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iirisconsulting · 1 year

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Celebrating 8 Years of Excellence and Innovation - IIRIS Consulting

Celebrating 8 Years of Excellence and Innovation - with infinite dreams in our eyes 📷📷

Today marks a very special milestone for us, as we're proudly celebrating our 8th anniversary! 📷📷 It's been an incredible journey filled with growth, achievements, and unforgettable moments. We couldn't have reached this point without the unwavering support of our amazing team with exceptional deliverables, and valued clients. Thank you for being a part of our success story! 📷📷

📷 As we reflect on the past 8 years, we're filled with immense pride and gratitude for the milestones we've achieved. It's the dedication of our team and the trust of our clients that have propelled us forward and made our journey so rewarding. We are truly honoured to have been a part of your lives and businesses. 📷📷

📷 Today, we recommit ourselves to the values that have guided us from the beginning – innovation, integrity, and excellence. We look forward to the future with optimism and great excitement, as we continue to evolve, grow, and make a positive impact in the lives of our clients and the business we serve. 📷📷

📷 Join us in celebrating this momentous occasion! 📷 Share your favourite memories, achievements, or experiences with us using #iirismilestone #iiris #iirisconsulting #infinitedreams

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iirisconsulting · 1 year

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Brand Protection Services in Gurgaon

IIRIS brand protection steps in to resolve and address the growing concern amidst corporates pertaining to their proprietary assets. Armed with experienced investigation and technological equipment. IIRIS offers asset protection across domains of piracy, counterfeit and pass offs.

Enforcement & Litigation Support

Brand Protection Strategies

Anti-counterfeiting

Verifications

Trademarks

Law Enforcement

Brand Due Diligence

Targeted Investigations

Intellectual Property Rights

Copyrights

Market Research

Supply Chain Audits

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iirisconsulting · 1 year

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INDIA IPR- ENFORCEMENT DIGEST Edition- March 2023

It is well known how improper management of everyday waste is impacting us badly.

One of the major problems is that it is leading to economic disbalance as well, as it is also harming the business and its brand health.

The IPR-Enforcement Digest explains the correlation between the hidden aspects of waste and the rise of counterfeiting as pressing concerns and why it is crucial to manage waste properly through strategies and to raise awareness in the present time.

Additionally, we are sharing the details of raid actions that happened in the month of February 2023 in India as well.

This monthly digest is produced by IIRIS Consulting Pvt. Ltd. with the aim of providing data, trend analysis, articles, new initiatives, etc. on a monthly basis.

By gathering intelligence regarding IPR enforcement actions in India and conducting trend analysis, this study highlighted the magnitude of the problem and the corrective action taken by law enforcement agencies to deter this crime of counterfeiting.

We welcome comments to improve the endeavour. There is always additional data, and do reach out to the editorial team in case you need something customized.

Let's keep fighting the counterfeiters.

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iirisconsulting · 1 year

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INDIA IPR- ENFORCEMENT DIGEST Edition- Feb 2023

Digital platforms have become an integral part of our lives, leading to the question of whether traditional marketplaces are becoming redundant. Fake websites and physical store branding can have similar effects on a brand's image, so companies need to pair these physical elements with digital solutions that offer not only protection and security, but advanced marketing capabilities.

This monthly digest is produced by IIRIS Consulting Pvt. Ltd. with an aim to provide data, trend analysis, articles, new initiates etc on monthly basis.

By gathering intelligence regarding IPR enforcement actions in India and conducting a trend analysis, this study emphasised the magnitude of the problem and highlighted the corrective action taken by law enforcement agencies to deter this crime of counterfeiting.

We welcome comments to improve the endeavour. There is always additional data and do reach-out to editorial team in case you need something customised.

Lets keep fighting the counterfeiters.

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iirisconsulting · 1 year

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INDIA IPR- ENFORCEMENT DIGEST Edition- Jan 2023

India has unique impacting factors for IPR enforcement – multiple layers of laws, different enforcement agencies, poor conviction rate and low awareness. Surely the criminal action route is higher deterrent when it comes to stop sale of illicit goods. The number of enforcement actions and the amount of seizure brings a good assessment of impact of the enforcement action.

Surely, the presence of supply chain inputs, manufacturing machinery and packaging material at site brings additional impact as well as intelligence. Due to lack of compiled data it is extremely complex to envisage actual impact and also conduct any kind of trend analysis. IIRIS with large base of knowledge and spread in India, is initiating a new endeavour – INDIA IPR ENFORCEMENT.

This monthly digest will provide data, trend analysis, articles, new initiates etc on monthly basis. We welcome comments to improve the endeavour. There is always additional data and do reach-out to editorial team in case you need something customised.

Let’s keep fighting the counterfeiters.

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iirisconsulting · 1 year

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Know more about our leadership — Brig Neelesh Bhanot

Brig Bhanot is an accomplished intelligence expert with ability to navigate complex situations with his strategic agility and operational precision. As he takes over this new role we wish him the best and are confident that IIRIS will gain newer heights under his leadership.

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iirisconsulting · 1 year

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REID TECHNIQUE APRIL, 2020, MUMBAI

The Reid Technique of Interviewing and Interrogation® For Loss Prevention and Corporate Security Personnel is a four-day workshop specifically designed for corporate security, loss prevention, asset protection professionals, auditors and human resources personnel.

Every year, thousands of individuals from business, law enforcement, and government organizations utilize the services of John E. Reid and Associates for law enforcement training programs, and their products to help them:

Develop interviewing & interrogation skills

Conduct investigations

Select new employees

During the first three days, participants will learn The Reid Technique of Interviewing and Interrogation, widely recognized as the most effective means available to exonerate the innocent and identify the guilty. The workshop is based on the basic tenet of the Reid Technique, as taught by John E. Reid and Associates, that a custodial suspect must be advised of his rights prior to any questioning about a criminal act. The third day is designed to build on the information learned and particular emphasis is placed on how to elicit information from the suspect during the interview stage that will serve as the basis for developing an individualized interrogational approach, based on the suspect’s profile and characteristics.

Without exception, past participants have commented on the value of the advanced techniques learned which give them a better understanding of the interrogation process, and allow them to enhance their skill level by learning new techniques and tactics. Information is the most valuable resource for any professional that has to solve problems, make decisions and identify and select talent. Getting to that information is not an easy task especially when you have to extract it from the minds of others.

The Reid methodology is a tried and tested method that enables professionals to extract that type of high value information effortlessly. The techniques on which it is based stem from the field of law enforcement and security but have also been effectively applied to areas such as human resources especially when recruiting for positions of trust for businesses, law enforcement and government agencies and also when conducting disciplinary or audit processes.

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iirisconsulting · 1 year

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Quad-ASEAN Defence Exchanges On The Rise

The Malabar Quad exercise will take place in September of this year. For the second consecutive year all four Quad countries will participate.

An Indian task force of 4 ships from the Eastern Naval Fleet are already on a two-month voyage through the South China Sea (SCS) and Western Pacific where the Malabar will take place. The group comprises guided-missile destroyer Ranvijay, guided-missile frigate Shivalik, anti-submarine corvette Kadmatt and guided-missile corvette Korea.

Besides Malabar, they will carry out bilateral exercises with the navies of Vietnam, the Philippines, Singapore (SIMBEX), Indonesia (Samudra Shakti) and Australia (AUS-INDEX). They visited Brunei before proceeding to Guam for the Malabar21.

All the Quad countries have recently (2-6 August) participated in the EAS, ASEAN+1 Ministerial meetings as well as the meeting of the ASEAN Regional Forum (ARF), the main forum for regional security architecture.

The Quad recognise that in the Indo-Pacific, particularly in the SCS, it cannot afford to be facing a hostile China and neutral ASEAN member states. Their buffer has to be more responsive than hitherto. The revitalization of US policy towards the ASEAN could be seen in this context.

The SCS and the Indo-Pacific is seeing an increasing level of activity from the Quad. They are engaging the ASEAN member states more. This has to take into account that China is certain of its control over the SCS and is focusing on Taiwan. China regularly breaches Taiwan’s ADIZ and has deployed both its aircraft carriers with full battle groups around Taiwan. The Chinese are using their occupied island territories in SCS with increased capacity of missiles and now aircrafts. At present, China has the capacity to deploy as many aircrafts as on an aircraft carrier on these Island bases at one time.

Therefore, the US and its partners realise that a single carrier battle group (CBG) would be inadequate to deal with the Chinese strength based off these Islands. At least two CBGs would be required in the Indo-Pacific. The USS Reagan led CBG, from Yokosuka, was deployed to help in the evacuation from Afghanistan and could return soon. It supported the 5th Fleet’s USS Dwight D Eisenhower and its CBG , which have been in the area since April 2021. The CBG led by USS Theodore Roosevelt has also returned to the SCS. If the Indo-Pacific Command is to be more effective it needs to constantly deploy 2 CBGs. The visit of the UK CBG may be partly seen in this context.

Another notable point is that the US scrambled out of Afghanistan and may reduce its involvement in West Asia. The exit from Afghanistan could allow more leeway for releasing periodic CBG deployment under CENTCOM to the SCS and Indo-Pacific.

The US is aware that ASEAN as a whole has been slow in re-engaging them for a joint exercise. The first ASEAN-US maritime exercise was held at the Sattahip naval base in Thailand in September 2019. It passed through Singapore and concluded in Brunei. About 1000 people representing all 10 ASEAN member states and the US promoted a shared commitment to maritime security and stability in Southeast Asia. This included all ASEAN countries including Chinese allies like Cambodia and Laos. Though this was the result of a proposal at the ADMM-US meeting in 2017 and 2018, it has not recurred because of sensitivities towards China and lack of unanimity among ASEAN members. A China-ASEAN exercise of 2018 has also not recurred.

The three ASEAN countries which US Defense Secretary Austin visited recently, undoubtedly have strategic importance. Singapore, for example, is a key port for the US 7th Fleet, playing a significant role in providing logistic support for military aircraft and ships. Vietnam and the Philippines directly confront China over their respective territorial issues in the South China Sea.

Through such efforts, the US has enhanced its engagement with individual ASEAN countries. In April 2021, the Philippines and the US conducted the 36th Balikatan exercise held since 1991. It now has an Indo-Pacific dimension. It was held despite the pandemic with reduced participation, tabletop exchanges, training, real time security training, and similar activities.

A significant result of Secretary Austin’s visit to Philippines was the decision to hold off on the abrogation of the Visiting Forces Agreement, the basis of the US Philippines arrangement for military bases

The US-Indonesia Garuda Shield exercise is another annual exercise for more than a decade. Held in August, it covered the large outlying islands of Indonesia, including Kalimantan, Sulawesi and Sumatra. Over a fortnight it involved amphibious, special forces and airborne units. In June 2021, Indonesian and US Marines conducted joint exercises focusing on conflicts in urban locations and are scheduled to do another exercise in the US later this year. US and Indonesia are constructing a joint maritime Training Centre in Batam, a small city on an island near the Malacca straits and close to Singapore. The US tries to solidify the US-Indonesia Major Défense Partnership and cooperation in support of a free and open Indo-Pacific (FOIP) region.

Thailand manifests the American dilemma in dealing with ASEAN. For several decades, Thailand and the US had a mutuality of interests as Thailand saw the US as a support against Chinese and Vietnamese influence in the region. Thailand, now having abandoned its democratic credentials, its military regime is more inclined towards engaging China and sees it as an uncritical partner. Due to their domestic issues and accommodation with China, Thailand does not have a strategic interest with the US; its main challenge is democracy, not China. The US has reduced financing for Thailand’s arms purchases following the coup in 2014.

This dilemma over democratic rights, economic assistance and proximity makes the US rethink its ASEAN engagement. Thus, traditional allies like Thailand and Philippines become ambivalent whereas old enemy Vietnam is a strategic partner.

During July 2021, Australia and Japan with eight other countries held joint exercises around Australia. This was preceded by the Australia-US, Talisman Sabre exercise. It was later joined by Japan, UK, Canada, South Korea and New Zealand. India, Indonesia, Germany and France sent observers. This combined exercise would further strengthen the FOIP.

The traditional ASEAN policy of outsourcing its security requirements mainly to the US was challenged when China became more aggressive and the US pivot to Asia did not happen under the Obama administration. During the Trump period, ASEAN was not a priority for the US. Under the Biden administration, the Indo Pacific and the Quad have a much higher priority.

Thus, the three-pronged policy recognises that China is the main factor and ASEAN has accommodated it, particularly in the economic sphere. The US wants to reengage with ASEAN and select member states. For this it prefers the regional architecture, to provide space, and a buffer between China and its rivals.

Increasingly the ASEAN buffer was inclining towards China. Now, efforts are made to restore the balance within that space particularly on the security and functional side. Undoubtedly for this to happen ASEAN member states also have to play a role.

ASEAN unanimity is now passe. When Cambodia takes over the chair for 2022 it is likely to play its pro-China role that it did in 2012. Hence, engaging ASEAN, praising its centrality and not giving up on it, is part of the policy.

A third prong of the policy of the US and other Quad members is clearly to engage with willing ASEAN member states who have greater strategic value. In this, Singapore, Indonesia, Vietnam, and Philippines are the main partners. Thailand, Malaysia, as well as Myanmar, due to their internal situations are not forthcoming. Such ‘ASEAN Plus’ policies from individual member states are small steps.

In my view this effort to deal with specific member states have increased their security and functional support for instance in fighting the pandemic. This could be viewed more vigorously by the US and its Quad partners. With this objective in mind, the significance of defence engagement of the US, the EU countries and the UK, with ASEAN countries certainly have greater significance as well.

Author

Written by Mr. Gurjit Singh

Ambassador Gurjit Singh is an advisory leader at IIRIS Pvt. Ltd.

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iirisconsulting · 1 year

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Artificial Intelligence in Security

In the late 1970s, academics and industry has worked on the subject of AI and with the advent of numerous connected networks and big data, Neural Networks and Deep Learning have emerged as key application areas of AI based. Last 24 months have been interesting for the Security Industry with new age technologies such as Artificial Intelligence, Machine Learning and Machine Vision making mainstream appearances; products getting smarter & sophisticated; and the overall adoption roadmap of these technologies seems much wide spread now than ever.

The growing number of companies innovating in AI applications for physical security is a clear indication that these are more than a passing phase.

These technologies have been identified as ‘Exponential Technologies’ as technology for which performance relative to cost and size is doubling every year.

The concept of Artificial intelligence is not new at all. It has been at the core of our smartphones since the last five years in the form of Siri, Alexa and Assistant (for Apple Amazon and Google environments respectively). For that matter, let’s go back a decade: ‘Text to Speech’ is a classic example of consumer genesis of AI.

This ‘Natural Language Processing’ will go beyond just speaking into the phone and resulting in typed text, rather these smartphones and other similar devices will even understand what has been entered. With smart elements such as smart tagging, key word identifying and geographical tagging: these systems will correlate the inputs and provide a better topic identification. A sentence such as ‘someone forced entered through main door’ will not be read just the way it sounds according to the English language, but these machines will apply the technology to decipher the outcome / output result by identifying it to be an ‘act of intrusion’.

A major deep learning breakthrough occurred in 2015, which radically reduced the machine vision error rate. During a machine-vision competition, a large visual database designed for use in visual object recognition software research - succeeded for the first time in surpassing the five percent average human error rate, when analyzing a database of images. Such a rapid enhancement was caused not only by progress in advanced algorithms, but also by the development of new and much faster hardware systems based on graphics processing unit (GPU) cores, instead of traditional central processing units (CPUs). These new marriage of hardware and software architectures allowed for faster learning phases.

Understanding these Technologies

Artificial intelligence (AI) is the body of science, algorithms, and machines that are able to perform some version of learning and independent problem solving, based on advanced software and hardware components. Data is core to AI; large datasets are the foundation for recent performance improvements across market applications. Within the AI subject field there are other sub-fields such as machine learning, neural networks, and deep learning.

Machine Learning involves collecting large amounts of data related to a problem, training a computer using this data and employing this model to process new data. Deep learning, which is a branch of Machine learning, is a way to emulate the functions of the human brain using software algorithms.

With deep learning, you can show a computer many different images and it will “learn” to distinguish the differences. This is the “training” phase. After the neural network learns about the data, it can then use “inference” to interpret new data based on what it has learned. For example, if it has seen enough cars before, the system will know when a new image is a car.

For this to happen, the system “learns” by looking through large volumes of data that need faster processing time to achieve artificial intelligence (AI). This is where Graphic Processing Unit (GPU) comes in, and is making artificial intelligence accessible to the security industry. By improving surveillance efficiency and accuracy with AI during the course of time - the technology is already being added to existing cameras to more efficiently search for objects or persons of interest. In surveillance applications, AI could eliminate the need for humans to do hard laborious work such as look at hours of video footage.

A system relying on neural networks differs from conventional pattern-recognition systems, in that it will continuously learn from experience, and base its ability to discern and recognize its surroundings like human beings do: by learning from real sounds, images, and other sensory input.

Enabler of Competitive Advantage

In the recent past, the usage of machine learning – primarily in the applications for image processing and natural language processing, machine translation has exploded in the industry and allied sectors. Most of these capabilities are based on open-source libraries, and can be deployed easily and rather cost effectively in the cloud or distributed cloud – the entry barriers are on an all-time low and is on the rampant decline further. This will always give way for product and services innovations and the benefits will be beyond standard automation based tasks.

The proliferation of these technologies have especially resonated with the c-level business leaders who have embraced these in order to differentiate themselves from competitors.

As per a recent study conducted – 45% of businesses have deployed these technologies in the financial sector that are core to their business and about 10% are still experimenting – thus taking the overall count to more than 50% of the total businesses who are leveraging these technologies at some level.

Let’s take financial and human capital organisations for example – the adoption of AI and ML lies in the motivation to saving money – where in these technologies cut costs and increase productivity by a factor of billions of dollars. However, the main focus of these technologies over a period of time is well timed and informed decision making. About 60% organisations use it to drive decision making – and data is at the core of all of this. Any innovation that makes better use of data, and enables data scientists to combine disparate sources of data in a meaningful visualisation that could have the potential to gain competitive advantage. The areas where these are used are: Risk Management, Performance Analysis & Reporting, Ideation and Automation.

The key adoption drivers are to these are: Extract better (read ‘meaningful’) information, increase the pace of productivity, reduce overall operating costs and extract more value from data available (or data mined).

AI and the Security Industry

AI, ML and Deep learning technologies offer a much higher level of accuracy and reliability to recognise an object or behaviour, and accurately classify significantly higher than the traditional / conventional rules-based algorithms.

New age algorithms make deep learning solutions to view a scene as intuitively as a human being. The ability of deep learning algorithms to view a scene intuitively, as a human viewer would, means that detection accuracy increases dramatically. Neural networks allow a computer to apply a series of algorithms to a given situation learning to identify increasingly more sophisticated features such as shapes, colors, tones, textures - unlike rules-based solutions which are limited to the limited inputs. Also, as compute power continues to increase, the neural networks will leverage for improved accuracy.

Deep learning has demonstrated its capacity to increase the effectiveness of a computer to reliably classify objects and behavior. Security software companies are now marketing analytics that can leverage deep learning to turn vast amounts of video footage into usable information in a fraction of the time it would have taken in the past. In the video surveillance analytics market, some algorithm developers are using AI in the form of deep learning to maximize their output efficiency. Most of these software companies are training the algorithm mostly in the cloud, using solutions such as Amazon Web Services or Azure as heavy computing power is expensive so it is leased. This has bolstered the growth of the security could market by a factor of 35% yearly.

Programming and coding methods have also been optimised for rapid deployment. In the past, the speed and quality of the analytic was directly impacted by the team’s size. Now, analytics can be developed for niche applications quickly and with far lesser resource requirement boosting up competition amongst niche players. Furthermore, most of the large companies are focused on one-size fits all, leaving opportunity in niche applications.

Video processing software also allows users to interact with the surveillance footage using a search engine like interface with natural language search terms such (such as ‘man in a red shirt’, or ‘blue car’). This makes searching video like a breeze and much easier to use and search, there by significant reducing time and human effort to pull footage from hundreds of thousands of cameras. In addition to this, the ability to detect multiple objects and classify them allows for much greater insight – for example, this extends the ability to recognizing a cars color, type, make, model, and analysing which direction and speed it is moving at - making it possible to provide trending analysis, draw patterns and conclusions based on historical data.

This coupled with the concept of Command & Control Centres, the industry is moving in the direction of ‘Usable and Actionable’ Result oriented framework for security information management and security operations.

Face Recognition Applications and Biometrics:

Most facial recognition analytics on the market today feature some kind of deep learning. Not only does it increase the accuracy of facial recognition sensors, it also enables faces to be identified in larger and more crowded scenes. In the wake of recent terrorist attacks in crowded locations, this capability could change the whole approach to security monitoring, allowing law enforcement to track suspects with greater speed and efficiency.

However, deep learning analytics are doing more than just improving accuracy rates. They are also enabling the system to make assumptions and provide business intelligence on a detected face. Age and sex recognition algorithms, which are particularly popular within retail applications, allow end-users to profile potential customers and target marketing material appropriately. Furthermore, some vendors claim to be able to recognize a person’s emotions through analytic algorithms. There remains some debate as to the accuracy of these solutions currently.

One area where facial recognition has the potential to disrupt, is in the access control market. Facial recognition solutions have been used for a number of years at passport control in airports. However, as the price of the technology and cameras reduces, it is expected that facial recognition will be used to prevent access to restricted areas.

Risk Based Access Control:

In nearly all access control systems, the authentication process is a singular event; a credential is presented and access is granted or denied. However, by leveraging the advanced capabilities of neural networks this process can be made more intelligent.

At a basic level, risk based access control can be summarized as follows: in many sports stadiums public office space is combined with the actual sports stadium. Access to the office locations needs to be open when workers are accessing it during the week. However, when the sports event is on this access should be restricted and only provided to key personnel with the correct access control credentials.

In the example given the authentication process is dynamic, depending on circumstances. This allows the system to shift gears and provide a higher level of building security when certain events happen. By introducing the intelligence of AI to a risk-based access control authentication decision, the process can be made more complicated. Instead of defining risk levels by looking at the events currently on in the building, the system could pull data from other security or building management systems or social media alerts to make decisions based on this data. The main barrier to developing this level of complexity using traditional rules-based analytics is that there are simply too many variables to account for. The use of neural networks means developers do not need to write rules for the system to follow, they simply need to provide the algorithm with objectives and training data. Over time, the system will be able to decide how all of the inputs should relate to the current risk level.

Real Time Crime Analysis

Predictive analysis tools have come a long way since the first products and solutions. Police agencies can now make use of a wide range of data inputs and advanced data mining techniques to predict where criminal activity is likely to occur. This approach is called the predictive crime center and it is becoming an important part of modern policing.

Data from video surveillance, traffic management cameras, audio analytics, gunshot detection, weather systems, and other public safety systems are analyzed in parallel to identify patterns and potential threat events. Over the past few years, social media has also become a viable tool in public safety. In many cases, incidents are first reported on social media platforms such as Twitter and Facebook. Analyzing the data “hose” is challenging but can support quicker emergency response times when applied successfully.

The future predictive command center will be reliant on powerful analytics software to extract intelligence from the unstructured data sources routed into command centers. The solution must be open to ensure that enough data is fed into the big data solution. Artificial Intelligence will play a key role in navigating this data, recognizing patterns and making intelligent decisions independently of the human operators.

Related, a more localized solution to predictive alerts could be implemented in the suburban environment. AI could be used to identify criminal behavior such as burglary and theft. Deep learning video surveillance cameras could support the process, alerting to triggers such as loitering, repeatedly walking past the same spot and wearing clothing that makes it hard to identify an individual. Artificial intelligence in this case could also make better use of the crime data available – in terms of frequency, time, approach, and direction, to more accurately predict future criminal events.

Managing Large Data Volumes (Big Data), Privacy and Cyber Security

AI supports more detailed statistical analysis of the operations of security departments. However, one of the challenges for “big data” is in having enough data to make reliable statistical conclusions. As we have already highlighted, the short-term data analysis opportunities will likely be in situations where large data sets are created such as in safe city projects. Smaller companies may not be able to make accurate decisions based on a more limited data set. Ultimately, AI is required to identify that thing that does not belong in the data: this requires enough data to recognize anomalies, not just new content.

Another challenge is in normalizing the data. Social media represents an important new source, but in order to alert to abnormal behavior there needs to be an assessment of what is normal behavior. Consequently, normalizing the data set is critical to assess what is the typical amount of conversation around a specific topic.

The physical security market could also learn from other industries in applying AI to customer service. Natural language processing is improving and chat bots are increasingly used by consumer facing companies to provide an artificial intelligence interface for their users. This type of technology could be deployed to support physical security and employee security applications in the future.

As discussed, the performance of an artificial intelligence algorithm is linked to the quality and size of the available dataset. In an increasingly connected world, new physical security sensors are being deployed all the time, driving different data types into the AI solution. While this is great for the evolution of deep learning algorithms, it does present a threat in terms of cybersecurity. Historically, the biggest challenge for cybersecurity in the physical security market has been the lack of awareness throughout the route-to-market. End-users often underestimated the force of cyber threats and integrators and equipment suppliers were not focused on building cyber protection into their solutions.

More recently, equipment vendors in the video surveillance and access control markets have shown more commitment towards cyber security. Responses have included product hardening guides, encryption certification, the auditing of firmware code and partnerships with dedicated cyber security solution providers.

However, many of the connected device start-ups entering the physical security market don’t have the resources to focus on cyber security and will remain a threat to the overall solution. As the large IT companies improve their cyber defenses, it is likely that attacks on IoT vendors will increase in regularity and intensity. Ultimately, these companies will provide an easier target to hackers looking to maximize their impact.

AI is also relevant in terms of cyber security technology. For example, the defense market is already using deep learning applications to analyze cyber data to better protect critical national infrastructure. Many industry observers think that hackers will use this technology to escalate their attacks in the future too, increasing the cyber threat further. There are also some concerns related to how AI solutions interpret inputs and whether this could be manipulated by cyber criminals to cause confusion and damage in the future.

Related to the cyber threat, data privacy and risk will also be important considerations as AI solutions become more pervasive. Data encryption of video surveillance images is not common at the moment; mostly it is used in healthcare or critical infrastructure. GDPR (General Data Protection Regulation) in the EU could define video as unique personal data which may change the encryption requirements for video feeds.

GDPR could also impact what data is stored and how it is shared, impacting the analytics market. In particular, face recognition and person classification analytics will be considered personal data and have constraints on what can be done with the information. In response, Belgium announced that it will be banning the use of facial recognition for private use. The legislation does allow access control law enforcement applications but is an example of how data privacy could impact the physical security AI market.

Future is NOW for Artificial Intelligence

AI will be disruptive to many industries – not just the physical security market. Moreover, the impact of AI will not be just on industries and finance, but our entire society, especially in the areas of privacy and data security, labor, and ethics. The need for data security and privacy is more essential today than ever, given the availability of such powerful technologies.

The physical security market is primed to benefit from AI for two reasons:

• AI, in the form of deep learning algorithms, has the potential to revolutionize the video surveillance analytics market providing face recognition, object recognition and behavior recognition at a reliability level that will really matter to end-users.

• The physical security industry generates data. Video surveillance images, access control data, audio analytics, social media, police records management systems and other IoT sensors all generate data that can be correlated and analyzed by artificial intelligence systems to build a safer society. Intelligently managing this data is huge challenge. AI can help solve this problem.

The challenge for physical security vendors, end-users, and integrators will be how to make the most of the AI opportunity. This will involve investment, education and judgement to best apply this transformative technology to the individual challenges faced by each participant.

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iirisconsulting · 1 year

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INDIA IPR- ENFORCEMENT DIGEST Edition- April 2023

We are thrilled to release IPR Enforcement - Monthly Digest - Edition Apr'2023. This digest is produced by IIRIS Consulting Pvt. Ltd. to provide data, trend analysis, articles, new initiatives, etc. every month.

In the digest, we summarize the specifics of the monthly raid actions across India. #raid#enforcement#anticounterfeiting#fightingagainstfake

This issue describes the enforcement measures that took place in India in the month of March 2023 and the dual effects that occurred on the Indian economy and brands during the COVID-19 times.

Do check out this edition, as this study revealed the scope of the issue and the necessary steps taken by law enforcement authorities to prevent counterfeiting crime by gathering information about IPR enforcement actions in India and doing trend analysis.

We welcome comments to improve the endeavour. There is always additional data, and do reach out to the editorial team in case you need something customised.

Let's keep fighting the counterfeiters.

Visit us to know more - www.iirisconsulting.com

Editorial Team - Capt Sandeep Kumar Mehta Sagarika Chakraborty Sanjay Sharma Nandini Chaturvedi Amnish Sharma Esakki Aathimoolaperumal Prateek Kumar Lovika Chutani Anil Yadav Akash Wigh Ajay Kumar Singh Pundhir neelesh bhanot

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