For this, two prototypes have been developed that are built (1) according to the classical circuit-switched scheme and (2) with an aggregation of several virtual channels. Prototyping, installation on various vehicles and measurements of the stability of the entire system as a whole were carried out. The paper also presents structural diagrams, hardware, and a list of problems and difficulties that the authors encountered during the practical implementation and implementation of these systems. In the future, it is planned to expand the study of these systems when working with high-level channel virtualization and the search for methods to accelerate its work. © 2020 IEEE., This scientific work was partially supported by RAMECS and self-determined research funds of CCNU from the colleges’ primary research and operation of MOE (CCNU19TS022). open access

The paper presents the research of the stability of the system with a redundancy of communication channels. For this, two prototypes have been developed that are built (1) according to the classical circuit-switched scheme and (2) with an aggregation of several virtual channels. Prototyping, installation on various vehicles and measurements of the stability of the entire system as a whole were carried out. The paper also presents structural diagrams, hardware, and a list of problems and difficulties that the authors encountered during the practical implementation and implementation of these systems. In the future, it is planned to expand the study of these systems when working with high-level channel virtualization and the search for methods to accelerate its work. © 2020 IEEE., This scientific work was partially supported by RAMECS and self-determined research funds of CCNU from the colleges’ primary research and operation of MOE (CCNU19TS022). open access

The paper presents the research of the stability of the system with a redundancy of communication channels. For this, two prototypes have been developed that are built (1) according to the classical circuit-switched scheme and (2) with an aggregation of several virtual channels. Prototyping, installation on various vehicles and measurements of the stability of the entire system as a whole were carried out. The paper also presents structural diagrams, hardware, and a list of problems and difficulties that the authors encountered during the practical implementation and implementation of these systems. In the future, it is planned to expand the study of these systems when working with high-level channel virtualization and the search for methods to accelerate its work. © 2020 IEEE., This scientific work was partially supported by RAMECS and self-determined research funds of CCNU from the colleges’ primary research and operation of MOE (CCNU19TS022). open access

The paper presents the research of the stability of the system with a redundancy of communication channels. For this, two prototypes have been developed that are built (1) according to the classical circuit-switched scheme and (2) with an aggregation of several virtual channels. Prototyping, installation on various vehicles and measurements of the stability of the entire system as a whole were carried out. The paper also presents structural diagrams, hardware, and a list of problems and difficulties that the authors encountered during the practical implementation and implementation of these systems. In the future, it is planned to expand the study of these systems when working with high-level channel virtualization and the search for methods to accelerate its work. © 2020 IEEE., This scientific work was partially supported by RAMECS and self-determined research funds of CCNU from the colleges’ primary research and operation of MOE (CCNU19TS022). open access

This paper contains an analysis of the LockerGoga ransomware that was used in the range of targeted cyberattacks in the first half of 2019 against Norsk Hydra-A world top 5 aluminum manufacturer, as well as the US chemical enterprises Hexion, and Momentive-Those companies are only the tip of the iceberg that reported the attack to the public. The ransomware was executed by attackers from inside a corporate network to encrypt the data on enterprise servers and, thus, taking down the information control systems. The intruders asked for a ransom to release a master key and decryption tool that can be used to decrypt the affected files. The purpose of the analysis is to find out tactics and techniques used by the LockerGoga ransomware during the cryptolocker attack as well as an encryption model to answer the question if the encrypted files can be decrypted with or without paying a ransom. The scientific novelty of the paper lies in an analysis methodology that is based on various reverse engineering techniques such as multi-process debugging and using open source code of a cryptographic library to find out a ransomware encryption model. © 2019 IEEE.

In this paper, we propose a viewing direction weighted bit plane least significant bit (LSB) data hiding method for 360° videos. Normalized Gaussian mixture models (GMMs) of the distributions of the relative viewing direction frequency for latitude, longitude, and both latitude and longitude are used to describe the human viewing behavior of 360° videos on head-mounted displays (HMDs). Apart from formulating data hiding weight functions to control the amount of secret data to be hidden at given latitudes and longitudes, the GMMs are used in this work also to define viewing direction weighted bit plane functions. These viewing direction weighted bit plane functions specify the number of bit planes to be used for data hiding depending on the latitude and longitude. As humans pay more attention to the central front view of 360° videos when watched on HMDs, the number of engaged bit planes is decreased accordingly from the poles to the equator, and from the west and the east to the front view. A performance assessment of the proposed viewing direction weighted bit plane LSB data hiding method is conducted, showing the trade-offs between capacity and objective perceptual video quality. The results indicate that it is preferable to first utilize a given bit plane for data hiding in an entire 360° video frame before engaging the next higher bit plane subject to the viewing direction weighted bit plane functions. © 2021 IEEE.

With the wide spread of digital document use in administrations, fabrication and use of forged documents have become a serious problem. This paper presents a study and classification of the most important works on image and document forgery detection. The classification is based on documents type, forgery type, detection method, validation dataset, evaluation metrics and obtained results. Most of existing forgery detection works are dealing with images and few of them analyze administrative documents and go deeper to analyze their contents. © 2021 IEEE., open access

The development of immersive media systems and services relies on subjective tests that provide ground truth on the quality of experience as perceived by humans. In this paper, we investigate the opinion score consistency through a repeated subjective 360° video quality assessment experiment. The test stimuli are presented on a head-mounted display with participants given the task to rate the video quality in three repeated sessions for both standing and seated viewing. The statistical analysis of the data from the subjective tests aims at revealing if participants change their rating behavior over time or keep their opinion scores given to the test stimuli in standing and seated viewing consistent in a statistical sense. The experimental results are reported in terms of histograms of opinion scores, skewness and kurtosis of opinion scores, mean opinion scores, standard deviation of opinion scores (SOS), SOS fitting functions, and analysis of variance tests. The statistical analysis supports the conjecture that each participant has its own but consistent rating behavior throughout the respective sessions for standing and seated viewing. The finding that the quality rating behavior of the individual participant does not fundamentally change over time may, e.g., assist in scheduling subjective tests under pandemic conditions where experimental campaigns may need to be stalled for an unknown period of time. © 2021 IEEE., open access

This paper describes work in progress of an interdisciplinary research project that focuses on the placement and analysis of public close-circuit television (CCTV) cameras using data-driven analysis of crime data. A novel web-based prototype that acts as a framework for the camera placement analysis with regards to historical crime occurrence is presented. The web-based prototype enables various analyses involving public CCTV cameras e.g., to determine suitable locations for both stationary CCTV cameras as well as temporary cameras that are moved around after a few months to address crime seasonality. The framework also opens up for other analyses, e.g. automatically highlighting crimes that are carried out closed by at least one camera. The research also investigates to what extent it is possible to generate estimates on the amount of detail captured by a camera given the distance to the crime light conditions. The research project includes interdisciplinary competences from various areas such as criminology, computer and data science as well as the Swedish Police. © 2021 IEEE.

In this paper, we propose a viewing direction weighted bit plane least significant bit (LSB) data hiding method for 360° videos. Normalized Gaussian mixture models (GMMs) of the distributions of the relative viewing direction frequency for latitude, longitude, and both latitude and longitude are used to describe the human viewing behavior of 360° videos on head-mounted displays (HMDs). Apart from formulating data hiding weight functions to control the amount of secret data to be hidden at given latitudes and longitudes, the GMMs are used in this work also to define viewing direction weighted bit plane functions. These viewing direction weighted bit plane functions specify the number of bit planes to be used for data hiding depending on the latitude and longitude. As humans pay more attention to the central front view of 360° videos when watched on HMDs, the number of engaged bit planes is decreased accordingly from the poles to the equator, and from the west and the east to the front view. A performance assessment of the proposed viewing direction weighted bit plane LSB data hiding method is conducted, showing the trade-offs between capacity and objective perceptual video quality. The results indicate that it is preferable to first utilize a given bit plane for data hiding in an entire 360° video frame before engaging the next higher bit plane subject to the viewing direction weighted bit plane functions. © 2021 IEEE.

With the wide spread of digital document use in administrations, fabrication and use of forged documents have become a serious problem. This paper presents a study and classification of the most important works on image and document forgery detection. The classification is based on documents type, forgery type, detection method, validation dataset, evaluation metrics and obtained results. Most of existing forgery detection works are dealing with images and few of them analyze administrative documents and go deeper to analyze their contents. © 2021 IEEE., open access

The development of immersive media systems and services relies on subjective tests that provide ground truth on the quality of experience as perceived by humans. In this paper, we investigate the opinion score consistency through a repeated subjective 360° video quality assessment experiment. The test stimuli are presented on a head-mounted display with participants given the task to rate the video quality in three repeated sessions for both standing and seated viewing. The statistical analysis of the data from the subjective tests aims at revealing if participants change their rating behavior over time or keep their opinion scores given to the test stimuli in standing and seated viewing consistent in a statistical sense. The experimental results are reported in terms of histograms of opinion scores, skewness and kurtosis of opinion scores, mean opinion scores, standard deviation of opinion scores (SOS), SOS fitting functions, and analysis of variance tests. The statistical analysis supports the conjecture that each participant has its own but consistent rating behavior throughout the respective sessions for standing and seated viewing. The finding that the quality rating behavior of the individual participant does not fundamentally change over time may, e.g., assist in scheduling subjective tests under pandemic conditions where experimental campaigns may need to be stalled for an unknown period of time. © 2021 IEEE., open access

This paper describes work in progress of an interdisciplinary research project that focuses on the placement and analysis of public close-circuit television (CCTV) cameras using data-driven analysis of crime data. A novel web-based prototype that acts as a framework for the camera placement analysis with regards to historical crime occurrence is presented. The web-based prototype enables various analyses involving public CCTV cameras e.g., to determine suitable locations for both stationary CCTV cameras as well as temporary cameras that are moved around after a few months to address crime seasonality. The framework also opens up for other analyses, e.g. automatically highlighting crimes that are carried out closed by at least one camera. The research also investigates to what extent it is possible to generate estimates on the amount of detail captured by a camera given the distance to the crime light conditions. The research project includes interdisciplinary competences from various areas such as criminology, computer and data science as well as the Swedish Police. © 2021 IEEE.

The development of immersive media systems and services relies on subjective tests that provide ground truth on the quality of experience as perceived by humans. In this paper, we investigate the opinion score consistency through a repeated subjective 360° video quality assessment experiment. The test stimuli are presented on a head-mounted display with participants given the task to rate the video quality in three repeated sessions for both standing and seated viewing. The statistical analysis of the data from the subjective tests aims at revealing if participants change their rating behavior over time or keep their opinion scores given to the test stimuli in standing and seated viewing consistent in a statistical sense. The experimental results are reported in terms of histograms of opinion scores, skewness and kurtosis of opinion scores, mean opinion scores, standard deviation of opinion scores (SOS), SOS fitting functions, and analysis of variance tests. The statistical analysis supports the conjecture that each participant has its own but consistent rating behavior throughout the respective sessions for standing and seated viewing. The finding that the quality rating behavior of the individual participant does not fundamentally change over time may, e.g., assist in scheduling subjective tests under pandemic conditions where experimental campaigns may need to be stalled for an unknown period of time. © 2021 IEEE., open access

In this paper, we propose a viewing direction weighted bit plane least significant bit (LSB) data hiding method for 360° videos. Normalized Gaussian mixture models (GMMs) of the distributions of the relative viewing direction frequency for latitude, longitude, and both latitude and longitude are used to describe the human viewing behavior of 360° videos on head-mounted displays (HMDs). Apart from formulating data hiding weight functions to control the amount of secret data to be hidden at given latitudes and longitudes, the GMMs are used in this work also to define viewing direction weighted bit plane functions. These viewing direction weighted bit plane functions specify the number of bit planes to be used for data hiding depending on the latitude and longitude. As humans pay more attention to the central front view of 360° videos when watched on HMDs, the number of engaged bit planes is decreased accordingly from the poles to the equator, and from the west and the east to the front view. A performance assessment of the proposed viewing direction weighted bit plane LSB data hiding method is conducted, showing the trade-offs between capacity and objective perceptual video quality. The results indicate that it is preferable to first utilize a given bit plane for data hiding in an entire 360° video frame before engaging the next higher bit plane subject to the viewing direction weighted bit plane functions. © 2021 IEEE.

With the wide spread of digital document use in administrations, fabrication and use of forged documents have become a serious problem. This paper presents a study and classification of the most important works on image and document forgery detection. The classification is based on documents type, forgery type, detection method, validation dataset, evaluation metrics and obtained results. Most of existing forgery detection works are dealing with images and few of them analyze administrative documents and go deeper to analyze their contents. © 2021 IEEE., open access

This paper describes work in progress of an interdisciplinary research project that focuses on the placement and analysis of public close-circuit television (CCTV) cameras using data-driven analysis of crime data. A novel web-based prototype that acts as a framework for the camera placement analysis with regards to historical crime occurrence is presented. The web-based prototype enables various analyses involving public CCTV cameras e.g., to determine suitable locations for both stationary CCTV cameras as well as temporary cameras that are moved around after a few months to address crime seasonality. The framework also opens up for other analyses, e.g. automatically highlighting crimes that are carried out closed by at least one camera. The research also investigates to what extent it is possible to generate estimates on the amount of detail captured by a camera given the distance to the crime light conditions. The research project includes interdisciplinary competences from various areas such as criminology, computer and data science as well as the Swedish Police. © 2021 IEEE.

In this paper, we propose a viewing direction weighted bit plane least significant bit (LSB) data hiding method for 360° videos. Normalized Gaussian mixture models (GMMs) of the distributions of the relative viewing direction frequency for latitude, longitude, and both latitude and longitude are used to describe the human viewing behavior of 360° videos on head-mounted displays (HMDs). Apart from formulating data hiding weight functions to control the amount of secret data to be hidden at given latitudes and longitudes, the GMMs are used in this work also to define viewing direction weighted bit plane functions. These viewing direction weighted bit plane functions specify the number of bit planes to be used for data hiding depending on the latitude and longitude. As humans pay more attention to the central front view of 360° videos when watched on HMDs, the number of engaged bit planes is decreased accordingly from the poles to the equator, and from the west and the east to the front view. A performance assessment of the proposed viewing direction weighted bit plane LSB data hiding method is conducted, showing the trade-offs between capacity and objective perceptual video quality. The results indicate that it is preferable to first utilize a given bit plane for data hiding in an entire 360° video frame before engaging the next higher bit plane subject to the viewing direction weighted bit plane functions. © 2021 IEEE.

With the wide spread of digital document use in administrations, fabrication and use of forged documents have become a serious problem. This paper presents a study and classification of the most important works on image and document forgery detection. The classification is based on documents type, forgery type, detection method, validation dataset, evaluation metrics and obtained results. Most of existing forgery detection works are dealing with images and few of them analyze administrative documents and go deeper to analyze their contents. © 2021 IEEE., open access

The development of immersive media systems and services relies on subjective tests that provide ground truth on the quality of experience as perceived by humans. In this paper, we investigate the opinion score consistency through a repeated subjective 360° video quality assessment experiment. The test stimuli are presented on a head-mounted display with participants given the task to rate the video quality in three repeated sessions for both standing and seated viewing. The statistical analysis of the data from the subjective tests aims at revealing if participants change their rating behavior over time or keep their opinion scores given to the test stimuli in standing and seated viewing consistent in a statistical sense. The experimental results are reported in terms of histograms of opinion scores, skewness and kurtosis of opinion scores, mean opinion scores, standard deviation of opinion scores (SOS), SOS fitting functions, and analysis of variance tests. The statistical analysis supports the conjecture that each participant has its own but consistent rating behavior throughout the respective sessions for standing and seated viewing. The finding that the quality rating behavior of the individual participant does not fundamentally change over time may, e.g., assist in scheduling subjective tests under pandemic conditions where experimental campaigns may need to be stalled for an unknown period of time. © 2021 IEEE., open access

While the Internet of Things (IoT), Wireless Sensor Networks (WSNs), and the techniques for extracting digital data have seen continuous advancements, so does the cyber-Threat landscape. Virtual sensors which normally use abstraction layers that operate over a physical infrastructure to achieve their objectives, have seen rapid adoption, for example, it has aided in achieving manufacturing 4.0. This abstract layer has in the recent past seen tremendous proliferation within the sensor-based platform. Coupled with data pre-processing and key compliance with the guidelines for information security, incident investigation principles, and processes. This paper discusses a step towards a Learning-enabled (LE) Virtual Sensor Forensic (VSF) architecture that is compliant with edge intelligence technology, which is based on an initially proposed generic VSF architecture. Furthermore, apart from the learning capabilities, the LE-VSF architecture considers proactive and reactive investigation techniques by assuming an Internet of Vehicle (IoV) attack scenario, enhancing the reliability of a forensically sound data source. This proposition is essential in any sensor-based abstraction where the forensic analysis would otherwise be cumbersome and susceptible to noise. © 2021 IEEE.

In this paper, we propose a viewing direction weighted bit plane least significant bit (LSB) data hiding method for 360° videos. Normalized Gaussian mixture models (GMMs) of the distributions of the relative viewing direction frequency for latitude, longitude, and both latitude and longitude are used to describe the human viewing behavior of 360° videos on head-mounted displays (HMDs). Apart from formulating data hiding weight functions to control the amount of secret data to be hidden at given latitudes and longitudes, the GMMs are used in this work also to define viewing direction weighted bit plane functions. These viewing direction weighted bit plane functions specify the number of bit planes to be used for data hiding depending on the latitude and longitude. As humans pay more attention to the central front view of 360° videos when watched on HMDs, the number of engaged bit planes is decreased accordingly from the poles to the equator, and from the west and the east to the front view. A performance assessment of the proposed viewing direction weighted bit plane LSB data hiding method is conducted, showing the trade-offs between capacity and objective perceptual video quality. The results indicate that it is preferable to first utilize a given bit plane for data hiding in an entire 360° video frame before engaging the next higher bit plane subject to the viewing direction weighted bit plane functions. © 2021 IEEE.

This paper describes work in progress of an interdisciplinary research project that focuses on the placement and analysis of public close-circuit television (CCTV) cameras using data-driven analysis of crime data. A novel web-based prototype that acts as a framework for the camera placement analysis with regards to historical crime occurrence is presented. The web-based prototype enables various analyses involving public CCTV cameras e.g., to determine suitable locations for both stationary CCTV cameras as well as temporary cameras that are moved around after a few months to address crime seasonality. The framework also opens up for other analyses, e.g. automatically highlighting crimes that are carried out closed by at least one camera. The research also investigates to what extent it is possible to generate estimates on the amount of detail captured by a camera given the distance to the crime light conditions. The research project includes interdisciplinary competences from various areas such as criminology, computer and data science as well as the Swedish Police. © 2021 IEEE.

The development of immersive media systems and services relies on subjective tests that provide ground truth on the quality of experience as perceived by humans. In this paper, we investigate the opinion score consistency through a repeated subjective 360° video quality assessment experiment. The test stimuli are presented on a head-mounted display with participants given the task to rate the video quality in three repeated sessions for both standing and seated viewing. The statistical analysis of the data from the subjective tests aims at revealing if participants change their rating behavior over time or keep their opinion scores given to the test stimuli in standing and seated viewing consistent in a statistical sense. The experimental results are reported in terms of histograms of opinion scores, skewness and kurtosis of opinion scores, mean opinion scores, standard deviation of opinion scores (SOS), SOS fitting functions, and analysis of variance tests. The statistical analysis supports the conjecture that each participant has its own but consistent rating behavior throughout the respective sessions for standing and seated viewing. The finding that the quality rating behavior of the individual participant does not fundamentally change over time may, e.g., assist in scheduling subjective tests under pandemic conditions where experimental campaigns may need to be stalled for an unknown period of time. © 2021 IEEE., open access

This paper describes work in progress of an interdisciplinary research project that focuses on the placement and analysis of public close-circuit television (CCTV) cameras using data-driven analysis of crime data. A novel web-based prototype that acts as a framework for the camera placement analysis with regards to historical crime occurrence is presented. The web-based prototype enables various analyses involving public CCTV cameras e.g., to determine suitable locations for both stationary CCTV cameras as well as temporary cameras that are moved around after a few months to address crime seasonality. The framework also opens up for other analyses, e.g. automatically highlighting crimes that are carried out closed by at least one camera. The research also investigates to what extent it is possible to generate estimates on the amount of detail captured by a camera given the distance to the crime light conditions. The research project includes interdisciplinary competences from various areas such as criminology, computer and data science as well as the Swedish Police. © 2021 IEEE.

With the wide spread of digital document use in administrations, fabrication and use of forged documents have become a serious problem. This paper presents a study and classification of the most important works on image and document forgery detection. The classification is based on documents type, forgery type, detection method, validation dataset, evaluation metrics and obtained results. Most of existing forgery detection works are dealing with images and few of them analyze administrative documents and go deeper to analyze their contents. © 2021 IEEE., open access

The development of immersive media systems and services relies on subjective tests that provide ground truth on the quality of experience as perceived by humans. In this paper, we investigate the opinion score consistency through a repeated subjective 360° video quality assessment experiment. The test stimuli are presented on a head-mounted display with participants given the task to rate the video quality in three repeated sessions for both standing and seated viewing. The statistical analysis of the data from the subjective tests aims at revealing if participants change their rating behavior over time or keep their opinion scores given to the test stimuli in standing and seated viewing consistent in a statistical sense. The experimental results are reported in terms of histograms of opinion scores, skewness and kurtosis of opinion scores, mean opinion scores, standard deviation of opinion scores (SOS), SOS fitting functions, and analysis of variance tests. The statistical analysis supports the conjecture that each participant has its own but consistent rating behavior throughout the respective sessions for standing and seated viewing. The finding that the quality rating behavior of the individual participant does not fundamentally change over time may, e.g., assist in scheduling subjective tests under pandemic conditions where experimental campaigns may need to be stalled for an unknown period of time. © 2021 IEEE., open access

With the wide spread of digital document use in administrations, fabrication and use of forged documents have become a serious problem. This paper presents a study and classification of the most important works on image and document forgery detection. The classification is based on documents type, forgery type, detection method, validation dataset, evaluation metrics and obtained results. Most of existing forgery detection works are dealing with images and few of them analyze administrative documents and go deeper to analyze their contents. © 2021 IEEE., open access

In this paper, we propose a viewing direction weighted bit plane least significant bit (LSB) data hiding method for 360° videos. Normalized Gaussian mixture models (GMMs) of the distributions of the relative viewing direction frequency for latitude, longitude, and both latitude and longitude are used to describe the human viewing behavior of 360° videos on head-mounted displays (HMDs). Apart from formulating data hiding weight functions to control the amount of secret data to be hidden at given latitudes and longitudes, the GMMs are used in this work also to define viewing direction weighted bit plane functions. These viewing direction weighted bit plane functions specify the number of bit planes to be used for data hiding depending on the latitude and longitude. As humans pay more attention to the central front view of 360° videos when watched on HMDs, the number of engaged bit planes is decreased accordingly from the poles to the equator, and from the west and the east to the front view. A performance assessment of the proposed viewing direction weighted bit plane LSB data hiding method is conducted, showing the trade-offs between capacity and objective perceptual video quality. The results indicate that it is preferable to first utilize a given bit plane for data hiding in an entire 360° video frame before engaging the next higher bit plane subject to the viewing direction weighted bit plane functions. © 2021 IEEE.

This paper describes work in progress of an interdisciplinary research project that focuses on the placement and analysis of public close-circuit television (CCTV) cameras using data-driven analysis of crime data. A novel web-based prototype that acts as a framework for the camera placement analysis with regards to historical crime occurrence is presented. The web-based prototype enables various analyses involving public CCTV cameras e.g., to determine suitable locations for both stationary CCTV cameras as well as temporary cameras that are moved around after a few months to address crime seasonality. The framework also opens up for other analyses, e.g. automatically highlighting crimes that are carried out closed by at least one camera. The research also investigates to what extent it is possible to generate estimates on the amount of detail captured by a camera given the distance to the crime light conditions. The research project includes interdisciplinary competences from various areas such as criminology, computer and data science as well as the Swedish Police. © 2021 IEEE.

Watching 360° videos on head-mounted displays (HMDs) has become more popular in recent years. As such, subjective quality assessment of 360° videos on HMDs is needed to obtain a ground truth on the quality as perceived by users. Due to the lack of standardized methods, the absolute category rating (ACR) with hidden reference (ACR-HR) method for conventional videos has also been used for subjective quality assessment of 360° videos on HMDs. A modified ACR (M-ACR) method tailored for assessing 360° videos on HMDs has recently been proposed. In this paper, we compare the ACR-HR and M-ACR with hidden reference (M-ACR-HR) method regarding subjective quality assessment of 360° videos on HMDs. The comparison is conducted subject to participants' experience with watching immersive media on HMDs. The findings include: 1) Average rating times to cast opinion scores is lower for the ACR-HR method irrespective of participants' experience, 2) Mean opinion scores are similar for both methods irrespective of participants' experience, 3) The M-ACR-HR method is more reliable, especially with experts and participants with no experience, 4) Discomfort is significantly lower for the ACR-HR method, especially, for participants with no experience. © 2020 IEEE., open access

In this paper, we propose a visual attention based least significant bit (LSB) data hiding method for 360° videos. In particular, information about the relative frequency of pixel access is used to control the amount of secret data to be hidden at the different latitudes of 360° videos. In this way, the typical behavior of users paying more attention to the equator region compared to the north and south poles when viewing 360° videos on a head-mounted display is taken into account. An analytical expression for capacity offered by this method to hide secret data in 360° cover videos is derived. A performance assessment of the visual attention based LSB data hiding method is conducted in terms of the peak signal-to-noise ratio (PSNR) and weighted-to-spherically-uniform PSNR (WS-PSNR) which both quantify the fidelity of a 360° stego-video with reference to the related 360° cover video. © 2020 IEEE., open access

Watching 360° videos on head-mounted displays (HMDs) has become more popular in recent years. As such, subjective quality assessment of 360° videos on HMDs is needed to obtain a ground truth on the quality as perceived by users. Due to the lack of standardized methods, the absolute category rating (ACR) with hidden reference (ACR-HR) method for conventional videos has also been used for subjective quality assessment of 360° videos on HMDs. A modified ACR (M-ACR) method tailored for assessing 360° videos on HMDs has recently been proposed. In this paper, we compare the ACR-HR and M-ACR with hidden reference (M-ACR-HR) method regarding subjective quality assessment of 360° videos on HMDs. The comparison is conducted subject to participants' experience with watching immersive media on HMDs. The findings include: 1) Average rating times to cast opinion scores is lower for the ACR-HR method irrespective of participants' experience, 2) Mean opinion scores are similar for both methods irrespective of participants' experience, 3) The M-ACR-HR method is more reliable, especially with experts and participants with no experience, 4) Discomfort is significantly lower for the ACR-HR method, especially, for participants with no experience. © 2020 IEEE., open access

In this paper, we propose a visual attention based least significant bit (LSB) data hiding method for 360° videos. In particular, information about the relative frequency of pixel access is used to control the amount of secret data to be hidden at the different latitudes of 360° videos. In this way, the typical behavior of users paying more attention to the equator region compared to the north and south poles when viewing 360° videos on a head-mounted display is taken into account. An analytical expression for capacity offered by this method to hide secret data in 360° cover videos is derived. A performance assessment of the visual attention based LSB data hiding method is conducted in terms of the peak signal-to-noise ratio (PSNR) and weighted-to-spherically-uniform PSNR (WS-PSNR) which both quantify the fidelity of a 360° stego-video with reference to the related 360° cover video. © 2020 IEEE., open access

Watching 360° videos on head-mounted displays (HMDs) has become more popular in recent years. As such, subjective quality assessment of 360° videos on HMDs is needed to obtain a ground truth on the quality as perceived by users. Due to the lack of standardized methods, the absolute category rating (ACR) with hidden reference (ACR-HR) method for conventional videos has also been used for subjective quality assessment of 360° videos on HMDs. A modified ACR (M-ACR) method tailored for assessing 360° videos on HMDs has recently been proposed. In this paper, we compare the ACR-HR and M-ACR with hidden reference (M-ACR-HR) method regarding subjective quality assessment of 360° videos on HMDs. The comparison is conducted subject to participants' experience with watching immersive media on HMDs. The findings include: 1) Average rating times to cast opinion scores is lower for the ACR-HR method irrespective of participants' experience, 2) Mean opinion scores are similar for both methods irrespective of participants' experience, 3) The M-ACR-HR method is more reliable, especially with experts and participants with no experience, 4) Discomfort is significantly lower for the ACR-HR method, especially, for participants with no experience. © 2020 IEEE., open access

In this paper, we propose a visual attention based least significant bit (LSB) data hiding method for 360° videos. In particular, information about the relative frequency of pixel access is used to control the amount of secret data to be hidden at the different latitudes of 360° videos. In this way, the typical behavior of users paying more attention to the equator region compared to the north and south poles when viewing 360° videos on a head-mounted display is taken into account. An analytical expression for capacity offered by this method to hide secret data in 360° cover videos is derived. A performance assessment of the visual attention based LSB data hiding method is conducted in terms of the peak signal-to-noise ratio (PSNR) and weighted-to-spherically-uniform PSNR (WS-PSNR) which both quantify the fidelity of a 360° stego-video with reference to the related 360° cover video. © 2020 IEEE., open access

In this paper, we propose a visual attention based least significant bit (LSB) data hiding method for 360° videos. In particular, information about the relative frequency of pixel access is used to control the amount of secret data to be hidden at the different latitudes of 360° videos. In this way, the typical behavior of users paying more attention to the equator region compared to the north and south poles when viewing 360° videos on a head-mounted display is taken into account. An analytical expression for capacity offered by this method to hide secret data in 360° cover videos is derived. A performance assessment of the visual attention based LSB data hiding method is conducted in terms of the peak signal-to-noise ratio (PSNR) and weighted-to-spherically-uniform PSNR (WS-PSNR) which both quantify the fidelity of a 360° stego-video with reference to the related 360° cover video. © 2020 IEEE., open access

Watching 360° videos on head-mounted displays (HMDs) has become more popular in recent years. As such, subjective quality assessment of 360° videos on HMDs is needed to obtain a ground truth on the quality as perceived by users. Due to the lack of standardized methods, the absolute category rating (ACR) with hidden reference (ACR-HR) method for conventional videos has also been used for subjective quality assessment of 360° videos on HMDs. A modified ACR (M-ACR) method tailored for assessing 360° videos on HMDs has recently been proposed. In this paper, we compare the ACR-HR and M-ACR with hidden reference (M-ACR-HR) method regarding subjective quality assessment of 360° videos on HMDs. The comparison is conducted subject to participants' experience with watching immersive media on HMDs. The findings include: 1) Average rating times to cast opinion scores is lower for the ACR-HR method irrespective of participants' experience, 2) Mean opinion scores are similar for both methods irrespective of participants' experience, 3) The M-ACR-HR method is more reliable, especially with experts and participants with no experience, 4) Discomfort is significantly lower for the ACR-HR method, especially, for participants with no experience. © 2020 IEEE., open access

Watching 360° videos on head-mounted displays (HMDs) has become more popular in recent years. As such, subjective quality assessment of 360° videos on HMDs is needed to obtain a ground truth on the quality as perceived by users. Due to the lack of standardized methods, the absolute category rating (ACR) with hidden reference (ACR-HR) method for conventional videos has also been used for subjective quality assessment of 360° videos on HMDs. A modified ACR (M-ACR) method tailored for assessing 360° videos on HMDs has recently been proposed. In this paper, we compare the ACR-HR and M-ACR with hidden reference (M-ACR-HR) method regarding subjective quality assessment of 360° videos on HMDs. The comparison is conducted subject to participants' experience with watching immersive media on HMDs. The findings include: 1) Average rating times to cast opinion scores is lower for the ACR-HR method irrespective of participants' experience, 2) Mean opinion scores are similar for both methods irrespective of participants' experience, 3) The M-ACR-HR method is more reliable, especially with experts and participants with no experience, 4) Discomfort is significantly lower for the ACR-HR method, especially, for participants with no experience. © 2020 IEEE., open access

In this paper, we propose a visual attention based least significant bit (LSB) data hiding method for 360° videos. In particular, information about the relative frequency of pixel access is used to control the amount of secret data to be hidden at the different latitudes of 360° videos. In this way, the typical behavior of users paying more attention to the equator region compared to the north and south poles when viewing 360° videos on a head-mounted display is taken into account. An analytical expression for capacity offered by this method to hide secret data in 360° cover videos is derived. A performance assessment of the visual attention based LSB data hiding method is conducted in terms of the peak signal-to-noise ratio (PSNR) and weighted-to-spherically-uniform PSNR (WS-PSNR) which both quantify the fidelity of a 360° stego-video with reference to the related 360° cover video. © 2020 IEEE., open access

In this paper, we propose a visual attention based least significant bit (LSB) data hiding method for 360° videos. In particular, information about the relative frequency of pixel access is used to control the amount of secret data to be hidden at the different latitudes of 360° videos. In this way, the typical behavior of users paying more attention to the equator region compared to the north and south poles when viewing 360° videos on a head-mounted display is taken into account. An analytical expression for capacity offered by this method to hide secret data in 360° cover videos is derived. A performance assessment of the visual attention based LSB data hiding method is conducted in terms of the peak signal-to-noise ratio (PSNR) and weighted-to-spherically-uniform PSNR (WS-PSNR) which both quantify the fidelity of a 360° stego-video with reference to the related 360° cover video. © 2020 IEEE., open access

Watching 360° videos on head-mounted displays (HMDs) has become more popular in recent years. As such, subjective quality assessment of 360° videos on HMDs is needed to obtain a ground truth on the quality as perceived by users. Due to the lack of standardized methods, the absolute category rating (ACR) with hidden reference (ACR-HR) method for conventional videos has also been used for subjective quality assessment of 360° videos on HMDs. A modified ACR (M-ACR) method tailored for assessing 360° videos on HMDs has recently been proposed. In this paper, we compare the ACR-HR and M-ACR with hidden reference (M-ACR-HR) method regarding subjective quality assessment of 360° videos on HMDs. The comparison is conducted subject to participants' experience with watching immersive media on HMDs. The findings include: 1) Average rating times to cast opinion scores is lower for the ACR-HR method irrespective of participants' experience, 2) Mean opinion scores are similar for both methods irrespective of participants' experience, 3) The M-ACR-HR method is more reliable, especially with experts and participants with no experience, 4) Discomfort is significantly lower for the ACR-HR method, especially, for participants with no experience. © 2020 IEEE., open access

In this paper, we are going to verify the possibility to create a ransomware simulation that will use an arbitrary combination of known tactics and techniques to bypass an anti-malware defense. To verify this hypothesis, we conducted an experiment in which an agent was trained with the help of reinforcement learning to run the ransomware simulator in a way that can bypass anti-ransomware solution and encrypt the target files. The novelty of the proposed method lies in applying reinforcement learning to anti-ransomware testing that may help to identify weaknesses in the anti-ransomware defense and fix them before a real attack happens. © 2020 IEEE., open access

In this paper, forecasting sales model for truck components using machine learning algorithms is proposed. The forecasting model helps companions (i.e. Volvo Trucks) in the activity of trade and business. It also plays a major role for firms in decision-making operations in the areas corresponding to sales, production, purchasing, finance, and accounting. In order to achieve good forecasting sales mode, firstly, a normalization approach is performed on the time-series data to reduce and eliminate the data redundancy. After that, feature extraction and selection techniques are employed on the normalized data. Finally, different machine learning methods such as Support Vector Machine Regression, Ridge Regression, Gradient Boosting Regression and Random Forest Regression have been applied to the features of the normalized time-series data. Results depict that ridge regression method gives the most promising forecasting sale results of truck components compared to the other machine learning methods. © 2020 IEEE., open access

In this paper, we are going to verify the possibility to create a ransomware simulation that will use an arbitrary combination of known tactics and techniques to bypass an anti-malware defense. To verify this hypothesis, we conducted an experiment in which an agent was trained with the help of reinforcement learning to run the ransomware simulator in a way that can bypass anti-ransomware solution and encrypt the target files. The novelty of the proposed method lies in applying reinforcement learning to anti-ransomware testing that may help to identify weaknesses in the anti-ransomware defense and fix them before a real attack happens. © 2020 IEEE., open access

In this paper, forecasting sales model for truck components using machine learning algorithms is proposed. The forecasting model helps companions (i.e. Volvo Trucks) in the activity of trade and business. It also plays a major role for firms in decision-making operations in the areas corresponding to sales, production, purchasing, finance, and accounting. In order to achieve good forecasting sales mode, firstly, a normalization approach is performed on the time-series data to reduce and eliminate the data redundancy. After that, feature extraction and selection techniques are employed on the normalized data. Finally, different machine learning methods such as Support Vector Machine Regression, Ridge Regression, Gradient Boosting Regression and Random Forest Regression have been applied to the features of the normalized time-series data. Results depict that ridge regression method gives the most promising forecasting sale results of truck components compared to the other machine learning methods. © 2020 IEEE., open access

In this paper, we are going to verify the possibility to create a ransomware simulation that will use an arbitrary combination of known tactics and techniques to bypass an anti-malware defense. To verify this hypothesis, we conducted an experiment in which an agent was trained with the help of reinforcement learning to run the ransomware simulator in a way that can bypass anti-ransomware solution and encrypt the target files. The novelty of the proposed method lies in applying reinforcement learning to anti-ransomware testing that may help to identify weaknesses in the anti-ransomware defense and fix them before a real attack happens. © 2020 IEEE., open access