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Why does hotel cybersecurity matter?

The hospitality sector has become one of the lucrative targets attacked by cybercriminals. The major reasons are:

1. The hospitality sector stores a lot of sensitive information of users due to its extensive use of Artificial Intelligence and Machine Learning to offer top experience. This includes personal preferences, travel itineraries, passport details, credit/debit cards.
2. Financial operations for the guests and executives can be a prime target.
3. Loyalty programs encourage more visits than scrutiny for credit card statements. 

Data theft is becoming a major concern as hackers can access the entire chain networks with just one regional hack due to interconnectivity. There are potential entry points for hackers such as electronic door locks, alarms, climate control systems, Wi-Fi, Internet of Things, etc.

The lack of security awareness is a big issue due to more employment rate in the hospitality sector. Another issue can be higher turnover that can put everything in jeopardise due to one unsuspecting employee.

A failure in cybersecurity can be catastrophic that can increase the chance of blowing brand reputation. It is essential to keep cybersecurity at the front seat instead of treating it as an afterthought. 

Types of Security Threat in Hospitality

Many vulnerabilities in the digital world include the hospitality sector. Now since security is covered, let us understand what are the types of security threats in the hospitality sector. 

1. Point of sale attack

POS attacks target the credit cards that are common in the hospitality sector. They can be a weaker link for hospitality as it is easier for hackers to hit due to weak passwords and insecure remote access. The third vendors are usually hired to offer top security to the POS. It is essential to use end-to-end encryption, two-factor authentication, and antiviruses on the system to prevent hackers from data breaches. Along with this, PCI standards should be followed by the hospitality sector for servers, routers, and networks, monitor threats, or hire data security providers.

2. Phishing attacks

Another common type of cyberattack is a phishing attack that looks like an email sent from a trustworthy source. This consists of the link that can install unwanted software in the system that can result in accessing unauthorised data such as credit cards and passwords. 

3. Ransomware and Malware

Cyberattacks are extremely common that install malicious software or malware in the user’s computers that can steal data and delete files. There are trojan horses as well along with spyware and viruses that can encrypt the data allowing victims to suffer due to data loss. The ways to stay protected against ransomware and malware are backing up data regularly, keeping software up-to-date, and educating staff to avoid such breaches. 

4. Denial of Service attacks (DDoS)

These types of attacks happen on the network or server by overloading it. The internal traffic is increased that results in generating a powerful torrent and ends up overloading the servers. This is one of the popular ways for cyberhackers to use and has exceeded 1,800 attacks in a day in 2021. 

Cybersecurity Practices to follow in Hospitality

The best way to prevent any type of data theft, the hospitality sector can devise the right strategy and focus on the basic principles. There are few practices that one can follow including:

1. The hospitality sector needs to educate the staff against the threat to ensure that they can prevent carelessness while dealing with technology. 
2. Employing SaaS platforms and software providers that can help in managing and securing critical operations. 
3. Working on digital infrastructure and taking help from reputable service providers for third-party software. 
4. Design a plan to prevent data breaches or to tackle any hacks immediately. 
5. Use a secure third-party server to ensure top security to the data.

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What is Zero Trust Security?

As the name suggests, zero trust showcases that companies shouldn’t trust any individual or device when it comes to securing their confidential data or sensitive information. This can be outside or inside the premises that have made it essential to verify the source before giving access.

The companies need to verify the person and establish trust before giving access to any type of data. This helps in eliminating anyone who might leak the data and prevent data breaching within the network. However, there is a zero trust architecture that the companies can implement that mitigates the risk of unauthorized access and data breaches while offering the highest level of security.

Zero trust security is based on the major principles including least privilege access, user verification or identification, micro-segmentation, advanced data theft prevention techniques, and real-time monitoring of device access. 

Why implement Zero Trust Security?

Now you know what zero trust security is all about and know why companies need it in the first place. The model focuses on the default secure state of the information that includes outside network access to offer adequate security.

The zero trust security goes way beyond conventional security approaches that only focus on corporate firewalls that can be easily avoided without resistance. Many connections can easily access data and run businesses openly, which is leading to cyberattacks due to its lack of security layers.

The open networks inside the company can be an alarming situation that enterprises need to address. The companies need to consider their access management and address bad external actors to eliminate compromises.

Here are the major benefits to opt for a zero trust security model or mechanism.

1. Prevention of unauthorized access

The zero trust security offers stringent policies that allow companies to monitor unauthorized access. It protects data, prevents any external threats, and safeguard the data from internal threats. They always verify and never trust policy is introduced with the zero trust security model that prevents any type of data misuse.

2. Remote “secure” workforce

With the pandemic, cybercrime have increased when users are working remotely. To prevent this, companies can implement a zero trust security model that minimizes new vulnerabilities and increased sudden exposure. The robust security mechanism can decrease the dependency on firewalls and use advanced measures to avoid any hacks. 

3. Greater visibility

Zero trust means adding more security strategies and not trusting anyone. The users can decide who will access the data, what they can access, and even track their activities. With stringent authentication, the admin can offer top security to the sensitive information while monitoring others who are accessing the network. Admin gets complete visibility over others including precise location, time, and application used by others. 

4. Ensure compliance

Zero trust evaluates the data first before giving any access to them along with tracking others. It helps in producing evidence, maintaining system security, and making governance faster and efficient. 

5. IT Management

Since the admin can control, monitor, and analyze the activities of the users with zero trust security, it is easy to manage the tasks. Automation allows users to identify security aspects and get everything approved by the admin that decreases human errors. The admin is in charge of making the decisions and allowing their team to innovate instead of working on mundane tasks. 

Conclusion

Zero trust security is the need of time with companies embracing remote working and planning to shift their workforce to permanent work from home. A robust system is required to identify and access the controls as a stronger security architecture. The users need to verify all the devices from the admin to protect organizations from foreign or domestic online threats. 

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Several examples of augmentation in human life are spectacles that enable people with poor eyesight to view clearly, monochrome glasses that gives colour to people with colourblindness, microscope which allows us to explore the hidden small microscopic world with, within or around us under the scanner of lenses and so on. It is kind of hard to imagine lives around us without them. While these technological inventions have not only dominated our professional and personal spheres but have also become an inseparable part of our lifestyles.

In today’s modern era, humans have not only successfully augmented reality but have also found some very non-invasive ways to augment humans.

1. Future Work Transformation Spending

In 2021, Future of Work (FoW) spending is forecasted to be about 656 US bn dollars worldwide. If further calculated it would be about 17.4% more from 2020 in terms of future work transformations. This not only hints towards a requirement for human and machine collaboration but also some flexible work situations.

The increased workload around the world, deeply interconnected areas of varying fields and the never-ending input and output of various data from one department to another shows the relevance of a smartly connected appliance. Along with this, it can showcase the true worth of networking smart gadgets. The 17.4% increment in workload demonstrates the periodic changes in the working pattern in terms of advancements and the addition of something more. It also shows the intensities with which the companies need to be working to pay off the heavy demands of customers.

With the graph given below, it is clear how within a span of one year (2020-2021) an increment of 97 points nears 100 points. This shows an increase of 17.3% within just one year which is a huge increment for just one year if we think.

2. Difference Between AI And Augmented Intelligence

Artificial intelligence helps in advancing human potential by boosting productivity, eliminating the burden of mundane or secondary tasks, focusing on the primary tasks and enhancing quality in it.

The major difference between AI and Augmented Intelligence is that of autonomy. Artificial intelligence is used to operate without any external support or human assistance whereas augmented intelligence is the manifestation of our desires to improve on something but with human assistance of course.

3.  Fragmentation Of Augmented Intelligence

The market has been divided into various segments for easy understanding of the intelligence in terms of product, end-users and region.

Product:

• Wearable augmentation
• Inbuilt augmentation

Sector:

• Defence
• Manufacturing
• IT
• Healthcare

Biology:

• Bionics and prosthetics (artificial limbs)
• Brain-computer interfaces
• Neurotechnology (brain implants)
• Nootropics (“mind” drugs)
• Gene editing (a special tool that enables DNA editing and will help in future treatments of many ailments and illnesses which are hereditary or so on)

Technology:

• Wearable
• Virtual reality
• Intelligence virtual assistant
• Inbuilt augmentation

Spreadability of augmentation region wise:

• North America
• Asia-pacific
• Europe
• Rest of the world

4.  Scope Of Augmented Intelligence

Based on the various factors of how functional, technologically advanced and regionally acceptable augmented intelligence is, the scope of AI remains very subjective. A deep understanding and research in terms of what the particular region demands plus what the company can offer at the best possible price and quality remain the line of understanding here.

If we are reading in between the lines given the highly online and active world we live in (which is a practical internet and intelligence dependent era)- a good lookout for intelligence investments and augmentation of some immediate tools is required. It will not only boost the productivity of the company but will also help the company take a lead in the market.

The human augmentation market is expected to reach approximately 2.84 billion dollars by 2023, growing at a compound annual growth rate of 30.07% between 2017 and 2023. Health will be the most highly expected growth-oriented in the coming years at a compound annual growth rate of 30.54%.

Over a decade it has been reported that augmentation is not only new but also a very innovative take on how productivity can be achieved in a very time-bound but also healthy and interactive session

AI in the manufacturing market is dominated by globally established players namely- Nvidia(USA), IBM (United States of America), Intel (United States of America), Siemens (Germany) and General Electric company (United States of America).

5.  AI in the manufacturing sector

Manufacturing is the keystone to deciding the country’s economic growth; in globalized terms but also on an international level. For a level playing field, advancement in the manufacturing process is not only a necessity but also the desired input. Thus investing in automation and augmentation in manufacturing processes enhances and speeds up the entire process and reduces the time taken but also enables the unit to serve the supply-demand gap. The marketing sector has been divided into various sectors. Various fragmentation of AI in manufacturing are:

Technology-

• Machine learning – deep learning, supervised learning, reinforced learning
• Context-aware computing
• Computer vision

Application-

• Quality control
• Industrial robots
• Cybersecurity
• Field services
• Production and management
• Machine inspection
• Maintenance
• Fault detection

6.  Internet of things (IoT)

Ever imagined how with a single voice command your TV turns on and you can also switch off the other appliances simultaneously? With just a single command you can ask Alexa to play your favourite songs and spell out the headlines.  With the growing emphasis on digital transformation, more and more organizations are motivated to opt for the internet of things(IoT).

This newness enhances the customer’s experience but also creates new and better experiences for the customers in terms of technological advancements, better channelling of the product etc.

Some examples of IoT are connected appliances (example Alexa connected appliances), smart home security systems like digital locker systems or digital door locks etc, health monitoring smartwatches or devices, smart factory equipment (control system, smart sensors, automated doors etc), ultra-high-speed wireless internet, biometry cyber security scanners and so on.

It works on the data collected by the sensors and finally assimilates together to turn into operations based on the demands of the user. Just as machine learning is a way in which computers learn about how to communicate by similarly storing data, IoT is a way of allowing humans to communicate over a network and operate using the stored data and references of the sensors.

While machines have been partially successful in emanating the human tendencies or skills but have not entirely been able to truly replicate them in essence. Which is a bit more research and experimentation further in terms of implementation. With the unique blend of AI and IoT, many can achieve wonderful results- depending upon the reasonability and feasibility for the required task. Wherein AI is typically machine-oriented and associated. Meanwhile, IoT is this capability of how to thread up the already smart devices together on the network.

Hence taking a holistic approach toward adopting AI and IoT and thorough strategic planning and investment depending upon the regional and time requirements would also allow the human generations to deal with anthropogenic issues in an accessible and doable format.

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Getting to know about SIEM(Security Information and Event Management):

SIEM  is used extensively by large enterprises for quite a long time, which helps them to recognize the blind spot in logging, filtering the noise, and tuning firewall audits, proxy filtering logs and data from end-point will improve existing alerts results.

SIEM best practice:

With the lack of adequate Audit policies, most of the logs(80%) are having noise. If tuning is not proper, it will not give accurate result value from SIEM investment. Sending everything from logs to the SIEM is completely irrelevant and will give undesirable results. To save both time and money, it is important to use channelized audit policy and filter out the critical events, by enforcing correct policies with a firewall filtering out the noise and tuning it.

Getting to know about XDR(Extended detection and response):

XDR on the other hand is the latest thread detection mechanism in the field of cybersecurity. It helps to reformulate gathering, normalizing, and correlating data security from several sources and strengthening the security products to respond correctly and quickly. 

XDR do much more than detecting the security incidents:

It is an integrated security strategy platform with different tightly coupled security applications in a single platform. It is having a four-stage process to collect logs, packets, files & user data from multiple sources and then detect the patterns for vulnerable behavior. After successful identification of these patterns, query investigation is done for the malicious activities and finally automating the response by taking appropriate actions and generating POF(plenty of fish) reports.

What makes XDR different from SIEM:

It is using new cloud-native technology architecture and different microservices such as service-oriented architecture(SOA) with the help of clustering and containers. It provides scalability and flexibility in the deployment with high-performance-centric queries which will make the whole process faster than SIEM.

SIEM aggregate data from different sources together from the whole environment at one place and allow security specialists to work on that interface. Although it collects information from all the sources, the resulting details are of low level. It does not allow any surplus information from data about the tools used for additional research analysis about specific incidents. From tools like EDR(Endpoint Detection and Response) & EPP (Endpoint Protection Platforms), It has a restrictive capability to process advanced groups of security information.

What makes XDR better:
XDR is having various complementary tools other than SIEM:

• Security tool Interaction helps to retrieve query data and procedure to be taken care of as preventive measures to deal with the incident.
• Central data lake storage to collect and integrate all the raw data from different sources.
• Advanced AI and machine learning algorithms to improve the quality of events.

           XDR has 3 main functions in cloud and CSP which make it different from SIEM:

• identity management security – to capture data from cloud providers and activate identification functions to keep track of the identify anomalous activities.
• Logging data analyzer – to analyze tons of data and make meaningful decisions out of the information by eliminating the noise.
• Network flow analyzer – the large data and its complex behavior make it hard to trace the network in real-time. XDR provides a mechanism to identify and separate the vulnerable system and identify security breaches and respond accurately.

Comparison in SIEM and XDR:

Conclusion of the story:

In short, we can say XDR is an alternative for SIEM, which includes core functionality of SIEM and improvise them with the use of artificial intelligence by analyzing and correlating the high volume of data for a better accurate and automated response. It is completely NextGenXDR which will provide all the leverages to use machine learning to do preemptive measures against any cyberattack. SIEM security analysts will either innovate or die. Technology continuous innovation is compulsory for both SIEM and XDR.

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