Search Results (4)

Video Surveillance Systems (VSSs) are integral parts of road tunnels. Currently, they perform a number of functions, such as ensuring the protection of tunnel technologies, monitoring tunnel operation, or recognising license plates. If VSSs are to be designed to protect the tunnel and its technologies from unauthorised intentional human activity, it is necessary to ensure that they are designed in such a way as to meet the essential functionality requirement of the physical protection system (PPS). In this case, the VSS, as one of the alarm systems, should perform the function of early intrusion detection. The verification of the functionality of the PPS is possible using a software tool to model and simulate various intrusion scenarios. This article provides an example of the use of the SATANO software evaluation tool. The VSS enables multiple applications, such as monitoring, detection, knowledge, and identification. In this paper, the defined current standardised requirements for the design of VSSs in tunnels are considered from the point of view of their possible use for intelligent video analysis, enabling the recognition of various risk situations (e.g., faults or accidents of vehicles). Using the software tool, IP Video Design Tool, the requirements for the design of cameras in tunnels are assessed and adapted from the perspective of the use of intelligent video analysis. In the event that there is a requirement to use the VSS during emergency situations (e.g., fire), it is necessary to assess the operating conditions and period of time through which the VSS would operate in a given tunnel. This article presents the results of the simulation of the spread of a fire in a tunnel and its impact on the operation of the VSS. Full article

Video surveillance systems are widely deployed with large systems for use in strategic places such as home security, public transportation, banks, ATM centers, city centers, airports, and public roads, and play a vital role in protecting critical infrastructures. As various attacks are possible in these systems, identifying attacks and considering suitable security measures are essential. In this paper, we present a detailed review of existing and possible threats in video surveillance, CCTV, and IP-camera systems. This provides insight for the better identification of the security risks associated with the design and deployment of these systems and promotes further research in this emerging field. We also present countermeasures to prevent and protect the surveillance systems from various security attacks. Full article

Closed-circuit television (CCTV) and video surveillance systems (VSSs) are becoming increasingly more common each year to help prevent incidents/accidents and ensure the security of public places and facilities. The increased presence of VSS is also increasing the number of per capita exposures to CCTV cameras. To help protect the privacy of the exposed objects, attention is being drawn to technologies that utilize intelligent video surveillance systems (IVSSs). IVSSs execute a wide range of surveillance duties—from simple identification of objects in the recorded video data, to understanding and identifying the behavioral patterns of objects and the situations at the incident/accident scenes, as well as the processing of video information to protect the privacy of the recorded objects against leakage. Besides, the recorded privacy information is encrypted and recorded using blockchain technology to prevent forgery of the image. The technology herein proposed (the “proposed mechanism”) is implemented to a VSS, where the mechanism converts the original visual information recorded on a VSS into a similarly constructed image information, so that the original information can be protected against leakage. The face area extracted from the image information is recorded in a separate database, allowing the creation of a restored image that is in perfect symmetry with the original image for images with virtualized face areas. Specifically, the main section of this study proposes an image modification mechanism that inserts a virtual face image that closely matches a predetermined similarity and uses a blockchain as the storage area. Full article

Video surveillance systems (VSS), used as a measure of security strengthening as well as investigation, are provided principally in heavily crowded public places. They record images of moving objects and transmit them to the control center. Typically, the recorded images are stored after being encrypted, or masked using visual obfuscations on a concerned image(s) in the identification-enabling data contained in the visual information. The stored footage is recovered to its original state by authorized users. However, the recovery entails the restoration of all information in the visual data, possibly infiltrating the privacy of the object(s) other than the one(s) whose images are requested. In particular, Artificial Intelligence Healthcare that checks the health status of an object through images has the same problem and must protect the patient’s identification information. This study proposes a masking mechanism wherein the infiltration of visual data privacy on videos is minimized by limiting the objects whose images are recovered with differential use of access permission granted to the requesting users. Full article