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Sec 320

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Perimeter Security Applications
Robinson Paulino
DeVry College of New York
Sec- 330
Professor: Gerard Beatty

Perimeter Security Applications
Outline
Introduction 2 Intruder Detection Accuracy 3 Security Cameras 4 1. Using Size Filters for Video Analytics Accuracy 4 2. Geo-Registration and Perimeter Security Detection Accuracy 5 3. Clarity against a moving background 5 Perimeter Security Best Practices 6 Auto Tracking PTZ Camera 6 Long Range Thermal Camera 6 Covering Perimeter Camera Blind Spots 7 Determine a Perimeter Camera’s Range 7 Perimeter Fence . 8 Chain-Link Fences Protection 8 Electric and Infrared Fences 8 Fiber Optic Intrusion Detection Systems 9 In-Ground Intrusion Detection Systems 10 References 11

Perimeter Security Applications
Introduction
Physical security is the protection offered for property, these may be buildings or any other form of asset, against intruders (Arata, 2006). . The idea therefore, is to keep off unwanted persons or objects from ones premises. One’s premise is defined by a boundary which separates private property from the rest of the land. This boundary is referred to as the perimeter.
The perimeter could be physical or logical. Physical security is intended to keep intruders from land and grounds around such property. Logical perimeters on the other hand, are for protection against computer sabotage or any other remote malicious activities (Fennelly, 2012). In a nutshell, perimeter security is being precautious against any form of harm that may be intended against property or even people on that property. If the adversary could be noticed before any harm is done, it would be certainly better. Therefore, in addition to the physical security it is wise to have an intrusion detection system.
Intruder Detection Accuracy Intrusion detection is a process that involves monitoring of the events taking place around and within the boundaries of the property. These events are monitored in search of signs of possible incidents which fall under what is a security violation or possible violation of security. Intrusion prevention is the process of performing intrusion detection and attempting to stop detected possible incidents. Intrusion detection and prevention systems (IDPS) are primarily focused on identifying possible incidents, logging information about them, attempting to stop them, and reporting them to security administrators. In addition, individuals and organizations use intrusion detection and prevention systems for other purposes, such as identifying problems with security policies, documenting existing threats, and deterring individuals from violating security policies. While defining what intrusion detection systems are, it would make sense to describe what they are not and what they cannot do. Intruder detector systems do not prevent any form of intrusion. They do not prevent any kind of destruction caused by the intruder. They do not prevent malicious entry and destruction of systems put in place either.
Their main function is to detect an intruder just as the name clearly states. Their function is to detect an intrusion once and when it happens. In essence, they are analogous to a burglar alarm in a house. Such an alarm can trigger an immediate response e.g. call the police; can be used to alert the owner that unauthorized behavior is taking place.
It is therefore, of immense importance to ensure that the information collected is accurate and will not send security agents on a wild goose chase. In reference to perimeter security and intrusion detection, security devices like cameras, in ground intrusion detection systems and electric and infrared fences are used to a large extent.

Security Cameras
Accuracy in intrusion detection could be ascertained through:
1. Using Size Filters for Video Analytics Accuracy
Perimeter cameras that use video analytics are designed to detect movement. However, there is a lot of movements outdoors. There are birds flying around, small crawling animals, and trees swinging in the wind or even papers whirling in the wind. This could cause a lot of security alerts happening every so often causing nuisance and little or no trust in the system. The key to accurate detection, outside in the open, is to figure out the precise location of the moving object and then determine its size. This is done using cameras that are set to map their field of view to the GPS coordinates of all points in the scene (Philpott & Einstein, 2006).
. Such GPS Analytics are used to set accurate size filters and get rid of movement that has no representation of a security concern – like birds or flying papers – while ensuring that all human-sized motions are detected .Accurate size filters are above all important over extensive areas usual of site perimeters, where small objects near the camera look way larger than a human moving far off in the distance.
2. Geo-Registration and Perimeter Security Detection Accuracy
Geo-registration provides a number of additional benefits. These include the ability to automatically steer cameras to an intruder’s precise location, and to display the detected targets onto a sitemap of the premises so that the intruder is followed in real time. Geo-registration also enables a three-dimensional capability for the smart cameras. They can determine the actual size of any moving object anywhere in the field of view. Accordingly, these cameras that are Geo-registered will detect man-sized objects anywhere within their field of view, and ignore any other movements close or away from the camera.
3. Clarity against a moving background
Video analytic cameras placed outside have to identify security violations against the moving backdrop. The cameras must ignore any movement or reflection. This will ensure that they capture important images like a human being passing by. Failure to do so, the alerts made by the system will be nuisance and a failure to respond to the system as time goes. Filtering such movement is best accomplished with on-board processing and video memory buffers for making the right determination. This is no easy task, given that the cameras capture a lot of data in real life time. A camera with a large memory is required so that it has enough space to capture real time events and past events (Philpott & Einstein, 2006). This would help to make out what movements warrant an alarm and which are to be ignored. Without sufficient on-board processing and video analysis memory to filter non-important motion, such an environment would most likely be overwhelmed with nuisance alerts.
Perimeter Security Best Practices
Outlined here under are some of the perimeter security best practices when using cameras for security detection.
Auto Tracking PTZ Camera
An automatic PTZ camera, unlike the ordinary PTZ camera, automatically zooms and tracks the intruder in real time. This kind of camera requires no manual steer. It makes it easy for use on large perimeters. It is fitted with a thermal sight sensor that is used to locate the intruder while still in watch over the perimeter, and zooming in the intruder in real life.
Long Range Thermal Camera A long range thermal camera with video analytics offer significant economic advantages for perimeter security application covering large outdoor areas. To leverage extended range products effectively, it is vital to consider a number of best practices of product selection and deployment. With the right approach, the resulting cost savings now make accurate thermal analytic cameras affordable for mainstream perimeter applications. Great camera range brings in the possibility of less expensive mounting options. With a long range, the camera could be placed in a far distance and yet capture the whole scenery (Philpott, & Einstein, 2006).
In addition, waterside applications pose even larger obstacles for mounting cameras because one cannot put poles in the middle of an active waterway. In such cases, such as protecting ports or dams, longer-range cameras allow for achievement of security objectives in a practical, less costly manner.
Smart perimeter cameras are designed to detect movement, but outdoors everything moves. There are birds flying around, small crawling animals, and trees swinging in the wind or even papers whirling in the wind. This could cause a lot of false alarms. False alarms are a nuisance. This translates to little or no trust in the system. The key to accurate detection out in the open is to figure out the precise location of the moving object and its size determined.
When using longer-range cameras, it is important to know the actual size of all objects in the camera’s field of view, which can be achieved through GPS analytics. By knowing the precise location of the target, one can accurately measure the size of the target. Appropriate size filters are then applied to eliminate movement that does not represent a security concern, while still detecting security intrusions under all conditions (Philpott & Einstein, 2006).
Covering Perimeter Camera Blind Spots
Perimeter blind spots are areas within the perimeter that are not covered by the long sight of the cameras. To ensure that there are no blind spots in a perimeter, the cameras must be set in a way as to overlap each other’s area of coverage. This ensures that no space is left in the dark. This is a zero blind spot strategy. A site survey can be used select the camera with the right lens and to help place the cameras in position as to avoid blind spots. (Philpott & Einstein, 2006).
Determine a Perimeter Camera’s Range
A perimeter security system based on video analytics operates by “seeing” targets that move into a camera’s detection area. It so happens that the detection range of a camera more often than not, does not match the specifics published by the manufacturer. Therefore, it is the task of the integrator to find out the camera’s range and then design a dependable system that would have no blind spots. It is also essential that the distance by which a camera can automatically detect a person walking directly towards it is discovered.
Perimeter Fence A perimeter fence is a structure that goes around the perimeter of premises to prevent access or intrusion (Fennelly, 2012). These fences are of different kinds, specific to what they are made of.
Chain-Link Fences Protection
Chain-link fences are the most common perimeter fences as they are easy to construct, not expensive and durable while serving the purpose of keeping people in or out of a given area. Chain-link fences can be used for animal pens or even caging ball courts to avoid interfering with passerby. The chain link varies in size, making it easy to serve different purposes. A chain link fence could be made obstructive to climbing intruders by adding barbed wire on it.

Electric and Infrared Fences
An electric fence is a powerful intruder deterrent, which can be attached to an existing perimeter fence or used as a stand-alone fence. The obvious physical presence of the fence and bright yellow warning signs are visually off-putting to any potential intruder and present a potent front-line deterrent. Any attempt to cut or climb the fence is met by a non-lethal but very unpleasant shock and attempts to short circuit, reduce the voltage or breach the fence in any way generates an immediate alarm.
Fiber Optic Intrusion Detection Systems
The intrusion detection system used in this work is based on the Microstrain Locator Technology as applied to fence perimeter applications. The Microstrain Locator is based on the use of a bidirectional Mach Zehnder (MZ) as a distributed sensor to detect and locate an intrusion anywhere along its sensing arms. The deployed sensing system consists of an industrial computer which houses a highly coherent 1550nm laser source. This laser injects continuous wave counter-propagating light into the MZ. Two detectors with associated electronics, also housed in the sensing controller, receive the clockwise and counter-clockwise signals from the MZ to analyze the signals. The sensing controller also includes polarization controllers to maximize the MZ’s fringe visibility and optimize the location accuracy by actively compensating for changes in fiber birefringence (Bucaro et al., 1977).
Detection of an event is based on analyzing the interferometric signals, while an event’s location along the sensing length is resolved by measuring the time difference between received counter propagating signals. Additionally, using the event signals detected by both detectors it is possible to apply the appropriate signal processing techniques to classify the signals and perform both signal identification and signal discrimination.
A novel adaptive level crossings algorithm has been described to achieve nuisance alarm suppression and simultaneous signal recognition and event discrimination in a fiber optic intrusion detection system (Giallorenzi, 1985).
By measuring and analyzing the level crossings (LC) of a number of different intrusion and nuisance event signals obtained from a number of installed Locator systems in the field, it has been shown that the LC algorithm can form the basis of both event signal recognition and discrimination techniques for reducing nuisance alarm rates, as well as detecting intrusion events during torrential rain periods on fence-mounted fiber optic intrusion detection systems without compromising sensitivity.
In-Ground Intrusion Detection Systems
Optical fiber sensors are now used in a large variety of diverse applications, from static and dynamic strain sensing, to chemical and biological sensing (Giallorenzi, 1985). It is well recognized that optical fibre sensors have many desirable attributes which are advantageous with respect to other sensing methodologies. These advantages include greater sensitivity, reduced size and weight, and immunity to electromagnetic interference (Giallorenzi, 1985).
The use of optical fibre systems is increasing in some security applications however, for both transmission of information as well as for sensing applications, since these systems are immune to electromagnetic interference, and offer faster data transmission rates (Bucaro et al., 1977).
With an in-ground intrusion detection system, one can detect and locate intrusions on large perimeters and borders. The fiber optic cable is buried in gravel, detecting and locating any intrusion to within a hundred yards regardless of the perimeter length. It prevents nuisance alarms, while maintaining maximum sensitivity to legitimate intrusion events.
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References
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Arata, M. J. (2006). Perimeter Security. Maidenhead: McGraw-Hill.
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Fennelly, L. J. (2012). Effective Physical Security (4th ed.). Boston, Mass: Butterworth-Heinemann.
Giallorenzi T. G. (1985) Optical Fiber Sensor Technology. in Proc. IEEE 1985 International Electron Devices Meeting 31, p. 116.
Philpott, D., & Einstein, S. (2006). The Integrated Physical Security Handbook. Arlington, Va.: Homeland Defense Journal. Bucaro J. A., Dardy H. D., Carome E. F. (1977). Optical Fibre Acoustic Sensor. Applied Optics 16 (7), 1761-1762.
Philpott, D., & Einstein, S. (2006). The Integrated Physical Security Handbook. Arlington, Va.: Homeland Defense Journal.
Tyska, L. A., & Fennelly, L. J. (2000).Physical Security: 150 Things You Should Know. Boston: Butterworth-Heinemann.
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