When it comes to surveillance, there is a fine line between privacy and public safety. Because of this, surveillance laws are often scrutinized by both sides. A new bill was introduced at the end of 2016 which requires any local law enforcement agency in California that uses surveillance technology to submit a plan to local officials on how it uses equipment and information collected. This would need to include surveillance plans for any facial recognition software, drones, and even social media monitoring, and would be presented at an open hearing.
While this disclosure from law enforcement may put some worries at ease, others may want more. Privacy advocates believe that this is still not enough to cover spying equipment and technology that is continuing to evolve and expand. On the other side, law enforcement officials argue that creating plans and policies for each device may be unfeasible and interfere with investigations.
But state Senator Jerry Hill (D-San Mateo) says that it was introduced “to create transparency and a check and balance.” Without regulations on these devices and technology, they can easily be abused and infringe on our privacy rights.
With fairly comprehensive digital privacy laws, California has been actively working toward disclosure when it comes to law enforcement surveillance. State laws require a probable cause warrant for access to digital content and devices (ex. cell phones) and law enforcement must catalog information and make it publicly available.
The new bill gives agencies until July 1, 2018 to draft policies detailing all the types of surveillance technology used and the authorized reasons for using them, along with the types of data collected, who can access them, and a description of their training. It also prohibits an agency from acquiring new technology unless approved by local officials at a regularly scheduled public meeting.
Last year, two surveillance laws went into effect, one of which requires to draft and publicly post privacy and usage policies for operating automated license-plate recognition software. The other requires the same for the use of cell-site simulators (“Stingrays” or “Dirtboxes”). These are powerful tracking devices that function as fake cellphone towers to collect information. However, their ability to collect information from innocent people not under investigation has sparked outrage and court battles.
Despite current surveillance laws, privacy advocates believe that not all agencies are complying and that not enough is being done to ensure that they do. To evade the disclosure requirements, agencies could borrow technology from other federal agencies, which is not subject to state law.
In an effort to check compliance, the Electronic Frontier Foundation and other nonprofits and watchdog groups searched through numerous California government websites to make sure surveillance policies were posted. While many were easily located, policies for at least 90 agencies (which, based on public records, were believed to use surveillance technology) could not be found. Since this task in April 2016, more agencies have posted their policies online.
While the new bill is meant to be inclusive and comprehensive, concerns remain. Some worry that criminals may figure out how they are being tracked, others bring up issues of time sensitivity when it comes to buying or borrowing new technology, and privacy advocates are still skeptical about the cost, risks, and enforcement.
There are obviously mixed feelings about this new bill, and other surveillance laws. What are your views? Share your thoughts and opinions with us on Facebook, Google+, Twitter, LinkedIn, and Pinterest.
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We have seen the video surveillance industry change over the years. With improvements in quality and accessibility, surveillance camera popularity among businesses and consumers has grown. As we embark on this New Year, we look ahead to what new surveillance trends are on the horizon.
According to industry experts, aside from working on image quality and cost-efficiency, we will see an increasing focus on software developments. Things like built-in intelligence, deep learning, and other advances in video management are sure to surface this year.
New vendors and product lines with new configurations are likely to emerge this year as well, expanding upon multi-sensor and multi-directional cameras. The advanced technologies will soon make their way to the market for home and private use, forcing others to provide alternate offerings.
Managed services and moving toward cloud computing will rise in demand. By utilizing managed services and the cloud, businesses can manage their cyber security risk by employing companies whose sole purpose is to maintain data security. This will then force manufacturers to provide end-users with more network-based solutions.
With cyber security issues with surveillance cameras and devices making headlines last year, it has become a more prominent concern. This negative attention can drive down demand, which means manufacturers must address this issue immediately and proactively.
Things that will be considered include rigorous testing of products, increasing end-user and integrator education on how to use the system as well as a best practices guide. Firmware must be updated quickly and often, especially when new vulnerabilities are found.
Overall, cyber security must be approached as a team effort. Manufacturers should take all considerations into account when building and designing hardware and software, as well as strengthen password requirements and incorporate strong data encryption, and take lead when educating users and the industry of potential risks. In the same vein, customers should know what is insecure and how to best protect themselves for attacks.
Competition will be high throughout the year. Most manufacturers are working to improve image quality, frame rate, and low-light performance to please the consumer demand. As features and functions progress, so will the surveillance industry as a whole. Bottom line for customers is that they will be looking for the best solution with the best total cost of ownership.
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The use of artificial intelligence in security systems provides more flexibility, especially with new cyber threats always emerging. Namely, machine learning has garnered much attention for its involvement and improvement of security systems.
Most people use the term “artificial intelligence” loosely these days, but it traditionally refers to the theory and development of computer systems that may perform human tasks. Machine learning is a type of AI that allows a computer to learn, grow, and change when presented with new data.
The evolution of AI can be best described in three stages. First is the basic expert system. If we used this system to help distinguish between a dog and a cat, for example, it would use a single feature such as number of teeth to make the decision. Second is the probability-based system, which evaluates different factors (ex. number of teeth, weight, size) to determine the probability (expressed as a percentage) of the object being a cat or dog. Lastly is deep learning, which uses seemingly endless amounts of labeled samples to differentiate between cats and dogs.
If we applied these to antivirus systems, you could understand how a basic expert system would be weak and need constant updating for new threats. The probability-based system would be a bit stronger, however, only so many features would prove relevant resulting in disregarded data. Deep learning seems the most promising, and a startup called Deep Instinct is looking to develop this approach for cyber security.
Within the Deep Instinct laboratory, the deep learning system is trained on all the known samples of malware, which takes about a day to complete. The process requires heavy-duty graphical processing units to analyze the data, and the end result is a trained system about a gigabyte in size. It is then reduced to about 20 megabytes and can be installed on any endpoint device (including mobile). It works to analyze any incoming threats within a few milliseconds to keep your devices safe.
To keep the system up -to-date, new malware samples are added every few months, and updates are automatically sent to the end point devices. But even if the system is not updated for months, the small brains within the end point devices remain vigilant and can detect new files. The success rate is promising and deep learning systems will likely gain more popularity over time.
While deep learning systems are great for detecting threats, they are not the best for explaining how they did it. Eureqa is a proprietary AI engine from Nutonian whose main job is to find out why things happen. It has proven very valuable for researchers and journal publications, but it also plays a role in cyber security by helping to determine the anatomy of a cyber attack.
Still, cyber security can be a tricky mess. Constant updates are necessary thanks to appearance of new threats and attacks daily. Even though you are employing security systems to protect your data, there are still vulnerabilities between updates. And during that time, hackers can use the security software to test their attacks until something breaks through, leaving numerous customers at risk.
Tailoring your cyber security approaches can help to combat this. For example, Masergy Communications is a managed networking company which uses a combination of both local and global factors to predict and prevent cyber security issues or attacks. The unique local indicators help to improve accuracy.
Acuity Solutions offers the BluVector appliance which uses machine learning for cyber threats, and also uses a local and global approach. The pre-trained engine learns what a benign code looks like, receives updates based on global data, but also engages in new learning based on the individual customer. While the global data is shared, the customer-specific data is not, creating a more unique and secure experience.
As discussed, artificial intelligence and machine learning can greatly benefit different aspects of cyber security. What are your predictions on the future of AI in security solutions? Share with us on Facebook, Google+, Twitter, LinkedIn, and Pinterest!
For a wide range of security cameras and surveillance equipment, please visit SecurityCamExpert.com. To speak with a representative or request a site survey, please call 1-888-203-6294.
From law enforcement surveillance to recreational use by consumers, drones have grown in popularity over the years. Because of their advanced capabilities, a company has even created a drone home security system.
Proposed by Sunflower Labs, the system is designed to complement an existing alarm or security system. The drone streams video to your smartphone when a potential danger is detected, allowing you to determine whether you need to take further action or not.
The system is comprised of a drone plus in-ground smart lights used to detect motion, vibration, and sound. Using advanced data analytics, the system can differentiate humans from cars and animals. When there is a disturbance, artificial intelligence determines whether it is dangerous or not. For example, mail delivery persons will be recognized by their behavior (typically a quick stop by the front door or mailbox).
On the other hand, suppose a person approaches the back door and lingers. A push notification will be sent and you will be asked if you would like to look into the situation. Assuming you say yes, the drone will lift from its perch and autonomously fly to where the suspicious person is located. The drone will hover (30ft) until it is told to return to its nest. There is also an option within the app to alert local police.
By sending the drone to investigate first, Sunflower Labs CEO Alex Pachikov believes that this will decrease the number of false alarms. The drone also allows you to monitor your entire property instead of just entrances and exits, like most other security systems.
The drone is designed to be a minimal nuisance. Currently, the propellers automatically shut off if they hit anything, and considering its size, it is relatively quiet. The ultimate goal is decrease noises to a quiet hum and to get its weight down to half a pound (its current weight is two pounds) before it ships. In addition, it features two cameras which only capture footage of the home owner’s property in order to protect neighbors’ privacy.
Still, there are safety, privacy, and nuisance concerns about the drone. Since August, new rules allow operators who have passed an aeronautical exam to fly commercial drones under 55 pounds no higher than 400ft. And autonomous flying is not allowed for commercial drones.
Despite this, Sunflower Labs has no worries. They believe the policies will not apply as the homeowner will use the drone for non-business purposes. Since recreational users face fewer restrictions, homeowners will likely be held in the same regard.
As this system continues to develop, more details will emerge. As for now, the lights are expected to cost $159 each, and the drone may be rented for a fee (comparable to the cost of traditional alarm systems).
For traditional security cameras and equipment, please visit SecurityCamExpert.com. If you have any questions or need assistance, please call us at 1-888-203-6294.
Staying connected to your home is a convenience in itself, but in the case of natural disasters and emergencies, it can be an invaluable tool. If you live in an area prone to extreme weather, you likely have an emergency plan in place. However, a connected home can provide new and safer options to manage the situation.
Regardless of whether it is your home, vacation property, or even the home of a loved one, here are some ways connected technology can benefit you in the face of an emergency and beyond.
Unfortunately, emergency evacuations mean abandoned homes and properties, which is ideal for looters. With connected security cameras, you can keep an eye on who might be entering your home, as well as monitor the possible damage occurring as a result of the natural disaster.
Installing water sensors can alert you of flood conditions and even slow leaks, which can cause significant damage over time if not detected early.
Aside from water sensors, carbon monoxide and gas detectors can save lives by alerting you when levels become dangerous.
Connected devices such as smart locks and garage doors often have motion detection sensors which notify you when someone enters or exits your home.
Remote Monitoring & Push Notifications
Because you can monitor from a safe distance, these are ideal in emergency situations. Push notifications provide up-to-date alerts which allow you to deal with situations in a timely fashion. Both enable you to monitor and understand what is going on without putting yourself in danger.
Affordable & Reliable Communication
Because these technologies seem so advanced, people often interpret this as complicated and expensive. However, this is not the case. There are various solutions on the market that offer relatively simple installation for cost-effective prices. Because the accessories and transmission processes have become more affordable over the years, connected technology is more accessible and easier to manage and maintain.
You can possibly get a discount on your homeowner’s insurance if you install smart, connected devices. Many insurance providers are now offering discounts for those with smart homes. Some providers even partner with connected technology manufacturers to offer more incentives for customers.
Furthermore, choosing smart devices for your home helps to relieve emergency personnel and law enforcement agencies. Instead of entering an area affected by a natural disaster, you can check in on your property remotely to stay out of harm’s way and avoid interrupting the ongoing work of emergency personnel.
Peace Of Mind
As a whole, connected devices can offer some peace of mind in stressful, dire times. While these devices can be extremely helpful in disaster areas, all homeowners can benefit from a connected home.
Loss prevention tactics began with in-store monitoring and patrol. As our technologies evolve and the popularity of online shopping continues to grow, security measures have improved. In fact, a U.S. retail fraud survey revealed that spending on store fraud prevention declined while online fraud prevention spending increased.
Because cybercriminals are constantly sharpening their skills, loss prevention specialists are using new technologies to their advantage as well. For example, data analytics have helped specialists understand suspicious behaviors and patterns in the e-commerce and m-commerce environment, and social media vigilance has helped to identify potential threats.
As the retail industry continues to expand and grow, what’s to come in the future of retail loss prevention?
It’s true that retail uses a variety of different technologies to operate, including point-of-sale transaction profiling as well as RFID tracking. However, now more than ever, video surveillance is playing a larger and smarter role.
With video surveillance, loss prevention officers have been able to catch thieves in the act and the recordings have provided excellent evidence. With the introduction of built-in facial recognition technology and video analytics, video surveillance can do so much more.
In the same vein, the smart features, connectivity and convenience put these devices at risk. While their role is to protect the business, retailers must do their part to protect their devices, data, shoppers, and employees.
IT & Outside Vendors
Because of this, loss prevention specialists must develop their knowledge and skills with the new technology. They should understand how to use data analysis to identify ever-changing criminal activities, such as new ideas, concepts and schemes.
Loss prevention specialists, cybersecurity specialists and IT team members must all work together to create a system that complies with privacy issues and maintains heightened security to prevent any data breaches or disasters.
Development Of New Responsibilities
As retailers begin to shift from their brick-and-mortar stores (some even closing completely) to focus on e-commerce and m-commerce, the role of data loss prevention specialists will morph into something new, which encompasses more aspects involved in keeping a company safe and secure.
Businesses often turn to video surveillance to enhance security. In recent years, it has become a more feasible option for small businesses to employ cloud-based video surveillance due to lower costs and easy maintenance.
While some swear by the cloud, others are hesitant and worry about its security. If you are considering moving your video surveillance management to the cloud, you should get a better understanding of how it will work and how you can ensure that your data stays safe. Take these measures to ensure that your cloud-based video surveillance is as secure as it can get.
Is Your Hardware Secure?
Before you even think about cloud security, you must make sure that the equipment you have is free from security vulnerabilities. Do your homework and research different vendors’ reputation and history. Once you find a vendor you trust, make sure that your equipment is up-to-date with the proper software installed and in use. Maintain security by keeping your firmware current and using strong passwords. If your vendor has any other recommended best practices, be sure to follow them.
Because the definition of “cloud” can vary from vendor to vendor, make sure you know exactly what your vendor is offering. When it comes to cloud service for video surveillance, you should be provided with camera management and data storage in the cloud. Your media infrastructure and value-added services should be managed in the cloud as well. Beware of vendors who advertise a cloud service, but really only offer remote access to a local device. This can be beneficial, but is limited in comparison to real cloud services.
Learn More About The Cloud & Data Center
If your cloud provider’s solutions are rooted on well-known cloud servers such as Amazon, Microsoft, or Google, you can rest assured that their general security is adequate. However, if they are using their own proprietary data center, you may want to proceed with caution. While there are secure clouds out there, you don’t know for sure how secure theirs is.
It is much easier to track a well-known cloud provider’s track record. For example, the Amazon AWS data center is supporting some of the largest internet services in the world. Their data storage environment is designed to limit the loss of data objects and is set for “encrypted at rest” which means it is stored encrypted in the cloud.
Camera To Cloud Connection
You should always understand how your system works. When it comes to your cloud-based video surveillance, you should know how your camera connects to the cloud. There are three different types of connections:
When it comes to your cloud solution, we will deal with the first two options only. If you prefer no network configuration required, your available options will be limited, but viable. Some vendors offer a solution to configure your cloud cameras with no network configuration, while others have built-in direct connections for your camera to the cloud.
Beyond that, any other cloud solution is likely a P2P solution, which tends to be less reliable than other options, so be sure to research your camera and cloud vendors.
The other option is to configure your own network to permit access to your own device from the internet. This is technically called “port forwarding” and, if done correctly, can be completely legitimate and safe way to configure your cameras. If you choose this route, here are some tips to boost security.
Implement these measures and work with your network or IT person and you have an adequate way to configure your cloud video surveillance system. You will avoid any black box P2P connections while opening up a huge list of cameras you can use for cloud surveillance.
Cloud To User Connection
Now that everything is in order, find out how the cloud makes your data available to you through its web or mobile apps. All your data and video is under their control, therefore the traffic from the cloud to your web browser or mobile app should be strongly authenticated with username and password and encrypted in transit using TLS, including standard web traffic and video streams.
While other limitations may occur (ex. bandwidth capacity), security concerns should not hold you back from cloud-based video surveillance. As evidenced, there are smart ways to keep your cloud video surveillance safe and secure. If done correctly, cloud-based video surveillance can offer a better solution than local storage solutions.
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Despite how it may be depicted on television or movie screens, reviewing surveillance footage to find evidence is a lengthy process. Sifting through hours, sometimes days, of footage is costly, time consuming, and, when done by humans, is rarely effective. Luckily, advanced technologies can save the day.
Originally, CCTV video footage was used to monitor retail stores or businesses to prevent theft, damage, or employee misconduct, and provide evidence if something were to happen. If nothing occurred, the storage would be overwritten because space was limited and the footage proved useless.
These days, storage capacity has increased and new data processing techniques make this footage extremely useful. The accessibility of recording devices with advanced features is changing the value of videos. And thanks to machine learning and video analytics, surveillance footage can be sorted and evaluated in a timely manner.
Rather than wasting time and resources having humans evaluate footage, video analytics can take care of it. Video analytics is the process of extracting pertinent information from video footage. It basically works like image analytics, but goes a step further.
Image analytics can look at a still image to find patterns, anomalies, and identify faces. Video analytics can do the same, plus measure and track behaviors. Because of this, video analytics has a promising future within different industries.
The Use Of Video Analytics
Because this technology is great for identification, behavior analysis, and situational awareness, various businesses and industries can benefit greatly. Video analytics allows business owners to evaluate who visits their stores, identify peak hours, analyze customer behavior, and more. This gives businesses insight into how they can improve customer service and which deals or displays attract more customers. These types of insights can also benefit the marketing departments, as they can better understand customer demographic and tailor ads to those groups.
Video analytics can even be applied for security and law enforcement. Since body cameras for police are becoming widely adopted, these produce lots of video footage. Video analytics could make the recordings useful by adding rich tagging and indexing, making it easier to search through footage. Parsing through certain time periods and identifying persons with specific characteristics can help to develop leads and even recognize and predict different patterns.
For airports, stadiums and other major event and transportation venues, video analytics can evaluate footage and help to relieve congestion and lines. By monitoring these venues, more workers can be deployed to decrease wait times and improve customer service.
Video-Based Predictive Analytics
While still in the early stages, a new algorithm, as reported by MIT, allows a computer to predict human actions and interactions based on behaviors seconds before the action. The outlook for this algorithm is promising. As it develops, computers could eventually be taught to predict when a crime or injury may take place.
And as artificial intelligence (AI) and robotics become more feasible in our everyday lives, this type of machine learning and predictive analytics will be necessary for robots to interact with humans naturally.
An excellent example of these video analytics in action is Veenome for marketing. Its YouTube analytics tool helps advertisers choose which videos are better suited for them to display ads. Another example is Prozone for sports analytics. By analyzing video footage of the field, players’ stats can be recorded and more effective plays can be planned and executed.
These video-based predictive analytics can also help with decision-making in industries such as aviation, air traffic control, ship navigation, power plant operation, and emergency services. Accidents and crimes can be prevented, thus, potentially saving lives.
Video Gray Area
Of course, as it goes with all surveillance, privacy concerns arise. Currently, analytics where data collection does not require consent is still a gray area. Until laws are in place to protect the public as well as businesses, companies should consider employing video analytics ethically, with respect and privacy to the data and its consumers alike.
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While different types of biometric technology (ex. iris scanners, facial recognition) have been in the news, talk of artificial intelligence (AI), namely scene recognition, has mostly evaded the spotlight. If you are not familiar with scene recognition, it is basically a form of artificial intelligence that allows a device to categorize the features and objects in a photo or video much like our brains would. The process is comparable to the way Google Now or Siri comprehend voice commands, but with visual content instead.
To put the complexity of scene recognition technology into perspective, think about the many ways we can pronounce words and still be understood by a person or device. These possibilities seem minimal in comparison to the different shapes and positions a cat can assume and still be recognized as a cat, for example. This is just one of the many reasons why creating a scene recognition algorithm has been a long time coming. However, we are getting closer to its inception.
The first hints at this come in the form of the Nest Aware feature of the Nest Outdoor Camera. This feature can distinguish between humans and other things, such as a deer or butterfly or other natural phenomena, which may cause movement in a scene. This shows that cameras have the potential to sort useless parts of surveillance footage.
Security cameras with scene recognition could be very beneficial in different settings and scenarios. For example, scene recognition cameras could identify if a robber has entered your home, or, if you are keeping an eye on an elderly loved one remotely, you could be alerted if he or she has fallen. Because this technology takes motion detection much further, it can change the security and surveillance camera industry for the better.
Until scene recognition is more developed and refined, we likely won’t be hearing too much about it. Also, for those wary about surveillance already, having AI within the home may not be as comforting as it may be to others.
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Installing a surveillance system in your home or business can provide you with a sense of security. However, if you do not properly secure your system, cyber criminals can gain access to your video feeds.
Aside from an unnerving invasion of privacy, unauthorized access to your surveillance video can help criminals study the area, identify where important property is located, figure out traffic patterns, sabotage systems, deny access to feeds, and much more.
Because IP security camera systems connect to LAN networks, extra precautions are necessary to safeguard your system from attacks. Breaches are usually due to human error, negligence, and misconfigurations, and can often be prevented. The following are common vulnerabilities and ways to protect your surveillance system.
Default usernames and passwords are common with most IP based security cameras. They are used to set up your system and accounts for remote access. Too often, people fail to change these passwords, or choose simple passwords, making it easy for strangers to access feeds.
Be sure to set strong passwords, use good password management or user certificates in lieu of passwords. You may want to consider changing your password periodically as well.
Avoid enabling unused services as it can leave your system vulnerable to attacks. For example, cyber criminals could install malicious applications and scripts using file transfer protocol (FTP) or an app platform from an untrusted developer.
Minimize your risk by disabling any unused services and installing only trusted apps.
Sometimes organizations fail to define who has access to different aspects of the surveillance system, possibly leading to confusion and employees with unnecessary access. For example, it may be unclear as to who is responsible for reviewing security measures to ensure proper protocol is being followed.
For IT departments, it is recommended to only allow users access to the resources they need to perform their job.
Bugs and flaws in software codes can put your devices at risk. Luckily, you can do your part to prevent this.
Always keep your cameras, equipment, and software up-to-date with the latest firmware to ensure that bugs will not pose a threat. Vendors often post public common vulnerabilities and exposure reports which provide solutions for users.
Physical Installation Problems
Whether it is your cameras, wiring, or other infrastructure, poor installation can leave your system at risk.
Cameras should be installed out of reach to avoid any possible tampering or vandalism, but at a proper angle to view people and objects clearly.
Poor Physical Protection Of Equipment (Cabling, Servers, Gear)
If your cabling, server, or other surveillance equipment is not properly protected, your system is at risk for poor, intermittent performance. A small kink or damage to a cable can interfere with signal, causing disruption in your feed or even power failure.
Appropriate housing to protect your equipment from severe weather or extreme heat is available and is recommended for use if you are in an area susceptible to these conditions.
Routine maintenance is ever important to ensure that your system is and will continue to function properly.
A preventative maintenance program should include a checklist of issues to look for in order to avoid small issues that can turn into big problems (ex. damaged/loose cameras and equipment, exposed, loose, or damaged cabling, dirt/moisture on camera lenses). This will allow the owner to become accustomed to the system and more aware when something seems different or wrong (ex. possible signs of tampering).
Flaws In Standard Network Protocols
Most network surveillance systems use standard network protocols (ex. FTP, TCP/IP), however, weaknesses or flaws in these protocols can expose surveillance data to attacks.
For video streams sent over the network, the latest advanced encryption methods should be used.
Failure To Align Hardware/Software On The Network With IT Policy
If your hardware or software does not meet your IT organization’s network security policy, there will be security issues. For example, third-party software or apps are often poorly supported or lack security patches which make them vulnerable to security breaches. Thus, your IT department will not be happy.
Enforcing a strong IT policy is imperative for any business.