Fortinet Threat Landscape Index Hits Highest Point to Date, Demonstrating Continued Increase In Cyberattacks

News Summary:

Fortinet® (NASDAQ: FTNT), a global leader in broad, integrated, and automated cybersecurity solutions, today announced the findings of its latest quarterly Global Threat Landscape Report.

• The research reveals that cybercriminals continue to look for new attack opportunities throughout the digital attack surface and are leveraging evasion as well as anti-analysis techniques as they become more sophisticated in their attempts.
• The Threat Landscape Index crossed a milestone this quarter. It is up nearly 4% from its original opening position year-over-year. The high point during that year-long timeframe is the peak and closing point of Q2 CY2019. The upsurge was driven by increased malware and exploit activity.
• For a detailed view of the Threat Landscape Index and subindices for exploits, malware, and botnets, as well as some important takeaways for CISOs read the blog.

“The ever-widening breadth and sophistication of cyber adversaries’ attack methods is an important reminder of how they are attempting to leverage speed and connectivity to their advantage”, said Phil Quade, Chief Information Security Officer, Fortinet. “Therefore, it is important for defenders to do the same and to relentlessly prioritize these important cybersecurity fundamentals, to position organizations to better manage and mitigate cyber risks. A security fabric approach across every security element that embraces segmentation and integration, actionable threat intelligence, and automation combined with machine learning is essential to enable these fundamentals to bear fruit.”

Highlights of the report follow.

Upping the Ante on Evasion Tactics

Many modern malware tools already incorporate features for evading antivirus or other threat detection measures, but cyber adversaries are becoming more sophisticated in their obfuscation and anti-analysis practices to avoid detection.

For example, a spam campaigndemonstrates how adversaries are using and tweaking these techniques against defenders. The campaign involves the use of a phishing email with an attachment that turned out to be a weaponized Excel document with a malicious macro. The macro has attributes designed to disable security tools, execute commands arbitrarily, cause memory problems, and ensure that it only runs on Japanese systems. One property that it looks for in particular, an xlDate variable, seems to be undocumented.

Another example involves a variant of the Dridexbanking trojanwhich changes the names and hashes of files each time the victim logs in, making it difficult to spot the malware on infected host systems.

The growing use of anti-analysis and broader evasion tactics is a reminder of the need for multi-layered defenses and behavior-based threat detection.

Under the Radar Attacks Aim for the Long-haul 

The Zegostinfostealer malware, is the cornerstone of a spear phishing campaignand contains intriguing techniques. Like other infostealers, the main objective of Zegost is to gather information about the victim’s device and exfiltrate it. Yet, when compared to other infostealers, Zegost is uniquely configured to stay under the radar. For example, Zegost includes functionality designed to clear event logs. This type of cleanup is not seen in typical malware. Another interesting development in Zegost’s evasion capabilities is a command that kept the infostealer “in stasis” until after February 14, 2019, after which it began its infection routine.

The threat actors behind Zegostutilize an arsenal of exploits to ensure they establish and maintain a connection to targeted victims, making it far more of a long term threat compared to its contemporaries.

Ransomware Continues to Trend to More Targeted Attacks

The attacks on multiple cities, local governments, and education systems serve as a reminder that ransomware is not going away, but instead continues to pose a serious threat for many organizations going forward. Ransomware attacks continueto move away from mass-volume, opportunistic attacks to more targeted attacks on organizations, which are perceived as having either the ability or the incentive to pay ransoms. In some instances, cybercriminals have conducted considerable reconnaissance before deploying their ransomware on carefully selected systems to maximize opportunity.

For example, RobbinHoodransomware is designed to attack an organization’s network infrastructure and is capable of disabling Windows services that prevent data encryption and to disconnect from shared drives.

Another newer ransomware called Sodinokibi,could become another threat for organizations. Functionally, it is not very different from a majority of ransomware tools in the wild. It is troublesome because of the attack vector, which exploits a newer vulnerability that allows for arbitrary code execution and does not need any user interaction like other ransomware being delivered by phishing email.

Regardless of the vector, ransomware continues to pose a serious threat for organizations going forward, serving as a reminder of the importance of prioritizing patching and infosecurity awareness education. In addition, Remote Desktop Protocol (RDP) vulnerabilities, such as BlueKeepare a warning that remote access services can be opportunities for cybercriminals and that they can also be used as an attack vector to spread ransomware.

New Opportunities in the Digital Attack Surface

Between the home printer and critical infrastructure is a growing line of control systems for residential and small business use. These smart systems garner comparably less attention from attackers than their industrial counterparts, but that may be changing based on increased activity observed targeting these control devicessuch as environmental controls, security cameras, and safety systems. A signature related to building management solutions was found to be triggered in 1% of organizations, which may not seem like much, but it is higher than typically seen for ICS or SCADA products.

Cybercriminals are searching for new opportunities to commandeer control devices in homes and businesses. Sometimes these types of devices are not as prioritized as others or are outside the scope of traditional IT management. The security of smart residential and small business systems deserves elevated attention especially since access could have serious safety ramifications. This is especially relevant for remote work environments where secure access is important.

How to Protect Your Organization: Broad, Integrated, and Automated Security

Threat intelligence that is dynamic, proactive, and available in real-time can help identify trends showing the evolution of attack methods targeting the digital attack surface and to pinpoint cyber hygiene priorities. The value and ability to take action on threat intelligence is severely diminished if it cannot be actionable in real-time across each security device. Only a security fabricthat is broad, integrated, and automated can provide protectionfor the entire networked environment, from IoT to the edge, network core and to multi-clouds at speed and scale.

Report and Index Overview
The latest Fortinet Threat Landscape Report is a quarterly view that represents the collective intelligence of FortiGuard Labs, drawn from Fortinet’s vast array of global sensorsduring Q2 2019. Research data covers global and regional perspectives. Also included in the report is the Fortinet Threat Landscape Index (TLI), comprised of individual indices for three central and complementary aspects of that landscape which are exploits, malware, and botnets, showing prevalence and volume in a given quarter.

By: Fadi Kanafani, Middle East Managing Director & General Manager at NetApp.

The impact of AI is being seen across industries and geographies. AI is now a key to success for organizations and is set to be a significant contributor towards global economic growth by 2030. According to a study by McKinsey Global Institute (MGI), on average, the global gross domestic product (GDP) could increase by 1.2 percentage points per year, which would correspond to a total value added of 13 trillion US dollars.

Among a number of industry segments, the automotive industry is one of the most technologically advanced and progressive industries. It’s no surprise that the industry is a frontrunner in adopting and incorporating AI into research, design, and manufacturing processes for smarter and better outcomes and products.

When you think about AI in automotive, autonomous vehicles is likely the first use case that comes to mind. While the holy grail in the industry is full self-driving, defined as level 5, most companies are already offering increasingly sophisticated adaptive driver assistance systems (ADAS) as stepping stones towards that level of autonomy.

In an industry like automotive, the number of possible AI use cases is large and essentially divided into four segments which are autonomous driving, connected vehicles, mobility as a service, and smart manufacturing. Naturally, there are overlaps between some of these segments; success in one area can yield benefits in another. For example, autonomous driving may be a key element of a mobility-as-a-service strategy. There are also many requirements that all segments have in common, including infrastructure integration, advanced data management, security, privacy, and compliance.

There are, however, challenges to achieving full self-driving. Each car deployed for R&D generates a mountain of data; 1TB per hour per car is typical. Teams can expect to accumulate hundreds of petabytes to exabytes of data as autonomous driving projects progress. This raises several critical questions such as how to create a pipeline to move data efficiently from vehicles to train a neural network or how to efficiently prepare and label data for neural network training are some of the concerns. Some questions that need to be addressed are how much storage and compute power is needed to train a neural network, to run inference on a trained neural network and if the training cluster should be on-premises or in the cloud. It is also important to determine how to correctly size the infrastructure for data pipelines and training clusters including storage needs, network bandwidth, and compute capacity.

Cars and other vehicles are quickly transforming into connected devices, and there are a number of immediate use cases for AI in connected cars such as Personal assistants / voice-activated operations, Telematics and predictive maintenance, Infotainment/recommenders.

Today, cars use cellular and WiFi connections to upload and download entertainment, navigation, and operational data. In the near future, we’ll also see cars connecting to each other, to our homes, and to infrastructure. For example, Audi has already introduced technology to connect cars to stoplight infrastructure, enabling drivers in select cities to catch a “green wave”, timing their drives to avoid red lights. That’s just one of many opportunities to use data from connected cars.

In the future, car ownership may decline in favor of various forms of ride sharing, particularly in dense urban areas. Car companies will need to become mobility service companies to address changing consumer demand. Many car companies such as Ford and home-grown Careem are already branching out, acquiring scooter- and bike-sharing companies and creating delivery services.

The machine learning and deep learning problems in mobility-as-a-service models are significantly different than those in autonomous driving: How do you predict customer demand? How do you optimize fleet efficiency and minimize customer wait times? How do you dynamically set prices in response to demand? How do you ensure passenger physical security? How do you protect customer data, prevent fraud, and balance privacy versus convenience?

From an infrastructure standpoint, these distributed problems require different strategies and may require smart algorithms on the consumer’s device (smart phone), in the vehicle, and in the cloud, plus long-term, secure data management for compliance.

The auto industry has a lot on its plate. Companies must look for ways to increase operational efficiency to free up capital for investments like those described above. Industrial Internet of Things (IIoT) and Industry 4.0 technologies are the key to streamlining business, automating and optimizing manufacturing processes, and increasing the efficiency of the supply chain.

Common manufacturing use cases include an increased use of computer vision for anomaly detection, process control for improved quality/reduced waste, predictive maintenance to maximize productivity of manufacturing equipment.

Competition in the auto industry is also fierce. Leaders look to train their own AI specialists and developers and cooperate with other companies to maintain their standing. While these measures are intended to close the current knowledge gap, it also helps achieve the overarching goals of higher product quality, better customer experience with AI, and reducing operating costs. Innovations are the key to keeping up with IT companies in the competitive field of autonomous driving.

The benefits that AI brings to the automotive industry are perceived as excessive. At the same time, there is an increasing pressure on business representatives not to miss out on the next big thing. Industry studies usually stop at a point where they become interesting: the impact on daily work routine. It would be exciting to see which AI technology the experts in the automotive industry are working on and what challenges they face.

Author: Mohammed Al-Moneer, Regional Vice President of Sales, MENA at A10 Networks

Load balancing of application traffic has been around for a long time. But, as more organisations move to the private and public cloud, it’s undergoing significant changes. Let’s look at some of the important considerations of this evolving technology.

Three major requirements underline IT operations and DevOps today: agile, efficiency and, multi-cloud operations.

• Agile: The movement toward public cloud is arguably driven by an organisation’s desire to deliver more functionality faster. Public clouds like Microsoft Azure and Amazon Web Services (AWS) allow organisations the capacity and capability necessary to drive that agility.
• Efficiency: Doing more with less puts a great amount of pressure on IT operations. With infrastructure as a Service (IaaS), management is divided into infrastructure management and application management. IaaS addresses availability, elasticity and efficiency of operations, and cost. Application teams then address the efficiency of application delivery.
• Multi-Cloud Operations: Companies prefer to keep their data within their own data centres. Most adopt a multi-cloud infrastructure to balance privacy and efficiency. Less-sensitive data may be stored in public clouds while sensitive data remains in their private cloud.

Current State of Load Balancing in the Cloud

Advanced load balancing has emerged as an important element of modern operations. Load balancing has evolved given these three requirements of DevOps. Load balancing historically only handled distributing the traffic amongst servers and, in some cases, SSL offload.

Load balancers are in the middle of an organisation’s application traffic. They’re place in a critical position to see a tremendous amount of information about the flowing traffic.

Advanced load balancing provides more value and efficiency to the operations team. This is especially true with micro-services architecture and the deployment of datacentre containers or Kubernetes environments.

 5 Benefits of Advanced Load Balancers for the Cloud

The advantages of advanced load balancing can be condensed into five main categories. Let’s take a closer look at each benefit and why advanced load balancing plays an important role in promoting team agility, improving security, streamlining workflows and using new technologies.

1. Increased Visibility, Insights and Analytics

Increased visibility, insights and analytics allow organisations to accomplish several goals, spanning from basic to cutting-edge.

• Improve network traffic monitoring by including application traffic with traditional infrastructure monitoring. Organisations can learn what traffic is coming and how efficiently it is being served.
• Detailed reports and health statistics, and thus better understand how their infrastructure is performing.
• Operations teams can complete the troubleshooting process more efficiently.
• Analytics and insights become proactive rather than reactive. A company might notice a latency issue and work to fix it before users start sending in support tickets.
• Use the insights to perform actions automatically. Automatically adjust the infrastructure due to a change in application traffic, or block a user identified as an attacker.

1. Integrated Security

Load balancers are placed directly into the flow of all network traffic. That placement presents an ideal opportunity to understand the behaviour and differentiate between good and bad traffic. Load balancer can automatically detect anomalies and, as a result, stop malicious traffic.

Infrastructure security is the responsibility of public cloud providers like AWS and Azure. Application-level security is still the responsibility of application owners as per Shared Security Responsibility. It is essential organisations understand the importance of full stack security and look for load balancers with integrated security.

Security products have traditionally been overly complicated and difficult to configure. Modern security products’ makes it easy for operations teams to quickly configure and use critical functions. Advanced load balancers capable of integrating with advanced security products can increase efficiency and strengthen defences.

1. Centralised Management

Centralised management eliminates the need to log in to individual load balancers. There you can see the entire application stack within a single pane of glass. Public clouds allow the application stack to run across multiple regions. Centralised management allows application traffic to be managed across all regions within a single console. This provides both efficiency and easy manageability.

Advanced load balancers integrate with centralised management. Central management of policies is even more valuable when load balancers are deployed across multiple clouds. This power adds centralised visibility and analytics of the environment. The centralised analytics corelates data coming from various sites. This facilitates actionable insights across the entire environment.

Observations from one site, especially related to cyber security attacks, can be used for proactive actions on other sites. For example, a cyber attacker is identified at one site they can be blocked at all sites from a central console.

1. Automation and Multi-Cloud Integration

More than 70 percent of organisations have a multi-cloud environment. Any technology they adopt today must integrate across the entire environment. This includes public clouds, private clouds, data centres, and bare-metal servers. This requirement applies to choosing a load balancer.

It’s important that load balancers have APIs for integration. Many enterprises have already implemented continuous integration/continuous delivery pipelines. Load balancers need to integrate with DevOps toolchain and infrastructure platforms.

Full integration is achieved only when API calls are possible in all directions. DevOps tools can call the load balancer API. Load balancer can call the external API in case of an alert or event.

1. Containers and Container-Orchestration Integration

The industry is adopting containers and container orchestration systems. According to a recent survey by 451 Research, 71% of enterprises are either using or evaluating options like Kubernetes and Docker.

Applications are moving from monolithic to a microservice architecture. Deployments are migrating from traditional hardware servers with virtual machines running on the cloud, to containers running on multiple environments.

Kubernetes and Docker have been adopted by many of the industry’s top players, including Google, Amazon, Microsoft, VMware, RedHat, IBM and more. Docker and Kubernetes have as a result become de-facto standards.

Data centre criteria should include integration with container technologies. It must automatically scale containerised applications as needed while simultaneously maintaining complete visibility. This eliminates the need to manually configure policies or manage scaling.

Given the significant benefits of cloud load balancing, it’s easy to see why organisations are turning to new and advanced load balancing solutions. Load balancing is evolving to combat the evolving threat in cyber security and businesses have taken notice.

By Vikram Bhat, Chief Product Office, Capillary Technologies

Humans by nature are selectively attentive, which means, they react to things only if they are truly interested in it. For years, brands have ignored the very basic fact of making their consumers feel ‘invested’, interested and unique. Consumers, they are the reason brands exist. The proliferation of the internet and the introduction of mobile applications has made brands accessible to consumers more than ever. While competition is fierce in retail the industry with the arrival of new brands in an already saturated market, each of these brands are vying for the same customer. In such a competitive market, how then can brands differentiate their voice and build a loyal clientele?

Personalization is the answer

Gone are the days of mass marketing and ‘one size fits all’ campaigns as consumer expectations and buying journeys have evolved over time. With an omnichannel shopping experience, consumers expect a customized and seamless journey across platforms. They also expect brands to ‘address’ them individually and earn their loyalty. To make this happen, brands are turning towards personalizing their marketing campaigns with the help of technology. While the tried and tested micro segmentation method is effective, it is also a tedious process. Here’s where Artificial Intelligence is a real game changer.

But why should brands personalize their approach when they already have customers? Today, consumers have the power to choose, and personalization allows brands to communicate with and reach their target audience at the right time, with the right product, the right offer and message, through the right channel. Brands are able to achieve a better response rate, increased customer loyalty, and lower marketing costs. According to a report from Marketo, 79% of consumers are more likely to respond to brand promotions if it is tailored to their preferences and previous purchase interactions. Which is why personalization is also the first step toward building brand loyalty.

Role of data in personalisation

Knowing your customer is the key to a personalized campaign, and data is more important than you think. The journey always begins with capturing the right data. Brands must leverage their goldmine of data which they collect across platforms to keep campaigns on target and devoid of old-fashioned judgement and error-prone segmentation. An AI-driven strategy helps make sense of this data. It creates an algorithm to understand individual consumer preferences. It will deep dive into their buying patterns and history, product preferences and characteristics. It analyzes customer behavior and other parameters to create and send personalized campaigns to each customer – akin to giving someone a tailored suit. This helps brands achieve a true 1:1 personalization and continues to optimize campaigns through machine learning.

Personalization is also the first step towards building a brands customer experience. Consumers are inundated with messages from brands who are forced to compete on discounts to increase sales. According to Red Crow Marketing, on average consumers may be seeing more than 4000 adverts, most of which are of little or no interest. As consumers we tend to engage with advertising only if its meaningful. Such communications help create lasting relationships.

Brands need to be omnipresent, and AI is helping brands personalize their presence in more ways that one can imagine. Building brand loyalty is one. Consumers tend to be loyal to brands that care for them. A study conducted by Accenture shows that 91% of consumers are more likely to shop with brands who remember them and provide relevant recommendations. Today, brands have a goldmine of data but often lack the creativity to design compelling campaigns or the ability to identify their targets consumers. AI analyzes this data by looking at previous marketing campaign successes, buyer history, preferences and timelines, and other key markers to create new targeted campaigns.

Overcoming challenges with AI

A common obstacle that brands often face in taking personalization to the next level is the ability to design multiple versions of a campaign across platforms. Here AI helps save time and money while giving brands visibility into the buyers’ journey across multiple platforms.

The RoI on AI-driven campaigns are immense. Personalizing campaigns benefits brands immensely; it reduces acquisition costs by as much as 50 percent, enhances revenue by 5 – 15 percent and increases efficiency of marketing spend by 10 percent to 30 percent.

The future of personalization is a true 1:1 engagement, which AI is enabling. We are looking forward to a time when personalization will be the only way brands choose to interact with their customers– that’s the future which will eventually be a reality.

Author: Naji Kazak, General Manager – Middle East, Africa, Turkey & Russia at Alaris, a Kodak Alaris Business 

Historically, the healthcare industry has been paper intensive, but in this digital age, document scanning and archiving will help speed up patient care, improve records management, ensure regulatory compliance and provide significant cost savings. Medical scanning and data capture technologies are now becoming an integral part of the industry.

So, what are the right features to consider when choosing the best scanners for healthcare and medical records scanning?

Process Optimization

The admission process in any healthcare setting is time-consuming and creates a significant amount of paperwork. 70 percent of new patient information is received as paper documents which takes time and money to process manually. Manual data entry runs the risk of error, and this can impact patient care.

Scanning is often cumbersome because, in addition to patient intake forms, there are irregularly sized documents such as insurance cards and photo identification that also need to be in a patient’s medical record.

Today there are scanners that have superior document handling capabilities that ensure that patient records are quickly and reliably scanned. With features such as Active Feed, Controlled Stacking, and Intelligent Document Protection, all documents are accurately scanned without the need for presorting.

Compliance

It is important that the scanners being used contribute to the security of electronic personal health information. The scanners need to comply with existing and new legislation and ensure that confidential patient data is safely routed to a secure file repository. By eliminating paper records and digitizing paper based documents that arrive from external sources or documentation that gets produces during the hospital stay, you’ll mitigate risks and ensure secure data handling and storage. The insertion of patient data into the EMR system ensures patient privacy and compliance.

Optical Character Recognition

OCR is one of the most important features a scanner can provide to a healthcare setting for medical records scanning and indexing. Optical character recognition is the electronic conversion of images of typed, handwritten or printed text into machine-encoded text. OCR allows you to search and sort PDF documents in the same way you would a Microsoft Word, Microsoft PowerPoint, or Google Docs file. You can search by keyword, edit with a word processor, send the text by email, and even decode it using screen readers.

These benefits open up a larger bundle of benefits that otherwise would not be possible. Those benefits include:

• Speed:Modern OCR technology dramatically improves efficiency by decreasing the time spent searching for information on medical records. Instead of searching through documents manually, you can search by keyword. You can even use names as keywords to quickly find documents for specific patients.
• Cost efficiency:You can finish more work in the same amount of time when you eliminate the need to manually search for documents and specific notes on those documents. Additionally, you’ll save money by avoiding the costs associated with copying and printing.
• Reduced environmental impact:It’s simple: The fewer resources you use, the less of a negative impact you make on your environment. Digitally indexing your documents as opposed to using a traditional filing system reduces your paper usage.
• Reduced physical space:Without a physical filing system, you have more space available where filing cabinets used to be. For some offices, this means a more efficient use of space. For others, it may even mean relocating to a smaller space to take advantage of cheaper rent and lower overhead for heating, cooling, and lighting.
• Document accessibility:Having documents scanned and indexed with an OCR makes their information immediately accessible in multiple places and on multiple systems at once. This is a huge improvement compared to only having a select number of physical copies available in select locations, which you must spend time searching for and filing.
• Reduced errors:Data entry errors happen. So do typos, lost documents, and misfiles. Automatically indexing your documents eliminates all of these issues.

 

Intelligent Barcode Reading

Intelligent barcode reading automatically processes barcodes for job instructions when scanning. You can group different types of scanning jobs together, each type of job being bookended with barcodes prompting the scanner to read everything within them in a designated way. Once the scanner reaches the second barcode in the stack, it removes those instructions and moves on to the instructions provided by the barcode in the next stack. This way, you can process multiple types of jobs at once without needing to tend to the scanner.

This technology further improves the efficiency of your medical office, whether it is a small private practice or part of a larger hospital. Providing health centers with sufficient time to care for each individual patient is one of the game-changing differences between the bedside manners that make people feel welcome and the hurried attendance that leaves patients feeling like just another number. Less time spent in the back office means more time spent helping the patients themselves.

The Best Features Are the Ones You Need

Look for scanners that  usenative, non-proprietary TWAIN integrations, which means they are time-tested, provide for easy integration, and will not present surprises later on when PC’s are upgraded. Document scanner vendors should also have a full team of field engineers to provide installation, technical support, and proactive troubleshooting tasks to staff, avoiding costly downtime.

Scanners that are the best to use in your EMR system  integrate with the majority of electronic medical records systems like McKesson and Epic. Make sure they also have the required certifications like Cerner for example, so you can be sure that you comply with healthcare standards.

By Shereen Shabnam

With the recent introduction of the innovative IQOS at the Dubai Duty Free, interest in smoke-free products has increased in particular with the new IQOS 3 and IQOS 3 MULTI that comes with improved design and functionality and offers adult smokers a better alternative for nicotine consumption than traditional combustible cigarettes.

We recently ventured to Geneva to explore the benefits of moving away from smoking with combustion where toxicants associated with burning are the primary cause of smoking-related disease to an alternative that helps the transition to eliminate health issues related to smoking.

We learnt with Philip Morris International (PMI) that the high temperatures in the lit end of a burning cigarette, above 600C, cause a large number of chemical reactions to take place, breaking down the tobacco into the thousands of chemicals that appear in cigarette smoke. Many are considered harmful, and together they are recognized as the main cause of smoking-related diseases.

Seeing first hand the future plans of Philip Morris International as they work towards building their future on smoke-free products is commendable, especially as smoke free products are a much better choice for those who refuse to quit.

Through multidisciplinary capabilities in product development, state-of-the-art facilities and scientific substantiation, PMI aims to ensure that smoke-free products meet adult consumer preferences and rigorous regulatory requirements. The vision for PMI is that these products ultimately replace cigarettes to the benefit of adult smokers, society, the company and the shareholders.

Having seen the quality control measures on their production site and the commitment to invest further into smoke free alternatives, the future looks better for smokers worldwide as they learn that inhaling the complex chemical mixture of combustion compounds in tobacco smoke causes adverse health outcomes and move towards smoke free products.

Using smoke free products like IQOS eliminates burning and hence the formation of toxicants is significantly reduced. If the tobacco is heated to temperatures below 400C, a tobacco vapor is produced instead of smoke.

At these lower temperatures, the toxicants in cigarette smoke are significantly reduced or eliminated. The resulting vapor still provides the flavor and nicotine that adult smokers are used to and crave.

The positive response and the growing support for the role of non-burning alternatives in public health is a sign that smokers and stakeholders appreciate the research and studies done to make smokers understand the benefits of moving to smoke free products.

According to PMI, an increasing number of public health experts from around the world now believe that products that don’t burn tobacco and tobacco-free nicotine products that smokers can switch to can have a positive public health impact.

The new IQOS 3 and IQOS 3 MULTI deliver a premium tobacco experience with simplified usability, personalization and taste from real tobacco rather than liquid. Both devises have no ash and releases a nicotine-containing aerosol, not smoke, which leaves a less lingering smell on hands, clothes and hair, meaning, favorite clothes are safe from burns and undesired smoke smell.

The new IQOS devices have new protective reliability, a more sophisticated design and will appeal to adult smokers who would otherwise continue to smoke and are looking for an alternative.

IQOS has already helped nearly 6-million adult smokers stop using cigarettes and switch to smoke-free alternatives

The IQOS 3 MULTI provides the user with 10 consecutive uses without needing to be recharged. The work of over 400 PMI scientific personnel has yielded an elegant design, which does not sacrifice functionality.

As well as state-of-the-art design and premium feel, PMI products come with a choice of over 500 color combinations using a wide range of available accessories.

What we leant in Geneva is that IQOS is a technologically-advanced heat-not-burn alternative to cigarettes which emits over 90% less harmful chemicals compared to cigarettes and hence PMI has made a commitment to a smoke free world and having loved ones who are heavy smokers, I sincerely wish the message on the alternative smoke free products reaches far and wide.

Thankfully, with products like IQOS, there are now rapid developments in nicotine-based products that can effectively substitute for cigarettes and become viable alternatives to smoking in the future.