Category: White Paper

Integrating Comprehensive Security Courses for Future Managers Dr. Rajiv MathurVice Chairman, Training & Faculties – ICISSMRegional Advisor, Asia, OSPAs Introduction In the current business environment, security has become an integral aspect of operations, encompassing physical, cyber, and logical dimensions. From the industrial revolution to the Industry 4.0 era and the challenges posed by the pandemic, security discussions rightfully take center stage in boardrooms. Recognizing its paramount importance, academic institutions are adjusting their courses, making security a must-learn subject. This shift highlights a growing need for managers who truly understand security functions. Security – A Total Management Function Security, recognized as a comprehensive management function, involves both active and passive measures to protect the environment, allowing activities to proceed without disruption. It includes managing risks, preventing losses, protecting resources, and ensuring safety. This not only provides a sense of comfort and confidence but acts as a barrier against threats that could harm communities, businesses, or individuals. Managers in all kinds of businesses are expected to know various techniques to improve profitability by controlling costs. However, one often overlooked but significant way to keep costs down is by ensuring that all purchased materials are used efficiently in production, finished goods are sold for profit, and a company’s assets remain its own. This crucial management skill, referred to as ‘Security,’ is unfortunately one of the most neglected yet vital aspects of modern management. Security plays a key role in maximizing business efficiency and profitability. Managers hold the key to making security contribute effectively to a company’s profits by ensuring optimal resource use. Without this assurance, claiming to run an efficient business remains a challenge. The Evolving Role of Security in Business Security has transitioned from a peripheral concern to a central and indispensable function within organizations. The Manager Security now plays a pivotal role in collaborating with department managers to determine security needs, planning and implementing comprehensive security strategies, controlling budgets, and supervising security personnel. In the contemporary business landscape, where threats are multifaceted, managers need to possess a nuanced understanding of security to safeguard the interests of the organization. The Intersection of Management and Security As organizations recognize the intricate relationship between effective management and robust security, management institutes are increasingly incorporating security-related subjects into their curriculum. The Manager Security is not merely a guardian; they are integral to overall management and functioning. MNCs and large industries seek managers who are not only wellversed in traditional management practices but also possess a deep knowledge of security functions, making security education a crucial aspect of managerial preparation. The Manager Security’s Responsibilities A Manager Security’s responsibilities extend across various domains, including collaborating with department managers, developing security strategies, budget control, personnel management, intelligence gathering, emergency response coordination, and ensuring compliance with industry regulations. The complexity of these responsibilities underscores the need for specialized education to equip future managers with the skills necessary to navigate the evolving security landscape. “This crucial management skill, referred to as ‘Security,’ is unfortunately one of the most neglected yet vital aspects of modern management. Security plays a key role in maximizing business efficiency and profitability. Managers hold the key to making security contribute effectively to a company’s profits by ensuring optimal resource use. Without this assurance, claiming to run an efficient business remains a challenge”

Samir Nayak Sr. Sales Director & Country Manager, Everbridge Leading organizations are accelerating their digital transformation to cope with the multitude of disruptions that the pandemic and other critical events are creating. The COVID-19 pandemic is also shining a light on organizations that are succeeding in this environment, having strong business models in conjunction with strengths in adaptability and resilience. As security executives are navigating their organization’s road to recovery and considering a post-pandemic future, there are many lessons to be learned from how the world’s leading organizations are acclimatizing to operating with uncertainty. Not knowing when, or if, the COVID-19 pandemic will end means that changing your approach to security and adapting to better support your business operations is an ongoing endeavor. Many leading organizations are utilizing Everbridge Control Center for mission critical safety and security, and these customers offer valuable lessons for other organizations that are evaluating their security approach. In this white paper we are highlighting their top five security lessons learned that apply across all industries, navigating COVID-19, covering: Boardroom attention and security leadership. Agility, adaptability, and transformation. Automation to reduce risk and enhance compliance. Switch to remote working. Confidence in reopening facilities. 1. Boardroom Attention and Security Leadership The global pandemic is reshaping the business agenda. Many organizations are prioritizing safety and security above all other commercial decisions, forcing security executives into boardroom discussions where business executives are scrutinizing their security operations. Leaders at the forefront of the security industry are seizing their opportunity, by clearly setting out their longer-term investment requirements, rather than focusing on purely tactical initiatives. Ensuring safety and security are receiving the required level of ongoing investment allows their teams to stay ahead of emerging threats and critical events while comprehensively managing everyday organizational risks. They are requesting investment for sustained competitive advantage; articulating the commercial value of security to boardrooms and investing in technologies aimed at driving or enabling revenues and reducing costs over time. We see security executives achieving their objectives by also focusing on reducing risk and increasing operational compliance through digitization and automation. The larger the organization, the more important digitization and automation becomes for increasing behavioral consistency while reducing costs. Strong leadership skills demonstrating a proactive focus on protecting people and business operations have come more naturally to some security executives. Their training and experiences have given them the ability to operate calmly and effectively during life threatening crises. They have taken accountability for collaborating with business colleagues to ensure operational continuity while bolstering their duty of care. They are demonstrating their adaptability in uncertain environments and are at ease managing a growing number of risks. Leading organizations are proactively mitigating risks so that the organization can keep running. They are accelerating effective decision making, not making wrong decisions, having certainty when an incident or critical event is not taking place, and not escalating false incidents. This is where technology is contributing meaningfully, by enabling organizations to make the best-informed decisions through having the right information in the hands of the right people, at the right time. The lesson: Leading security executives are prepared and resilient. They act boldly, especially during uncertainty. They take a long-term view of strategy, yet they can adapt to a changing tactical environment.   2. Agility, Adaptability Innovation & Transformation During the pandemic we are seeing leading organizations adapt with agility in safeguarding people, facilities, and assets wherever they are located. These same organizations are transforming and preparing for growth. The most resilient are not only surviving they are looking to the future with optimism. These organizations may not be the ones you often read about when it comes to innovation and transformation, as they are too busy accomplishing their new plans. Supply chain issues, increasing insider threats, new cyber threats are not dulling leading organization’s ongoing responses. They are operating in a no fail environment and are mobilizing resources to address ambiguity and volatility. The overriding purpose of security innovation and transformation appears to be commercial and organizational success. Leading organizations are expecting their security to be: Commercially valuable, and more cost efficient.  Failsafe in protecting people, facilities, and assets with built-in mobility and digital/ physical convergence. Resilient and adaptable to be future proof. Responding faster through automation and data insights. The lesson: Leading organizations have commercially focused security executives that are using technology, as much as possible, to enable revenues, reduce costs and better protect assets. They are building for future growth. 3. Automation to Reduce Risk and Enhance Compliance While some organizations are advancing the use of artificial intelligence and machine learning, many more organizations are digitizing and automating standard operating procedures to provide comprehensive operational control and increase workforce productivity. We see customers digitizing and automating compliance, resulting in better: Management of (multiple) critical events. Safety and security. Protection of people, facilities, and assets. Operational resilience. Mitigation of business disruptions. Response, adaption, recovery, and learning from incidents Speed of response is one positive outcome of automation, directly affecting life safety or security. Using technology to automate alerts, decisions, actions, and reporting is clearly beneficial when the volume of information flooding into the organization is significant. Waiting for an operator to notice ‘something’ before acting is an avoidable risk. Without automation you are also relying on your operators to know your assets from memory (e.g., finding the nearest camera to where an incident is happening) or losing precious time through switching between applications and lookup lists. That is assuming that your operators are trained sufficiently that they remember the exact process your organization has prescribed for the exact situation, and that they can remember that process during a potential crisis moment. Beyond automation, our customers are using orchestration for dynamic workflows. They are not operating with data silos or fragmented operating pictures. Dynamic workflows defining how the system is going to react if ‘this and this happens’ or if ‘this and this but not that happens’ ensures that the system performs in the way the organization has…

Challenge The COVID-19 pandemic has changed our way of life, at both a professional and personal level. As new information emerges about businesses reopening and restrictions lifting to give way to a new definition of normalcy, there remains public and health safety guidelines to curb the spread. This challenge could not be more top of mind for organizations, both public and private, in how they open up their operations while keeping their employees and customers safe. It has been established that social distancing plays a pivotal role in limiting the spread of COVID-19. Organizations such as retail stores and business offices need a way to limit occupancy rates in their facilities at any given time in order to support effective social distancing measures. Solution Motorola Solutions is committed to innovating mission-critical technologies to protect people and communities. In the face of this global pandemic, Motorola Solutions is currently investigating different solutions, including looking at the analytics and software technology we have in the market that can be leveraged to help organizations effectively protect their employees and customers. Motorola Solutions’ Occupancy Counting feature in Avigilon Control Center (ACC) 7, the latest release of our video management software, can provide organizations an easy and streamlined way to count and identify the number of people in a facility. The feature aims to remove the staffing costs required to count people manually and the subsequent guess work on occupancy by frontline employees, particularly where facilities have multiple entry and exit points. Occupancy Counting helps organizations comply with social distancing guidelines by limiting the number of people in a facility, thereby reducing the interactions between them. Occupancy Counting leverages Avigilon’s analytic-enabled cameras that feature advanced object detection, including enhanced detection of people, which is particularly suitable for facility entrances or exits. To deploy the Occupancy Counting feature, Avigilon H5A or H4A cameras or third-party cameras connected to an Avigilon artificial intelligence appliance, can be specially placed at the entry and exit points of a facility or area to monitor traffic. AI-powered video analytics detect and classify a person crossing the entry or exit point and automatically translates these analytic events into entry and exit events. These events will be visible through dashboards in Avigilon Cloud Services (ACS) for managers to determine how many people are inside a facility, or alternatively, for automated screens to display at store fronts. Cloud-based reporting and visualizations provide helpful insights into hot spots and high traffic entry or exit points, allowing facilities to implement corrective measures to manage occupancy rates. For example, a retail store has been directed by its local government to reinforce social distancing measures by limiting the number of people in its store to 50% of its typical capacity. The retail store installs H5A cameras at its entrance to leverage the Occupancy Counting feature. As customers enter or exit the store, they are counted and compared to the occupancy threshold set in the ACS dashboard by store management. The front door display shows the current occupancy and when it is exceeded, displays a red screen that lets employees and customers know that they have to wait until people inside exit before they may enter. The ACS dashboard gives managers both a real-time and historical view of the occupancy of their facility and delivers further insights on typical peak times, the number of times per day customers must wait to enter, and finally, informs measures to optimize outdoor queuing support (e.g., sidewalk markers or crowd control barriers). The retail store is one out of many locations of a national chain. The security team of the retail chain has connected all of its stores that use ACC software to ACS, enabling them to use the Occupancy Counting feature across multiple stores from a central location, and determine if there are any trends that regional or national management should be aware of. In an office building setting, occupancy counting can display the number of people inside a facility based on strategically placed cameras installed at entry and exit points of the facility. The net total occupancy is displayed on a dashboard in ACS and can also be publicly displayed on a tablet placed at entry or exit points to manage traffic. Based on a set occupancy limit being reached or not, the tablet can be triggered to display instructions to permit entry or wait. The ACS dashboard can be used by management to provide insight on how many of their employees are returning to work in the office, allowing them to determine if additional guidelines like social distancing or face mask attire need to be reinforced. If occupancy limits are consistently exceeded, managers can also implement corrective measures such as requiring more employees to work from home. Organizations can pair the Occupancy Counting feature with Avigilon’s social distancing technology for a more powerful solution. Avigilon’s social distancing technology is powered by video analytics to automatically calculate the distance between individuals in the H5A cameras’ field of view. Managers can continuously monitor social distancing efforts within a facility, run reports of when social distancing violations occur and identify high traffic zones requiring additional attention or corrective action. As our world slowly reopens, it is imperative for organizations to follow public and health safety guidelines including social distancing and avoiding large gatherings. Innovative video security and AI-powered video analytics technology can deliver the intelligent capabilities that organizations need to protect people and create a new way of operating, especially when there is no timeline on when COVID-19 will recede as a global health crisis. In these uncertain times, a layered approach is the best strategy. Combining solutions for occupancy counting with technologies for social distancing, face mask detection and thermal screening efforts are essential for a depth in defense approach to limit the spread of COVID-19.  

In network video, copper cables (twisted-pair) have traditionally been used to connect the camera with the control center or the recording unit. In long-range surveillance installations, however, fiber-optic cabling can be a more cost-efficient alternative. Even though it is more expensive per meter, the superior transmission characteristics of a fiber-optic cable reduces the need for expensive signal amplifiers along the way, and makes it possible to transmit more data at a time. This white paper explains what fiber-optic communication is and how it can be used in network video. It also outlines how the Axis product line is designed to support fiber-optic communication. What is fiber-optic communication? In fiber-optic communication, light signals are transmitted through glass fibers. Light reflections within a strand of glass The fibers inside a fiber-optic cable are flexible, transparent strands of very pure glass or plastic. The core of a fiber is radially enclosed by another transparent material with slightly different characteristics, the cladding. This structure makes the fiber function as a ‘light pipe,’ so that light that enters the core at one end can emerge from the other end, even when the fiber is bent or twisted. For stability and protection, the core and cladding are normally enclosed by several protective coatings, as seen in Figure 1. Whenever the light inside the fiber hits the boundary between the core and the cladding, the light will bounce in a controlled manner and essentially continue forward, bouncing back and forth between the ‘walls’ (see Figure 2). It is as if the cladding was lined with mirrors. Hardly any light is absorbed by the cladding, which is why the fiber can carry the light across great distances with nearly preserved intensity. Single-mode and multi-mode fibers Fibers come in two types, suitable for different light sources and different transmission distances. Single-mode fibers have thin cores, about 8μm in diameter, and transmit infrared laser light (wavelength = 1,300 to 1,550nm). They are usually made of glass. Single-mode fibers support only one propagation path, or mode, and are used for communication links longer than 1km. They are typically used in10-/100Mbit/s network connections spread out over extended areas. Multi-mode fibers have a larger core diameter, typically 50-100μm, and transmit infrared LED (light emitting diode) light (wavelength = 850 to 1,300nm). They are usually made of plastic-clad silica or plastic. Multi-mode fibers support many propagation paths, or modes. They are used for short-distance communication links (up to 5km), and for applications where high power must be transmitted. Duplex and simplex transmission You can transmit either two signals (full duplex) or just one signal (simplex) through one fiber-optic strand. With duplex transmission, the transmitted signal and the received signal travel through the same strand. This means that in each fiber-optic strand there are two rays of light, traveling in opposite directions at the same time (see top part of Figure 4). In simplex transmission, there is only one ray of light traveling through each fiber strand. The received signal must then travel through a second strand (see lower part of Figure 4). Duplex transmission requires only half the number of fiber strands to transmit the same amount of data compared with simplex transmission.   Why use fiber-optic communication? The most common purposes of using fiber-optic connections are illumination, communication, and medical or industrial endoscopy where many fibers are bundled together to transmit an image. For telecommunications such as network video, the light traveling through the fiber is, of course, not just random light, but rather data streams encoded as light signals. Fiber-optic connections have been used for data transmission since the 1970s, but the techniques for both transmitting of the data and for manufacturing of the fiber-optic equipment have advanced drastically over the years. Long-range installations at low cost As we have seen, a fiber-optic cable can carry a signal across great distances with only very low attenuation. For a twisted-pair copper cable to be able to carry a signal across the same distance, the signal would have to be amplified at several instances along the way. This could be done using so-called repeaters, but these are rather costly. This is why fiber-optic cables can be a cost-efficient solution at long distances, even though they are more expensive per meter than copper cables. The maximum length of a fiber-optic cable ranges from 10km to 70km, depending on the type of fiber. The maximum length of a twisted-pair copper cable is 100m. Depending on the type of fiber-optic cables used, data rates can range up to 10,000Mbit/s. The cost-efficiency of fiber-optic installations is also due to the slenderness of the fibers. This means that more fibers can be bundled into a given-diameter cable. This allows more data to go over the same cable, and makes fiber-optic cables ideal for carrying digital information. No electrical interference Transmission through twisted-pair copper cables is susceptible to electromagnetic interference (EMI). This is when external electromagnetic fields affect the current in the cable, and may cause substantial problems with data loss. Fiber-optic cables, however, are immune to such interference. Also, the signal in one fiber does not interfere with those in other fibers in the same cable. Because the signal in a fiber-optic cable does not give rise to any electromagnetic field outside of the fiber, there is no signal leakage. This means that the transmission cannot be tapped, or accessed by unauthorized people. Fiber-optic communication in network video Axis offers a range of network video products that support fiber-optic communication. The key component in connecting a surveillance system with a fiber-optic cable is the SFP (small form factor pluggable) module. Other components are media converters and network cameras with integrated SFP slots. Overview of fiber-based network video system Figure 5 shows an example of a video surveillance system where a fiber-optic cable connects the sending side with the receiving side. Sending side   On the sending side of the system is a network camera (in this case AXIS Q3615-VE network camera) which provides video data to be transmitted. The…

While organizations look to incorporate video surveillance and access control systems that provide greater interoperability as part of their security strategy, the majority of security manufacturers have continued to provide disparate systems, with limited communication between systems. With the recent advancements in software technologies, and the ongoing partnerships between security manufacturers, integration has become a popular substitute for traditional interfacing. However, even integration has its limits. The answer can be found in a single software platform that can manage access control, intercom, intrusion, and video devices, while offering a unified interface to monitor the entire system. Such a system goes above and beyond the basic functionalities of interfacing and integration, while offering end-users an efficient, flexible and cost-effective option to system unification not available with highly customized and expensive solutions like PSIMs. Building Security Solutions That End Users Want Even today, with all the technologies available, the industry is struggling to fully succeed at building security solutions that fulfill the users’ true needs – a cohesive video and access control system that is efficient, non-proprietary, and cost effective. It is important to recognize that without these basic criteria, a unified video and access control system may not seem advantageous to customers and thus, not generate enough demand for manufacturers to justify developing such a product. Efficiency Gains Matter The priority of any security staff will be to spend time on performing their core tasks such as monitoring, investigating and responding to incidents to ensure the security of the organization. Their ability to perform these critical tasks should not be impeded by time spent managing technology. In other words, the security technologies they use should help them be more efficient and effective, while not slowing them down. In one of his articles, Rich Anderson, CTO of Razberi Technologies, and previously VP of Marketing for GE Security and VP of Enegineering for CASI-RUSCO, illustrates the common problem with today’s disparate systems with the following statement: “Access control systems in particular generate alarms for invalid badges, door-forced and door-held events. Those events need to be investigated, but the task of doing so with a standalone surveillance system is painful. Receive an alarm on one system, and your operator has to move to another completely different system to investigate. This surveillance system has a different user interface and so he/ she has to ‘switch gears.’ Then, which camera do you call up to view the scene? An experienced operator will know, but that ‘experience’ costs you a lot in terms of training.” Mixing and Matching Best-of Breed Technologies The PC industry has succeeded in building interoperable products. Anyone can buy a PC today, and down the line, add new hardware like a printer, web cam, gaming device, or even install a new hard drive that processes information twice as fast as the previous one. Almost anything can be done without changing the entire PC or operating system. However, the same cannot be said about, or achieved in the security industry. A user cannot simply decide to buy the latest high-tech wireless door controller and add it to an existing access control system. Or buy the latest and greatest IP cameras and connect them to a video management system (VMS) without first verifying that the specific model is supported. For these and many other reasons, the security industry is far behind the PC industry. In fact, it might never be possible to achieve what the PC industry has in terms of interoperability. Making a commitment to proprietary technology can be a costly decision. When a new technology emerges, the option to incorporate it becomes more of a question about whether or not to forego existing investments and start over from scratch with a new investment. On the other hand, having the ability to mix and match best-of-breed products from different manufacturers, and having the option to incorporate the latest advancements in technology into a security system ultimately provides more flexibility and the added assurance that your investment is future-proof. Managing Investments A solution that is entirely customized to fit with all existing business systems and infrastructure might be very efficient and attractive, but as with any customized approach it will likely be expensive as well. Take for example ERP systems (enterprise resource planning) deployed by many companies. An ERP system can be customized to adapt to virtually any business model and environment by specialized ERP system integrators. Although the cost of customizing such a system is very high, there is usually a significant productivity gain realized after deployment to justify this investment. In similar respects, investments in security departments and equipment are always considered an expense and it is unlikely that security systems could be adapted to every internal process. Since these systems rarely generate revenue, budgets are traditionally tightly controlled. Completely overhauling a system, regardless of the technology employed, is entirely dependent on budget availability and management’s buy-in. Often, even discussions of upgrading or replacing a system occur out of pure necessity (e.g., aging system or security flaw) and the process of sourcing and implementing a system could span months, if not, years. Therefore, it is crucial, more than any other factor, that the total cost of ownership of a cohesive video and access control system be justified. Integrated Systems With the recent advancements in technologies, and increased collaboration between manufacturers, integration has become a popular substitute for traditional interfacing.   In information technology, systems integration is the process of linking together different computing systems and software applications physically or functionally. Specifically in the security industry, the most popular integration methods involve network protocols and software development kits (SDK). Network protocols are very powerful as they support a mix of operating systems and allows you to manage your applications in real-time. However, integrating two systems through a network protocol requires more time than an SDK, or it may require a shared database between two systems. Network protocols are popular for edge-device integrations like IP cameras or door controllers but are even more commonly…

The primary objective for smart city initiatives is to intelligently use data and technology to make everyday life easier and better for the people who live in, work in and visit the city – while making innovative and efficient use of resources. Public safety plays an important role. This is why most smart city initiatives include video surveillance for key public areas, to achieve quicker alerting and better data to inform first responders regarding accidents, crimes and public safety situations. However, if smart city initiatives take traditional approaches for physical security technology, they will undermine their primary smart city objective. Over a decade of smart city initiatives has revealed what it takes for smart city technology deployments to achieve the sustainable quality of life transformations they intend, in the face of the challenges that smart city tech projects face. Recent successes have shown that cloud-based solutions are indispensable elements of smart city infrastructure, which includes both public and private infrastructure elements. Cloud-based deployments are essential for cost-effectiveness, scalability, and short deployment time frames. Furthermore, smart city security technology projects have new technical requirements – some of which can only be met using cloud technology. This paper examines those requirements and points to two very recent projects that exemplify the kinds of success that can be achieved. Smart Cities In June 2018, the McKinsey Global Institute released an in-depth independent research and analysis report titled, ‘Smart cities: Digital solutions for a more livable future.’ McKinsey’s research identified 60 data-driven smart city applications spanning the eight domains listed below. Eleven of these applications are physical security applications. Smart Applications Successful smart city security initiatives require more than just getting city planners and stakeholders, and their security integrators and consultants, on the ‘same page.’ They must all get on a ‘new page’ that includes: Expanded system design thinking. Up to date set of technology capabilities. Active stakeholder and citizen involvement. All are required for smart city deployment success. The Smart City Context The requirements for security technology deployments derive from the ways that smart city deployments differ from traditional security system deployments. The intelligence and operational capabilities of smart cities technology infrastructure resides in three layers identified by McKinsey analysis – technology base, applications interaction, and user base. This is the context for smart city security tech deployments. Technology Base Smart city security devices and systems are part of a larger city technology base connected by reliable high-speed communications networks. Achieving reliable high-speed internet access is always the first step in smart city development – unless it already exists. Applications Interact Applications are the tools by which a smart city turns raw data into alerts, insights and action – automating as much of the job as possible. Smart city security application design must consider that application data should not just facilitate public safety operations but must also contribute to the city’s greater understanding of itself. This is plain to see in Mexico City’s recent smart city security initiative. Public Usage The size of a smart city’s user base is the most significant difference from traditional security systems, which typically range from a few dozen to a few hundred users. Smart city citizen apps include personal security and safety features and have many thousands to millions of users. These mobile apps are the way smart cities enable citizens and visitors to interact with city services, including real-time services such as parking, public transportation, security and emergency services. This is an area where security technology and service providers can be innovative in providing value for citizen end-users as well as for city operations. Key Technology Requirements Smart city technology initiatives include 11 key requirements that have been traditional weak areas for physical security technology deployments: Intelligent connectivity. Simple scalability. Device and system interoperability. Open systems architecture. Systems integration interfaces. Privacy. Cybersecurity Data governance. Actionable data and analytics. Fault-tolerance. Future-readiness. The security industry has begun improving in some of these areas. However, physical security technology has typically lagged five to 10 years behind the state of information technology and related IT practices, and exponential technology advancement has made catching up an even greater challenge. Modern Technology is Required For large-scale smart city projects it’s not possible, for both technical and cost reasons, to adequately address most or all these 11 requirements with traditional on-premises devices and systems. However, well-engineered cloudbased systems with cloud-managed field devices make it both technically possible and financially feasible to fulfill smart city key requirements. These key requirements are well understood in the IT industry, but only recently has physical security technology advanced to the point where meeting all of them is feasible in smartcity security deployments. Intelligent Connectivity Smart city networks are, for the most part, very large shared networks – both wired and wireless. That means devices and applications that use significant bandwidth – such as security video – must not only use data stream reduction techniques such as compression and recording on motion and alarm, they must also be aware of LAN and internet bandwidth availability, and intelligently buffer transmissions as needed to throttle back their usage during times of peak overall network utilization. Develop a sound networking plan for any proposed project, verifying the infrastructure capabilities and documenting the planned intelligent use of existing network infrastructure and any new infrastructure to be added. Simple Scalability On-premises systems have fixed capacities for compute, memory, disk storage and networking. Well-engineered true cloud systems can scale those resources up or down on demand. NIST defines cloud computing as “a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (for example, networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.” A true cloud application – not just a client-server system hosted in the cloud – supports cloud-managed local devices and maximally automates their management. Automation includes performing system-wide firmware upgrades and digital certificate issuance. Well-designed cloud-based systems and tools can enable large-scale…

With great advances in video and access control technology – including mobile capabilities, cloud efficiencies, analytics and biometrics – security providers are aiming to create the most secure and seamless credentials, all during a time when privacy concerns seem to be dictating public opinion and impacting security. The increase in use of these technologies brings with it a growth in the volume of data. This article looks at the following areas of focus in privacy considerations: Definitions of privacy. Legalities of privacy and compliance (in the U.S.). Education on privacy. Definitions and ethical use of facial recognition. The biometric debate. Can we have both security and convenience? Definitions of privacy The description for privacy in Merriam-Webster’s dictionary is – “freedom from unauthorized intrusion.” From a legal point of view, privacy is defined as a person’s right to control access to his or her personal information. In today’s data-driven world, privacy issues are raised in the context of government collection or distribution of personal information, as well as corporate use of personally identifiable information (PII). PII is any data that could potentially be used to identify a particular person. Examples include a full name, social security number, driver’s license number, bank account number, passport number and email address. Photo or video data also comes into play, as well as biometric data. Legalities of privacy Milestone Systems is a global video management software company based out of Copenhagen, Denmark, that has had a focus since 2017 on the General Data Protection Regulations (GDPR) that went into force in Europe in May 2018. They define the individual’s critical privacy matters to be protected as ‘sensitive personal data’ such as your racial/ ethnic origin, genetic and biometric info, health and financial data, religious, political and sexual preferences. GDPR has a focus on these key principles: Lawfulness. Fairness and transparency. Legitimate purpose’ limitations on the gathering, use, sharing and storage of sensitive personal data, and its minimization. Milestone has investigated every facet of business from products to business practices, to ensure compliance and provide guidance to employees, partners and customers. In the U.S., three states led the way in 2019 enacting biometric privacy laws – Illinois, Texas and Washington. The California Consumer Privacy Act (CCPA) took effect in January 2020. Then multiple states proposed similar legislation to protect consumers. Arizona, Florida, and Massachusetts introduced legislation addressing biometric privacy, on the heels of a decision for the Illinois Biometric Information Privacy Act. The best way for security dealers, integrators and consultants to learn each state’s biometric laws and work within their parameters is to keep informed. To stay abreast of the changing state-privacy landscape, the IAPP Westin Research Center compiled a list of proposed comprehensive privacy bills from across the country. The updated version of this tool, including a new state law tracker map, exists on the IAPP Resource Center, here. It is advised to take a multi-path approach to stay informed from the many points of view: Join local chapters of SIA and ASIS to network with other professionals specific to your region. Partner with the manufacturers and developers of the technologies you are interested in; they will know how their solutions fit state and local legislation. Get involved with local law enforcement groups, attend relevant presentations on new local and state ordinances. Follow and support organizations like the IAPP which is the world’s largest and most comprehensive global information privacy community. Be vigilant for compliance Ensuring compliance with GDPR and similar data privacy laws requires high organizational maturity with careful planning and preparation of video surveillance and other security systems, including the policies and procedures regulating how the technology is used. To help system integrators and end users design, implement and operate video surveillance systems that are compliant with such privacy regulations, Milestone provides a holistic set of tools, including privacy guides, best practices and training resources to build privacy awareness. If you go to the Milestone website and search for GDPR, you’ll find 1,450 references. There’s a lot of useful information available. Education on privacy and cybersecurity The entire market needs to be educated on what’s being done with people’s sensitive information. Milestone carries out GDPR webinars that are mandatory for staff – as we have also done with cybersecurity training (both internally and externally for our partners) which is related when trying to preserve data privacy, access or sharing. Regarding cybersecurity hackers and our partners’ work with IT systems, current knowledge and best practices help to keep people’s sensitive information safe. Double authentication is becoming standard for managing access to company systems and websites. Data encryption is also key to the lockdown of information and its history of creation, access, user logs etc. Regular software updates with the newest version releases are also best practice to ensure against cyber trouble. At Milestone, we have a comprehensive system hardening guide online. It details the top five most effective cybersecurity strategies to focus on when combating cyberattacks: Isolate the device network from other networks. Educate employees about security threats. Use Active Directory for user and computer management. Enable encryption at every stage necessary. Separate the VMS server and client networks from the company’s business network. Ethics of facial recognition Advanced facial recognition technology has benefited Americans in countless under-publicized ways, helping to do many critical things, for example: find missing children, fight human trafficking, secure borders from drug trade, identify dangerous criminals, bring sexual predators to justice and thwart identity thieves. There is a difference between facial detection vs. facial recognition. Facial detection is a broader term and means that a system is able to identify that there is a human face present in an image or video. Facial recognition can confirm identity and thereby be used to control access to sensitive areas. Authentication/ verification helps verify a person is who they claim to be. The system checks a submitted photo against an existing template to verify that it is the same person – one-to-one (1:1) matching. This configuration is applicable to banking,…

In recent years, Artificial Intelligence (AI) has been the buzzword in the video analytics domain. Trade show stands are rife with AI demos promoting ambitious functionality set to change the face of CCTV in security. Impressive as many of these demonstrations are, there is a definite air of scepticism on the part of the end-user. Is the hype around AI warranted, and can science actually deliver? This feels reminiscent of a decade ago when video analytics promised to revolutionise CCTV monitoring. Today, reliable and effective analytics is the mainstream and is driving tangible business value. That said, there is no denying that the last five years of AI innovation has led to tangible and practical solutions, with the security industry finally starting to reap the benefits. However, AI is now at a precipice – on the cusp of what industry experts call an ‘AI winter’ – so, everyone is wondering what’s next and what is possible. This paper investigates precisely this, focusing on the physical security space.   What is AI? One formal definition of Artificial Intelligence (AI) identifies the technology with the “development of computer systems able to perform tasks normally requiring human intelligence such as visual perception, speech recognition, decision-making, and translation between languages.” In reality, the term AI covers a wide range of applications and tends to refer to the current problem being tackled, which of course is constantly evolving. When we think of AI in the security industry, this usually translates to a few key areas:  Asset protection & monitoring.  Access control. Business intelligence. Decision support. Machine Learning is the process of teaching a system to perform a task, while Deep Learning is just a subset of Machine Learning. There are many other non-deep learning based ML methods which, for the purposes of this paper, will be referred to as traditional ML approaches. Often, when AI is mentioned, what is really being referenced is the Machine Learning (ML) or Deep Learning (DL) algorithm powering that solution. For example, license plate recognition (LPR) is often the application of a DL model to locate and extract a license plate from an image, coupled with ML algorithms cross-referencing information from a database. Therefore, this application should be referred to as a combination of ML and DL – not simply AI. The distinction between traditional ML and DL is an important one, as the recent boom in AI solutions often refers to advances in Deep Learning techniques. In the majority of cases, the use of Deep Learning has led to a significant jump in accuracy over traditional ML techniques. For example, a well-known academic image classification challenge, in which images must be classified into one of a thousand different classes, has seen a notable increase in accuracy – going from 50% of the images being classified correctly in 2011, using traditional ML techniques, to nearly 90% today using modern DL techniques. The figure below illustrates the improvement in the ImageNet challenge over time. Machine Learning vs Deep Learning To understand Deep Learning’s dramatic improvement over traditional Machine Learning techniques, let’s look at how an example asset protection use case could be approached with both methodologies. The goal is to detect if the object in the field of view of a particular camera represents a threat and should generate an alarm (person, vehicle etc), or constitutes mere background noise that can be ignored. To begin, through the use of a movement-based tracker (another ML system) a camera has detected motion and defined a region of interest around the object.   Machine Learning (ML) The traditional Machine Learning pipeline generally requires the developer to represent an input (e.g., a region of interest in an image) into a structured feature descriptor of that input: for example, a set of numbers that represents the shape in the image (HOG, SIFT), or possibly another property in the image (colour, texture etc). The model is then trained by feeding labelled examples of the object feature descriptors you want to recognise (person, vehicle) and object feature descriptors of objects you expect to see but want to ignore (trees, shadows, animals etc.). The Machine Learning algorithm learns to group these feature descriptors into these categories so, when a new unlabelled feature representation is fed to the system, it can make an assessment as to which category it might fall into. A system’s accuracy hinges on a developers’ ability to come up with a feature descriptor which the Machine Learning algorithm can easily group into classes to detect vs those to ignore. One of the biggest advantages of using human-designed feature descriptors is the data required to train the ML model is reduced. Creation of labelled datasets to train any Machine Learning algorithm takes significant time and therefore resource. As a consequence, traditional Machine Learning techniques are still very much relevant due to this significant time and cost-saving. Deep Learning (DL) Deep Learning follows a similar process. However, instead of relying on a human-in-the-loop method of developing a robust feature descriptor, the Deep Learning system itself just looks at the labelled input data to learn the best way of grouping the images. By showing the system large numbers of samples (training), the system refines its model to best describe the data it is being shown. The disadvantage is that, for a Deep Learning model to learn that best representation from the data, a notably larger amount of data is necessary. However, although the data requirements are more significant, the Deep Learning approach removes the guesswork of a developer trying to define the optimal representation of an input to enable the system to learn. It also has the advantage that the same approach can be applicable to a range of different problems, whereas traditional ML may require redesigning the feature descriptor based on the application. Deep Learning has demonstrated its advantages over traditional methods. However, the real question is how it can be used to improve business processes or increase precision in detection, while reducing costs for security businesses….

This white paper discusses radar technology in security applications, and compares it with other available technologies. It also provides specific information about AXIS D2050-VE Network Radar Detector, its usage and its possibilities What is radar? Radar is a well-established technology for detecting objects. It was developed for military use in the 1940s, but is now widely used in civilian applications, for instance weather forecasts, road traffic monitoring, and collision prevention in aviation and shipping. Using radar technology for detection can reduce the number of false alarms and increase detection efficiency in conditions with poor visibility. AXIS D2050-VE Network Radar Detector is Axis’ first available radar-based motion detector. Owing to its advanced tracking algorithm, it is not only an affordable complement to security cameras, but it can also add valuable features to a surveillance system.   A radar device transmits signals consisting of radio waves, or electromagnetic waves in the radio frequency spectrum. When a radar signal hits an object, the signal is reflected or scattered in many directions. A small portion of the signal may be reflected back to the radar device, where it will be detected by a receiver. The detected signal provides information that can be used to determine the location, size and velocity of the object that was hit. Why use radar in surveillance? Due to its superior detection abilities in darkness or fog, a motion detector based on radar can be a cost-efficient complement to other types of surveillance. Reliable in challenging conditions By nature, radar surveillance is not dependent on visibility. Darkness, fog, or even moderate rainfall does not impair the detection abilities. There are other surveillance technologies that may also work in such conditions, for example thermal cameras equipped with video analytics, or PIRbased (passive infrared) motion detectors. However, surveillance based on radar can be a cost-efficient alternative to both solutions. Radar is easier to use, and more affordable than a thermal camera. Radar can also provide more information, at a longer range, than a PIR motion detector. Decreased false alarms Reducing the number of false alarms, while maintaining the detection efficiency of real incidents, is essential in surveillance. For example, alarms are often used to trigger a video recording. In case a forensic search would be needed in alarm-triggered recordings, it could be very time consuming to go through the recorded material if there were many false alarms. Motion detection systems often use video analytics applications that are triggered by a certain amount of pixel changes in the surveillance scene. Unnecessary or ‘false,’ alarms can typically be caused by effects such as moving shadows or light beams, small animals in the scene, rain drops or insects on the camera lens, movements caused by the wind, or bad weather. A detection system based on radar will only detect physical movement in a scene, ignoring purely visual effects such as shadows or light beams. Radar signals should also be generally less affected by rain or snow. In both radar detection and video analytics, it is possible to design the system so that small or swaying objects can be filtered out, as well as certain zones of irrelevant movements caused by, for example, wind in a tree. Complement to cameras A motion detector based on radar, exclusively, will not provide any visual confirmation. To efficiently identify the cause of an alarm, or to enable identification of individuals, the scene should also be monitored by a video camera. To add further value, rules could be established that state that only when both the video camera and the radar detector detect motion in an area will a motion detection alarm be transmitted to the operator or central monitoring station, along with detailed information about the object in motion. Such a collaborative validation can reduce false alarms even further. Axis network radar detector AXIS D2050-VE network radar detector is Axis’ first available radar-based motion detector. It can serve as an affordable complement to security cameras in medium-risk installations, improving detection in challenging conditions and minimizing false alarms. Owing to its advanced tracking algorithm and the positioning information it provides, the detector can also add new features and value to a surveillance system. Detection range and installation One radar detector unit provides accurate detection within a range up to 50m (164ft), within an angle of approximately 120 degrees. For coverage of a larger area, it is possible to use multiple detectors. Typical mounting height should be 3-4m (9-13ft). AXIS D2050-VE can be used as a stand-alone product, but may serve its purpose best as a complement to a camera that also provides a visual view of the scene. In order to facilitate a visual interpretation of the scene, the radar image as it is seen in the user interface can be easily integrated and calibrated with an uploaded reference map. The detector can be treated like a camera in the security system. It is compatible with major video management systems (VMS) and common video hosting systems. The detector comes with Axis open VAPIX interface enabling integration on different platforms. Typical installation scenes include fenced-off areas such as industrial properties or roofs, or parking lots where no activity is expected after hours. However, the detector’s advanced filtering and tracking function makes it valuable in most environments. Figure 2 shows a parking lot as monitored by the network radar detector and shown in the user interface. The radar image has been combined with a reference map of the scene. Include/ exclude zones The network radar detector comes with an intuitive user interface where the user should draw one or more ‘include zones,’ and possibly ‘exclude zones,’ within the detection range. Detection and tracking of objects takes place continuously within the whole detection range. However, owing to its filtering functionality, the detector will trigger actions only on objects detected within an include zone. The filter can also be set to ignore certain object types, and only trigger on, for example, large objects, only vehicles, or objects that have been tracked for a…