Security & Alarm Services


Singapore's RoboCop car has its own intruder-chasing drone

Engadget

If RoboCop has a gun in his thigh, this robotic security car from Singapore has a drone that it can send after intruders. It has 3D LIDAR sensors and GPS, along with other instruments that it uses to spot unattended bags and to differentiate between employees and intruders. It can differentiate the people security personnel mark as employees from unknown individuals. O-R3, he says, can complement human security personnel hired for jobs that require a higher level of skills.


Can artificial intelligence help thwart ransomware?

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Last week, the WannaCry ransomware attack crippled their network -- one report suggested people with life-threatening injuries were told not to come to the hospital. In the future, security systems could use artificial intelligence to monitor user behavior, track activity, suggest when there may be a danger and even mount an attack against the ransomware purveyors, effectively rendering the deadly malware client inoperable. Raja Mukerji, the cofounder and Chief Customer Officer at ExtraHop Networks, equates how an AI can block ransomware to how airport security stops people from using water bottles. A new technique using AI in airport security would not block all water bottles.


Can AI save us?

FOX News

Last week, the WannaCry ransomware attack crippled their network -- one report suggested people with life-threatening injuries were told not to come to the hospital. In the future, security systems could use artificial intelligence to monitor user behavior, track activity, suggest when there may be a danger and even mount an attack against the ransomware purveyors, effectively rendering the deadline malware client inoperable. Raja Mukerji, the cofounder and Chief Customer Officer at ExtraHop Networks, equates how an AI can block ransomware to how airport security stops people from using water bottles. A new technique using AI in airport security would not block all water bottles.


New AI technology reads emotions of potential terrorists

Daily Mail

A Russian firm has created software that can be embedded in CCTV cameras to track the age, gender, emotional state and identity of people and keep track of suspicious behaviour. NTchLab's software, which can be used in CCTV cameras, claims to read people's emotional states and will know if they might be about to do something dangerous (stock image) NTechLab has created a tool that can track the age, gender, emotional state and identity to monitor citizens and keep track of any suspicious behaviour. This is a sophisticated form of facial recognition technology which identifies people by analysing the shape of a person's face. This emotion reading technology is the latest offering by NTechLab, a Moscow-based company which monitors suspicious behaviour by looking at people's emotional state.


NVIDIA's AI may keep watch over smart cities of the future

Engadget

Video surveillance could the next step if NVIDIA's new video analytics platform, Metropolis, is successful. The initiative, announced just ahead of the annual GPU conference this week, will use learning AI to analyze the massive amount of data from surveillance video for "public safety, traffic management and resource optimization." NVIDA thinks that deep learning AI can help video analytics much more accurately than humans or even real-time computer monitoring. "The benefit of GPU deep learning is that data can be analyzed quickly and accurately to drive deeper insights," said Shiliang Pu, president at the Hikvision Research Institute in China.


Video scanning technology is being transformed by machine learning

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Its video processing software can identify objects and scenes in video and provides a timeline so you can jump to the place a certain element appears at a speed much faster than the human eye. Another company named 3VR is already operating in this segment of video surveillance and intelligence using machine learning techniques. The IBM Watson Visual Recognition Service uses machine learning CNN algorithms to analyze and understand the content of images and video frames. The IBM Watson Visual Recognition API allows images to be uploaded in a programmatic way to the system, then analyzed against the labels specified.


Crime fighting robots could soon replace security guards

Daily Mail

They are designed to function without any human control and are built with surveillance cameras, sensors, odour detectors and a thermal imaging system. They also have scanners that can read an impressive number of 300 car registration plates every single minute. They are designed to function without any human control and are built with surveillance cameras, sensors, odour detectors and a thermal imaging system. They also have scanners that can read an impressive number of 300 car registration plates every single minute.


Artificial Intelligence and Machine Learning: Cybersecurity Advances

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Could adding AI techniques to machine learning help deal with the high volume of data that most security teams have to prioritize? Or is it a step closer to Skynet? Some companies are adding in AI techniques as a way to reduce the noise that traditional security products produce.


Q&A with Balabit: Artificial Intelligence - the future of IT Security

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Increasing computing capacity, especially via affordable cloud computing and easy-to-use tools, made it possible for a much wider range of users to apply sophisticated machine learning and AI algorithms to solve their problems. The first is that most AI and machine learning solutions are self-adapting and require little customisation and maintenance. At the same time, it lowers maintenance costs significantly. Do you see AI being the'next big thing' in the cyber security industry?


Repurposing 1980s traffic systems for artificial intelligence

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Video monitoring systems for traffic have been in use since the mid- 1960s, initially pioneered by Israel and the Netherlands in order to capture motorists violating traffic light regulations. In terms of information that such images provide to machine systems, this means that the rear-most cars in a traffic jam may not occupy more than five pixels – an object-recognition challenge that seems science-fictional at the current state of the art. The economies of scale in existence at the time these legacy networks were created are another challenging factor, since the low frame rate of video capture (sometimes as little as one frame every 2-3 seconds) that they are set at makes it difficult to continuously evaluate individual vehicles, and maintain some understanding of ongoing traffic flow. The researchers have adapted to these challenges by formulating individual approaches to each pixel sector of the legacy feeds, with highly creative approaches to perspective-based clustering, that promises to yield some consistency in traffic evaluation from systems which were not designed to provide this information.