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30/05/2018

‘Internet-connected ones in city are prone to malware attacks’

The presence of CCTV cameras can make you feel safe, but how safe are the equipment itself?

Even as the State government has announced its plans to install 5,000 CCTV cameras in the city, cyber security experts claim that data from the existing Internet-connected CCTV cameras in the city are prone to malware attacks and resource theft has been happening for the past many years.

According to N. Vijay Shankar, a cyber security expert, this is mainly because of the weak passwords retained by the users.

“There are search engines which can monitor the active CCTV cameras and those that are vulnerable to dropping viruses such as the Mirai and Botnet. We found that the cameras in Bengaluru are very vulnerable,” he said.

Lt. Vineet Kumar, founder of National Anti-Hacking Group, a group of ethical hackers and cyber security experts, said that in 2012, a command and control server, used to steal data from various internet connected devices, including CCTV cameras, was detected in Bengaluru. “We even alerted the Karnataka police about this. Now even smart TVs and refrigerators are being hacked across the country. Bengaluru is one the prime targets as it is developing faster and becoming a smart city at a rapid pace,” he said.

The hacker gets access into the CCTV footage and then either uses it to facilitate a Distributed Denial of Service (DDoS) attack by sending the huge data from the Digital Video Recorder (DVR) to the target server.

“For example if an e-commerce platform has a discount sale coming up, the hackers of rival companies can bring the site down by flooding its server with images. One of the malware most commonly used is Mirai,” said Mr. Vijay Shankar.

There are different methods through which a hacker can get access to the DVR, including hacking into the phone through which CCTV is monitored. “However, the most common mistake is a weak-password or retaining the one issued by the company that installed the equipment. Through multiple combinations, a hacker can crack the password,” said R. Nandakumar, president, Electronic Security Association of India.

Pavan Duggal, a Supreme Court lawyer specialising in cyber law, said that he has seen a few cases from Bengaluru pertaining to CCTV hacking.

“People are not aware about cyber security of these equipment. Their cyber protection is very poor,” he said, recalling a recent case of an employee of a private company hacking into his company CCTV storage device to delete a footage of him stealing.

However, city police commissioner Praveen Sood, said the cameras installed by them are safe. “They have different layers of protection,” he said.

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30/05/2018

Corporate News
How Recognition can Prevent Crime and Improve Security
May 15,2018
Hikvision Facial Recognition

Why Facial Recognition?
Public security threats along with increasing security demands from users continually pressure security manufacturers to create ever improving technologies. International news constantly peppers the public consciousness with reminders of present dangers. The public wants to know – can these events ever be prevented?

For everything from safe city projects to home protection, developments are underway all over the world, with their relative obstacles. Safeguarding family members, homes, property, and vehicles are the most common applications using these emerging technologies. But the number of video surveillance cameras used in any given application, with their various networks and demanding resolutions, has increased dramatically with an equal increase in challenges. An ability to fast-track through oceans of data to find the small amount that is actually critical is now in high demand.

On the security side of video intelligence technologies, increasing customer safety has been the primary driving factor. On the business side of video intelligence technologies, increasing customer satisfaction has been the primary driving factor. Here, both service and safety are critical. Facial recognition technologies will not only address these issues, but will improve on our abilities to overcome the challenges involved. More than just speed up or enhance current methods, facial recognition will open up new avenues for security and new realms of data wherever it’s needed.

Security Industry Difficulties & Requirements
Identifying suspects during post-event investigation poses many complicated difficulties. Challenges include everything from reviewing footage from scores of cameras, comparing two face images of the same person with a 10-year age gap, and extracting the 5% (or less) of useful information from massive amounts of data, to implementing pre-event alarms to prevent incidents and managing increased video storage challenges due to increased resolutions. And likely a lot more, too.

These obstacles can prove paralyzing for standard video surveillance systems, even with up-to-date equipment. The sheer amount of information being processed bogs down system hardware. This is where more data-heavy solutions are needed, precipitating the development of deep learning and artificial intelligence products. Along with those new technologies, facial recognition is undoubtedly one of the most important right now.

Common Insufficiencies in Facial Recognition Solutions
Conventional intelligent video surveillance carries very strict requirements for a scene’s background. For human facial recognition process, two key steps are required. The first one is Feature Extraction, where the features are designed by humans and are always subjective. This method performs well in very specific environments, and subtle changes in lighting, environment, etc., sacrifice accuracy. The second step is “Classification Learning”, which uses shallow learning and analysis. Far from ideal, the results here directly restrict the breadth and depth of intelligent applications.

Deep-Learning Benefits for Intelligent Video Surveillance
Deep learning is intrinsically different from other algorithms. The way it solves the insufficiencies of traditional algorithms is encompassed in a few concepts.

First, From “Shallow” to “Deep”
The algorithmic model for deep learning has a much deeper structure than that of traditional algorithms. Sometimes, the number of layers can reach over a hundred, enabling it to process large amounts of data in complex classifications. Deep learning is very similar to the human learning process, and has a layer-by-layer feature-abstraction process. Each layer will have different “weighting,” and this weighting reflects on what was learned about the images’ “components.” The higher the layer level, the more specific the components. Simulating the human brain, an original signal in deep learning passes through layers of processing; next, it takes a partial understanding (shallow) to an overall abstraction (deep) where we can perceive the object.

Deep learning from shallow to deep


Second, From “Artificial Features” to “Feature Learning.”
Deep learning does not require manual intervention but relies on a computer to extract features by itself. This way it is able to extract as many features from the target as possible, including abstract features that are difficult or impossible to describe. The more features there are, the more accurate the recognition and classification will be. Some of the most direct benefits that deep learning algorithms can bring include achieving comparable or even better-than-human pattern recognition accuracy, strong anti-interference capabilities, and the ability to classify and recognize thousands of features.

From artificial features to feature learnings

With deep learning technology, the average accuracy of facial recognition increases significantly. Hikvision has demonstrated its ability to advance ahead of the competition. Its advantages in Artificial Intelligence in security have come about by having its own excellent algorithm development team and using the most powerful GPUs in our computer platforms. The results include winning in multiple International Deep Learning algorithm competitions, such as ImageNet, PASCAL VOC, the MOT Challenge, and more.

Achieving the best results come from a combination of having the right hardware and developing algorithms that can perform the computational requirements. Hikvision has the industry's first data computing platform with best-in-class hardware, and completely independent algorithm team.

Hikvision’s Facial Recognition Solution
Hikvision’s Facial recognition Solution pushes the limits of what is possible with today’s advancements in recognition abilities. This solution detects human faces and recognises attributes create pre- and post-event face contrasting. With immense capabilities for data storage behind this solution, Hikvision’s Face Library can generate blacklists and whitelists to trigger alarms and automate entry and exit authorizations in a range of applications.

Hikvision embeds its algorithms DeepinView Facial Recognition Camerawithin the cameras and recorders, so no PC server is needed. This means less delay in transmission, decreasing the burden on back-end devices. More than just efficiency, Hikvision holds a high success rate – the face-capture rate can reach 95% accuracy, with face-comparison accuracy rate up to 98%1 . Multiple models and types are available, with a wide variety of front-end or back-end combinations to meet multitudes of scenarios and environments. And with world wide support, all human faces are supported2.

Systems integrators will see a wide range of applications becoming possible with this facial recognition solution. It can be applied in banks, luxury shops, and hotels, to recognise VIP customers and initiate specialised services. Hikvision’s solution can be applied in security scenarios, like police stations, customs, international airports, government installations, and much more, to improve security and investigation efficiency.

1Based on controlled tests; the facial recognition engine requires face images with minimum 40 pixels between the subject’s eyes (“inter-pupillary” distance), preferably 60 to 300; the maximum pan and tilt angles are 25 degrees and 15 degrees respectively for facial image capture.
2At the time of this writing, faces fitting characteristics of Asian ethnicities have the highest degree of accuracy.

Learn more about How Deep Learning Benefits the Security Industry

Other recommended articles:
Technical article – Reducing false alarms with Deep Learning
Hikvision’s Deep Learning Technology in Smart Retail Solution


# # #
About Hikvision
Hikvision is the world’s leading provider of innovative video surveillance products and solutions. Featuring the industry’s strongest R&D workforce, Hikvision advances core technologies of audio and video encoding, video image processing, and related data storage, as well as forward-looking technologies such as cloud computing, big data, and deep learning. In addition to the video surveillance industry, Hikvision extends its reach to smart home tech, industrial automation, and automotive electronics industries to achieve its long-term vision. Always creating value for its customers, Hikvision operates 37 regional subsidiaries all over the world to achieve a truly global presence. For more information, please visit us at

13/11/2015

13/11/2015

Kerala HC directs all colleges in the state to install CCTV in Exam Halls [Read Judgment]
By: Ashok KM | November 12, 2015

The installation of CCTV cameras would certainly act as a deterrent for a student to indulge in the mal-practices for fear of being detected eventually, the Court observed.

High Court of Kerala has asked the Education department of the state to install CCTV cameras in the examination halls of the colleges to function during examination hours before June, next year. According to Justice V. Chitambaresh, the installation of CCTV cameras would act as a deterrent for a student to indulge in the mal-practices aforesaid for fear of being detected eventually.

Kerala Self-Financing Engineering College Managements Association and All Kerala Private Arts and Science Unaided College Management Association had approached the High Court challenging the order by University to install CCTV camera in Exam halls in Private colleges. They contended that particular brands of CCTV cameras are being insisted and that self-financing institutions alone have been targeted.

CCTV deters malpractice

The Court observed that the necessity toinstall CCTV cameras in the examination halls has arisen in view of the reporting of rampant copying during the examinations. The court said that the students may perhaps misuse the liberty given by the invigilators and indulge in impersonation or copying from bits and score high marks. The students who take pains to study and write the examinations without indulging in such malpractices would end up getting lesser marks much to their disgust and frustration. The court also added“alleged copying during examinations by a high ranking officer sparked controversy recently”

The court, however clarified that such CCTV cameras shall not function during class internals or viva voce even though the same may be insisted for the external examinations. The privacy of the students and the staff are infringed by continuous use of CCTV, the court said. “The external examinations conducted by the university should be free from all mal-practices and one of the remedies is the installation of CCTV cameras. Such surveillance is necessary only in the examination halls”, Justice Chitambaresh said.

University duty-bound to check malpractice

The court observed that the Universities are duty bound to conduct the examination free from all mal-practices including copying. Rejecting the contention of the petitioners that contention of the petitioners that the university lacks power to issue instructions to install CCTV cameras, the court said such power can be traced to Section 5 (xvii) of the Mahatma Gandhi University Act, 1985. The court further pointed out that the conduct of the examinations in a fair manner will certainly add to the impetus to study for a student thereby enhancing the quality of the course itself.

CCTV not just in private colleges

The court said that petitioners are justified in their complaint that the private institutions are only asked to install CCTV, because such malpractices have been reported even in the aided colleges affiliated to the university. Court said that the Government colleges are not free from the menace of malpractice during examinations.

Instead of quashing the directions to install CCTV in private educational institutions, the Court said it will rather direct all the colleges in the State (whether it be self-financing, aided, unaided or Government) to install CCTV cameras. Justice Chitambaresh said “The only remedial way is either to do away with installation or do the installation in all colleges and I opt for the lattertaking note of the social commitment.”