As AI continues to advance, we in the security industry must develop robust detection methods to preserve the accuracy and integrity of data, as this data is required to identify and respond to threats in the physical world. This is especially true on our continually advancing reliance on technology like video surveillance systems, VoIP intercom and phone systems, and protective intelligence used in security operations centers.

Understanding how to identify AI-generated content is crucial for maintaining trust and accuracy in an ever-evolving digital landscape. By staying vigilant and adapting detection strategies to keep pace with AI advancements, individuals and organizations can contribute to the ongoing battle against misinformation and deceptive practices, fostering a digital landscape built on trust and authenticity.

While the security industry progresses to embrace this technology in various capacities, let’s delve into some strategies that we mere mortals can use to detect AI’s presence in different domains, such as images, audio, and text.

While the security industry embraces AI in various capacities, understanding how to identify AI-generated content is crucial for maintaining trust and accuracy.

How to Detect AI in Images

Noise Analysis: AI-generated images often carry subtle patterns or artifacts that deviate from those present in naturally captured visuals. By scrutinizing noise patterns, and hard-to-generate items like hands, feet, logos, and background text in images, you can unveil the telltale signs of images crafted by AI algorithms. This nuanced examination aids in distinguishing between authentic and machine-generated visuals.

Examine the metadata: AI-generated images may lack the typical metadata markers associated with photos taken by traditional cameras. Anomalies in metadata such as geolocation, camera model, lens settings, etc., can serve as a red flag, prompting further investigation into the image’s authenticity.

Reverse image search: Employing reverse image search tools is a valuable technique to ascertain the origin of an image. AI-generated images often lack real-world counterparts, making them stand out in search results. This method is particularly effective in identifying instances where AI has been employed in the creation or manipulation of visual content.

How to Detect AI in Audio

Spectral analysis: AI-generated audio frequently exhibits specific spectral patterns or anomalies not found in naturally occurring sounds. Spectrogram analysis can unveil these hidden patterns, assisting in the identification of AI-generated audio content. This analytical approach is vital for differentiating between human and machine-generated sounds.

If you don’t have a spectrum analyzer handy, try these two human-capable detection methods. First, listen for words or phrases that get repeated – AI-generated content will use the same cadence, rhythm, and pronunciation, giving you a clue to its origin. Second, if you are having a dialog with AI, it does not know how to respond to bizarre questions – so if you get a call and it sounds like your family member asking for help and money, ask the AI for a code word like â€śwhat am I holding in between the toes of my left foot?” While the AI will have no idea how to respond, a family member will give you the secret code word or at least ask what the heck you are talking about.

Voiceprint analysis: Analyzing the voiceprint of a speaker can be instrumental in identifying AI-generated voices. AI often struggles to replicate the nuanced characteristics present in human speech, and voiceprint analysis can reveal discrepancies that may not be perceptible to the human ear.

Linguistic analysis: AI-generated speech may lack the natural flow and coherence found in human communication. Identifying unnatural syntax, grammar, or contextual inconsistencies can provide valuable clues in determining the authenticity of audio content.

How to Detect AI in Text

Linguistic anomalies: AI models may struggle with nuanced language use, so scrutinize for unnatural word choices, awkward sentence structures, or inconsistencies. Thorough linguistic analysis is crucial for revealing subtle signs of AI involvement in machine-generated text.

Stylometric analysis: AI models may exhibit consistent stylistic features that differ from the diversity found in human-generated content. Stylometric analysis, which focuses on patterns in writing style, is a powerful tool for detecting these subtle variations.

Contextual inconsistency: AI-generated text may struggle to maintain context throughout a piece of writing. Abrupt changes in tone, topic, or inconsistency in narrative flow can reveal instances where AI has been employed in the creation of textual content.

Cross-Domain Detection

Multi-modal Analysis: Combining techniques from image, audio, and text analysis creates a comprehensive approach to detecting AI across various domains. Cross-referencing results from different modalities can enhance the accuracy of AI detection and provide a more robust defense against machine-generated content.

Machine learning classifiers: Training machine learning classifiers using labeled datasets is an effective approach to distinguishing between AI-generated and human-created content. This method leverages the power of algorithms to identify subtle patterns across images, audio, and text, contributing to a more sophisticated and adaptive detection system.

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This article originally appeared in the Ěý´Ç´ÚĚý. Paul F Benne is the President of ĐÓ°ÉÔ­´´ and has over 35 years in the protective service industry.

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These technologies, which enable the identification of individuals based on their facial features, have been heralded as a breakthrough in enhancing security and streamlining law enforcement operations; however, they have also raised profound concerns about privacy, civil liberties, and potential abuses. As a response to these concerns, numerous cities and countries have started banning or heavily regulating the use of facial recognition technologies in these domains.

This has a big impact on the security industry as we prepare to understand, market, and deploy these technologies. Your customers will have questions, and their integrator should be able to provide some answers. Thus, it is essential to explore the arguments for and against the banning of facial recognition technologies in security and law enforcement to deliver the most informed recommendation to an end-user.

While the proponents of facial recognition technologies emphasize their utility, opponents argue that the risks and drawbacks far outweigh the benefits, leading to a growing movement to ban or heavily regulate their use in security and law enforcement.

The Rise of Facial Recognition Technologies
Facial recognition technologies have evolved at an astonishing pace. These systems utilize computer algorithms and databases of facial images to identify and verify individuals by analyzing distinct facial features. The technology has numerous applications, ranging from unlocking smartphones to enhancing security measures in public spaces and assisting law enforcement agencies.

Advocates of facial recognition technologies argue that they significantly contribute to national security and public safety. They cite instances where these systems have successfully identified and apprehended criminals, located missing persons, and thwarted potential terrorist threats. The potential applications are immense, including the rapid identification of suspects, enhancing border security, and improving the speed and accuracy of validating a person that may have been placed on a watch list.

The Case for Banning Facial Recognition Technologies
While the proponents of facial recognition technologies emphasize their utility, opponents argue that the risks and drawbacks far outweigh the benefits, leading to a growing movement to ban or heavily regulate their use in security and law enforcement.

Privacy concerns: The primary argument against facial recognition technologies is the grave invasion of personal privacy. The constant surveillance and monitoring of individuals in public spaces, without their consent or knowledge, raises serious ethical and legal concerns. The widespread use of these technologies could turn public areas into surveillance states, infringing on citizens’ rights to privacy and anonymity.

Inaccuracy and bias: Opponents have said these systems have been shown to exhibit a significant degree of inaccuracy, particularly when it comes to recognizing individuals from diverse racial and ethnic backgrounds. This inherent bias can lead to wrongful arrests and misidentifications, disproportionately impacting marginalized communities.

The potential for racial profiling and discrimination is a valid concern; however, tests of different facial recognition technologies have been conducted within the industry by IPVM.com that shows these systems can be successfully deployed but vary in their success by manufacturer.

Surveillance state: The deployment of facial recognition technologies has the potential to create a surveillance state, where individuals’ every move is tracked and recorded. This dystopian vision raises concerns about the erosion of personal freedoms and the establishment of a society where people are constantly watched and restricted in their actions.

Lack of accountability: In many cases, the use of facial recognition technologies lacks transparency and accountability. Law enforcement agencies and security firms may use these technologies without adequate oversight or regulations in place. This absence of checks and balances can lead to abuses of power and violations of civil liberties.

Security vulnerabilities: Facial recognition systems are not immune to security vulnerabilities. Hackers and cybercriminals could exploit these technologies to access sensitive information or manipulate data for malicious purposes. These vulnerabilities pose a significant risk to national security and individual privacy.

Bans and Regulations
In response to these concerns, several countries and cities have taken measures to regulate or prohibit the use of facial recognition technologies in various capacities. The website www.banfacialrecognition.com has a comprehensive list of U.S. locations where this technology is in use, under regulations, or banned.

European Union: The European Union has taken a proactive stance on protecting citizens’ privacy by implementing the General Data Protection Regulation (GDPR). GDPR places stringent regulations on the use of biometric data, including facial recognition technology. It requires explicit consent for data collection and mandates clear rules for its use.

San Francisco, California: In 2019, San Francisco became the first major city in the United States to ban the use of facial recognition technology by government agencies. The ban is aimed at preventing government surveillance and protecting civil liberties.

Massachusetts: Massachusetts followed suit with regulations aimed at protecting the privacy of its citizens. The state enacted a law that prohibits facial recognition technology for law enforcement purposes, except for cases involving serious criminal offenses.

Portland, Oregon: Portland passed a ban on the use of facial recognition technology by both public and private entities in 2020. The city cited concerns about civil rights and civil liberties as the driving force behind the ban.

The banning of facial recognition technologies in security and law enforcement is a complex issue that revolves around striking a balance between security and privacy. While these technologies hold significant promise in enhancing safety and aiding law enforcement, their potential for misuse, bias, and invasion of personal privacy has sparked a growing movement to restrict or prohibit their use. The global trend of implementing regulations and bans on facial recognition technology reflects the need to safeguard individual freedoms and civil liberties in an increasingly connected and surveilled world.

As you specify and endorse these systems for customers, I recommend consulting the Security Industry Association’s advocacy page on facial recognition technology.

What to Tell Your Customers
The future of facial recognition technology in security and law enforcement will likely involve continued debate and evolving regulations as governments and communities grapple with the challenge of preserving public safety while respecting fundamental rights. As technology advances and the societal landscape changes, finding a middle ground that respects both security concerns and individual privacy rights will remain a pressing issue for lawmakers, civil rights activists, and the general public.

As an industry we should note that the successful deployment and accuracy of these systems largely comes down to understanding the correct use-case, and designing the system to support the intended need. Too often, we rush to implement without considering proof of concept, not by the manufacturer, but within the context of the customers environment and application.

As you specify and endorse these systems for customers, I recommend consulting the Security Industry Association’s advocacy page on facial recognition technology (www.securityindustry.org/advocacy/policy-priorities/facial-recognition). The site includes research statistics that show positive support of facial recognition for public safety, air travel, workplace and other application areas. It also includes a full shareable document and a fact sheet exploring the values and the benefits of facial recognition that outlines each of SIA’s core principles regarding the responsible and effective use of facial recognition technology and makes recommendations for public- and private-sector applications of the technology, including by law enforcement. There are also success stories that integrators can use to validate the effectiveness of the technology.

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This article originally appeared in the Ěý´Ç´ÚĚý. Paul F Benne is the President of ĐÓ°ÉÔ­´´ and has over 35 years in the protective service industry.

The post Tech Trends: Should Integrators Specify Facial Recognition? appeared first on ĐÓ°ÉÔ­´´.

The gold standard for decades in maintaining dedicated and reliable inbound and outbound communications has been the POTS (Plain Old Telephone Service) line. It has been very typical to install POTS lines for duress alarms, intrusion detection systems, emergency intercoms, and dedicated voice lines for security operations and operations centers.

One of the great appeals for using POTS (besides being the only thing available) was that the POTS line provided both power and communications over a copper wire. The phones were powered by the telephone companies’ infrastructure, moving the points of failure outside of the users control, and onto the responsibility of the service provider. This type of system would provide for communications even if power was out. Amazingly, you could lose power and the phone would still work. Sure, it doesn’t sound impressive now, but in the 1970s it was.

As cellular technology became more dependable and widely available, many companies started to use this communications pathway as a backup or redundant method of communications; however, at the time, the technology was cost-prohibitive to deploy and use as a primary communication pathway, unless site specific conditions warranted its use in that capacity. Cellular technology has since become a viable option for both primary and backup communications of voice and data.

Now with more and more devices being IP-based, as well as the need to consolidate systems for voice and data communications, service providers are sunsetting the old and expensive-to-maintain POTS service – moving to Voice over Internet Protocol (VoIP).

The Rise of Voice over IP
VoIP is a technology that enables voice calls to be transmitted over the internet rather than traditional telephone lines. It utilizes packet-switched networks, converting voice signals into data packets for transmission.

This innovation has gained traction in recent years due to several compelling reasons:

1. VoIP offers substantial cost savings. Traditional landline services require dedicated infrastructure, which can be expensive to install and maintain. In contrast, VoIP utilizes existing internet connections, eliminating the need for separate telephone lines. This cost-effectiveness is especially attractive to small businesses and startups looking to streamline their operations, and it is commonplace for large enterprises.
2. VoIP provides an extensive array of features that surpass those of POTS. Call forwarding, voicemail transcription, video conferencing, and virtual phone numbers are just a few examples of the rich feature set offered by VoIP. These features enhance productivity, collaboration, and customer service capabilities, enabling businesses to operate more efficiently and competitively.
3. VoIP systems are highly scalable, allowing businesses to easily add or remove lines as per their requirements. This flexibility eliminates the limitations imposed by traditional phone systems and accommodates the ever-changing needs of modern enterprises. As companies expand or downsize, VoIP adapts accordingly, ensuring seamless communication without unnecessary costs or complications.

More Benefits of VoIP
The advantages of VoIP extend beyond cost savings and feature-rich functionalities. One of the most significant benefits is geographical flexibility. With VoIP, users can make and receive calls from anywhere with an internet connection. This eliminates the constraints of physical location, making it easier for businesses to establish virtual offices, remote work setups, and global presence. This allows for some unique applications in the security world as well.

Additionally, VoIP integrates well with other communication channels, such as email, instant messaging, and video conferencing platforms. This integration enhances overall communication efficiency, enabling seamless transitions between different modes of interaction. Whether it is integrating voice calls into customer relationship management (CRM) software or automating call routing, VoIP empowers businesses to streamline workflows and enhance customer experiences.

Furthermore, VoIP is compatible with various devices, including smartphones, tablets, and desktop computers. Users can access their VoIP services through dedicated apps or web-based interfaces, providing a unified communication experience across multiple devices. This flexibility ensures that individuals and businesses are always connected, regardless of the device they use or their physical location.

The Challenges of VoIP and Data Communications
IP-based technology does provide some challenges in maintaining communications pathways that are highly reliable with an uptime acceptable to support critical communications. While previous communications relied largely on the provider maintaining equipment and uptime availability, IP-based technology now requires that the provider and the customer maintain their systems so that they can be relied on for critical communications.

When migrating from a POTS-based method of communicating critical voice and data to a IP-based system, adding proper battery backup, redundant communication pathways, and proper network configurations to ensure network traffic priority is critical.

Article Link –

This article originally appeared in the Ěý´Ç´ÚĚý. Paul F Benne is the President of ĐÓ°ÉÔ­´´ and has over 35 years in the protective service industry.

The post Tech Trends: The Rise of VoIP appeared first on ĐÓ°ÉÔ­´´.

The advancement of technology over the past three decades is astounding. Just a short 20 years ago, the vast majority of video surveillance systems were still using VHS tapes, multiplexers, and analog cameras with resolutions that were just a fraction of todays most basic of imaging technologies. Patrol, response, and investigations were exclusively done by manpower.

Today, we are seeing a massive influx of true Artificial Intelligence – albeit mostly basic video-based analytics – into these traditional security technologies.

Basic AI in Practice for Security

We are now able to see the emergence of AI’s most elementary abilities surfacing in the security industry. An example is Coresight.ai, whose technology is able to provide facial identification of individuals using standard video surveillance cameras – even when the face of the subject is partially obscured. The technology provides the ability to match a person of interest on a watch list to individuals captured on live and recorded video.

Consider Zeroeyes and Omnilert, whose AI technologies use standard video surveillance cameras to detect a person in possession of a gun, prompting the system to trigger an action or alert prior to the subject carrying the gun making entry to a facility or shooting the weapon.

Companies like Viisights bring behavioral analytics that are able to detect a wide variety of behaviors like fighting, crowd formation, accidents, slip-and-falls, throwing objects, or other aggressive behaviors.

The vast amount of currently installed security technology is wholly reactive, meaning that an incident must take place prior to a mitigative action being taken. These technologies make security systems and departments proactive in a way we have never seen. AI can greatly speed the detection and response to many incident types, and also trigger on precursors that happen before an actual incident occurs.

As for AI and robotics, by now you have likely seen Spot the robot dog from Boston Dynamics, and perhaps some of you have seen Atlas, the most dynamic humanoid robot in the world from the same company. There have been plenty of similar robots roaming tradeshow floors the past couple of years.These robots now have human-like agility and the ability to analyze their environment. They are equipped with an array of sensors that give the robotic platform detailed information on its movement, surroundings, and position, as well as process incredible amounts of data in milliseconds. The robot can calculate thousands of probable scenarios, weighing what ones have the most likelihood of occurring, then almost instantly react to the situation, faster than humans are capable.

Imagine the Possibilities

You can easily extrapolate the possibilities. Consider the integration and convergence of just these few AI technologies and robotics mentioned: A person with a gun exits their vehicle at a school or bank, the AI determines the presence of a gun and also determines that the person in possession of the gun is on the facility’s watch list (placed on the list perhaps because they are a terminated employee or a student identified as high risk), this triggers an automated lockdown, pre-scripted announcements, law enforcement notifications, starts live video streaming to responding agencies, and automatically tracks the location and actions of the subject. Then a security robot, powered with this real-time information, moves into place to intercept the subject as they attempt to gain entry into the facility.

The robot can analyze threats, verbal exchanges, micro expressions and movements of the subject against thousands of like scenarios or previously documented incidents to make a determination of the subject’s probable actions before the subject even takes them. Then with faster-than-human reaction time and agility, engage the subject with less-than-lethal force to disarm and subdue the subject.

While we are not quite there yet, it is certainly on the horizon. In April, the New York Police Department announced the use of Spot the robot dog and other robots to start patrolling Times Square.

Playing Devil’s Advocate

To say this article is far-reaching would be a false statement; so why would I choose to open with such a negative statement like “the total destruction of mankind?”

Let’s entertain another scenario, an adversarial one. We know that all technology eventually becomes more commonly understood and can be used for both good and bad. Currently, the development of AI and robotics technology has little to no regulation or oversight, providing few limits to what this technology can be programmed to do, or better yet, to not do.

Elon Musk is quoted as saying AI is “quite a dangerous technology” and that AI has the potential to destroy civilization. What happens when an adversary – criminal enterprise, enemy state, or the AI itself – obtains and programs AI to do their bidding?

Imagine an adversary who develops an integrated AI robot with advanced sensory technology and physical agility, the ability to analyze and process petaflops of information to render an action hundreds of times faster than any human’s ability. The outcome is potentially unstoppable. It is a frightful view into a “Terminator” movie-type threat that security and law enforcement teams are not remotely ready or equipped to respond to.

Avoiding the Ugly

We should not be surprised that the security industry is embracing the newest emerging technologies such as AI and robotics. As illustrated, they are an obvious force multiplier and bring new efficiencies to improve the security function.

However, the bad is there, just bubbling under the surface.

In the end, the security industry should embrace a better approach to develop and use this technology with some firm ground rules – to hopefully harness the good and avoid the bad and potentially ugly.

Article Link –

This article originally appeared in the Ěý´Ç´ÚĚý. Paul F Benne is the President of ĐÓ°ÉÔ­´´ and has over 35 years in the protective service industry.

The post Tech Trends: AI – The Good, the Bad, and Perhaps the Ugly appeared first on ĐÓ°ÉÔ­´´.

But its not realistic to work all day long and not use your work supplied computer for personal business. So, how can you protect yourself without undermining your companies acceptable use policies or loosing your data at the whim of your employer? Here are three tips to help keep you personal data safe:

1. Use a USB thumb drive. This oversimple approach is straight forward. Use the computer as needed and store your personal information on a USB thumb (that you own). Don’t use the “chachkies” given out at trade shows by your company, that could be construed as company property.  Furthermore, websites such as portableapps.com can install and launch applications directly from a USB drive without having to install on a host computer.
2. Use a cloud based storage service WITHOUT installing their synchronizing software on your work computer. As needed upload/download temporary working files to the storage service from a folder marked “personal files and delete the local files after use. If you install the storage services sync’ing software you may be in violation of company policy, and all those files that have technically landed on company property are at risk.  Accessing these sites through Chrome’s incognito mode or Firefox’s privacy mode ensure that no personal information is retained on the host computer.  However, be aware that your network traffic can still be monitored and recorded.
3. Encourage your company to create and honor a personal folder policy. Basically this type of policy would allow you to store at will, non-IT-threating personal files on your work computer. The company would honor the boundary of your personal information, while allowing you to retrieve and retain that information in the event your employment is terminated.

As a personal best practice, you should always be in control and in ownership of your data. The best way to put this into perspective is to think about if you were to go to lunch, and from that point forward never have access to your work computer again. Would you be missing anything?

Additional privacy considerations:

• If you use an app like Evernote for personal and business use, consider creating separate accounts.
• Is your LinkedIn profile managed by your corporate email address?  What if tomorrow, you don’t have access to your corporate email account?

The post 3 Steps to Securing Personal Data on Company Computers appeared first on ĐÓ°ÉÔ­´´.

The NCEES (National Council of Examiners for Engineering and Surveying) recognize 25 different engineering trades.  The NCEES provides licensing in these trades to certified engineers who wish to become Professional Engineers.  See a full list at this link: .  The NCEES does not list Security Engineering.

So what is Security Engineering?  Let’s break it up and start with the term “security.”  According to Merriam-Webster, “security” is defined as “the state of being protected or safe from harm” and also “things done to make people or places safe.”  Now looking at Merriam-Webster’s definition for “engineering,” they state: “the application of science and mathematics by which the properties of matter and the sources of energy in nature are made useful to people.”  Now, if you’re following along, type in “security engineering” into Merriam-Webster.  The definition is not found.

Security Engineering is the application of science and mathematics by which the proper ties of matter and the sources of energy in nature are used to provide a state of protection and keep individuals and/or their property safe from harm.

Easy peasy.

When asked, and I have a few minutes to explain I usually tell it like this: I provide my clients with engineering expertise when selecting and deploying any type of physical, electronic, cyber, cultural, operational or non-tangible security countermeasure to protect and thwart any type of threat against them or their assets.  Refer to Paul’s post on the security domains to learn what each domain encompasses (ADD LINK).

Okay, so are we actually “engineers?  Yes.  I for one, am technically, by school, an Electrical and Computer Engineer.  Given the requirements today of modern security engineering and the technologies deployed by security engineerings, low voltage electrical and computer engineering knowledge is required.  I plan on expanding this idea in future posts.

The term “engineer is thrown around quite a bit today. Their are many variations of engineer, engineering technician, programmer, etc. and a quick Monster job search provides many varied positions in many varied fields.  Their are some big educational and training differences between engineers and engineering technicians, for example.

However, when looking specifically at the term Security Engineer, I often get reached out to by recruiters but the position they’re offering is typically an IT Security Engineer.  The jobs involve network cyber security requirements and programming knowledge.  A true Security Engineer is well rounded in all the security domains and understands the requirements for cyber security (firewalls) and physical security (berms and planters).

To expand on this, we look at the NCEES and the licensing of engineers.  When becoming a Professional Engineer through the NCEES, an engineer’s education and work experience are all evaluated.  The engineer is placed through two grueling eight hour exams, typically four years apart.  Upon successful completion of the exam, the engineer becomes licensed in his or her state and dubbed a Professional Engineer with “P.E. as a title.

As you can see, my name (at the time of this article) has an “E.I.T. suffix.  This stands for “Engineer in Training and signifies that I am halfway to achieving my P.E. license.

The most important aspect of the P.E. is that once those letters are attached to an engineer’s name and they have become a certified, professional engineer, they are no longer a civil engineer, or a mechanical engineer, or a security engineer.  They are an Engineer.  A title that requires the understanding, even if mildly, of all aspects of engineering.  The individual does not need to be an expert in every field of engineer, but must excel at their own discipline.  The awareness of other trades and how their trade can impact others is vital to the success of a professional engineer.

Security is a field that impacts many of the common trades involved in today’s construction projects.  Security is a necessity to many of our Clients that is typically not a profit builder, but a budget spender.  To help determine the most economical, efficient, and intelligent selection and deployment of countermeasures for your organization, only a Security Engineer with the proper knowledge can confidently secure your assets.

In the next post, I am going to discuss the differences and the interactions between a Security Consultant and a Security Engineer, and why you need both.

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