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Monthly Archives: February 2021

social engineering

Social Engineering

In this post, we’re going to talk about the most common social engineering attacks and different ways of stopping them.

We’ll also explain:

  • What is social engineering?
  • Why do social engineering attacks happen?
  • What do these attacks impact?
  • Worst cases of online social engineering.

So, if you want to know the most effective ways of protecting your company from widely spread social engineering attacks, keep reading.

Let’s begin.

What is social engineering?

Social engineering represents malicious (online) activities that trick people into revealing confidential information or providing access to resources (usually money).

RPA (robotics process automation) can be one of the solutions to this problem, as it can perform different manual tasks such as accounts validation and verification of incoming mail.

Examples of top social engineering attacks

social engineering cybercrime

Cybercriminals have learned various ways of convincing people to transfer money, provide information, or download a file infected with malware. Five of the most common social engineering attacks are:

Phishing

One of the most common types of social engineering attacks. Attackers use emails and text messages that contain links to malicious websites, or attachments with malware. It is hard to ignore these cyberattacks because they create a sense of urgency, curiosity, or fear among victims. In 2016, Verizon Enterprise reported that 30 percent of phishing emails were opened by the recipient and 13 percent of those clicked on the link or attachment. 

Spear-phishing

Spear-phishing targets specific individuals or enterprises. These attacks are much harder to detect because the e-mail is signed and looks like one a victim would normally receive from their IT support, for example. As a test spear-phishing attack, a security consultant pretended to be an IT engineer. He found out that 85 percent of employees whom he contacted gave out information which he had requested. In one of the biggest social engineering attacks – Carbanak -attackers managed to record how the company’s system works and steal almost $1 billion dollars.

Baiting

Cybercriminals use physical media (flash drives with labels like “payroll list”) or online forms (appealing ads) to lure users into a trap. Those items seem beneficial but are actually loaded with malware.

Scareware

This type of attack often comes in the form of popup banners and alerts on the web browser. Users think their system is infected with malware, and they install software that should help them, but, in reality, is malware itself.

Pretexting

The attacker usually pretends to be a co-worker, company supplier, police, or bank official. In that way, attackers can easily get users to believe them and steal security numbers, personal addresses and phone numbers, or bank records from them.

The challenges of social engineering security

Social engineering incidents happen because of mistakes made by people. There are three top challenges of social engineering security are:

#1 Fear

Attackers use fear, stress, and anxiety that comes with filing taxes, for example, to send emails to victims stating they are under investigation for tax fraud.

#2 Curiosity

Cybercriminals use events and news to take advantage of human curiosity. They trick people into opening emails by offering leaked data about a current trend or topic. For example, when Robin Williams passed away, a phishing message invited users to click a link and see an exclusive video of him saying his final goodbye.

#3 Helpfulness

An example of this is when an email sent out to the staff requesting accounting database password to ensure the manager pay everyone on time, and employees take the bait and send it believing they are helping out.

How to stop social engineering attacks

social engineering attacks

There are different ways to stop these attacks from happening. Some of them are simple but go a long way in protecting your company.

  1. Don’t open emails and attachments from suspicious sources. If you don’t know the sender, don’t open it. If you know them, but are suspicious about the request, check and confirm they did send it before acting on the request.
  2. Multifactor authentication can protect your account in case of an attack.
  3. Implement modern antivirus/antimalware software. It can identify and remove malicious emails before they reach an employee’s inbox.

How to prevent employees from avoiding security protocols

As a way to prevent employees from avoiding security protocols you should:

  1. Create security policies that clarify whom employees can share information with and how.
  2. Create official channels for staff to contact security and IT personnel.

How to train end users to avoid social engineering

Social engineering consequences can be prevented by informing employees and training them to detect and avoid them.

  1. Provide regular security awareness training that outlines common strategies that attackers use.
  2. Training should be personalized – employees should relate to content and situations used in it.
  3. Use simulations and tests to check how well employees are prepared to prevent these attacks.

If you’re worried about social engineering attacks, Demakis Technologies can help you!

Contact us to find out how you can use our cyber security services to protect you, your employees, your data, and your company from attacks.

Robotics and MSP

Robotics and MSP

Today, we’ll discuss the relationship between robotics and managed service providers.

Specifically, we’ll respond to the following questions

  • What is robotic process automation?
  • How does it work? And what makes it stand out?
  • How can it benefit your business?
  • What are managed services? And what’s their role in automation?

So, if you’re looking to leverage robotic process automation as a service to optimize your business, you’ll enjoy this article (regardless of whether you’re in retail, banking, finance, telecommunications, or IT).

Let’s get started!

What is robotic process automation?

Robotic process automation (RPA) is a SaaS (software-as-service) solution that enables robots (or bots) to automate and perform specific tasks without manual support.

These tasks are often repetitive, exacting, and time-consuming. So using bots to carry them out reduces the need for human input.

At the same time, automation lowers the potential for errors to occur. As machines, unlike humans, don’t have to think about doing a task – they just do it.

Tasks cover a variety of processes such as communication, data processing, financial transactions, and many others. Tasks also range from data mitigation to help desk support.

The benefits of robotic process automation

robotic process automation

A clear benefit of RPA is that it replaces humans by automatically performing repetitive and exacting tasks.

Think of RPA as robotics and industrial automation.

For example, machines and robotics in the manufacturing industry substitute people on the assembly line. As a result, mechanization lowers the demand for a large workforce at a factory.

Businesses benefit from RPA in the same way. In fact, it can reduce employee workload by as much as 20%.

Another advantage is visibility. All of the tasks that RPAs perform are transparent. And businesses just need a few operators to manage them and ensure absolute precision.

And less work means that a highly-skilled or creative staff can perform the same amount of work as a large pool of employees.

All of this helps you to rightsize your workforce. And that significantly reduces monthly overhead, while increasing their efficiency, and the efficiency of your organization in general.

How is RPA different from other automation?

Here, the main difference is the use of RPA within the front-end.

Because it can integrate with any type of existing system that you own, you can automate task-by-task. And since you target a single task, you won’t impact others or the process that it belongs to.

This allows you to create a fully scalable and sustainable ecosystem within a rapidly changing environment.

Due to the major changes in automation, RPA avoids traditional efforts that focus on larger-scale changes.

Instead, RPA handles only menial tasks of little value, which are still vital and necessary for your business.

Usually, these tasks are what disrupt workflow and place a burden on your teams. So automating them with RPA makes perfect sense.

What kind of industries can use RPA?

Robotics and managed services provider

There are two different types of industries that use robotics: manufacturers and service providers.

While manufacturing companies use actual robots in combination with the software, service providers typically rely solely on RPA.

The following industries apply the software to both B2B and B2C activities (which are almost all of them):

  • IT
  • Retail
  • Healthcare
  • Finance
  • Telecommunications
  • Food and beverage

What are managed services?

Managed services are third-party services that you can purchase to handle activities beyond your capacity.

Managed service providers (MSPs) usually handle highly specialized and advanced activities, like SaaS or maintaining IT infrastructure.

MSPs also provide a greater level of support and have many skilled professionals on hand who are available 24/7.

In the case of IT, for example, a company may outsource to an MSP rather than employ an entire IT staff internally (to adopt that process or reduce operational expenditure).

MSPs work on a flat-fee basis. They are also certified according to industry standards and the latest IT managed service provider trends.

MSPs are equipped with hardware and software that can meet their clients’ needs, including developers, troubleshooting, and field service support.

What is the relationship between robotics and MSP?

managed service providers robotics

As companies today follow the IT help desk outsourcing trends, we’ll see RPA handle a much greater percentage of IT support.

Because of that and the lack of tech capabilities among those businesses, more and more of them will have to outsource the implementation of RPA to MSPs.

At the same time, companies may rely on MSP for support when it comes to handling the cybersecurity of RPAs and the data it collects.

Just as we are witnessing industrial automation and robotics as an integral part of it, total automation isn’t far away.

As you read this, machine learning and advanced AI programming are already trying to emulate IT personnel.

What are the predictions for the future of the Internet?

Both robotics and MSPs contribute to the Internet of Things (IoT) and an even greater exchange of data over the Internet.

As for the predictions for the future of the internet, business people all over the world agree on one thing:

The individual roles humans and AI each have, and their relationship to each other.

So, the question remains open: how will we communicate over the Internet?

Will we be speaking to RPAs managed by MSPs twenty years from now?

If you’d like to be ahead of the game, learn how Demakis Technologies can help your company implement managed services, and contact us now!

Uncommon Cybersecurity Threats

10 Uncommon Cybersecurity Threats Webinar

Hello, everyone! Welcome to new webinar at “Tea Time With Demakis”. In this webinar we will be talking about 10 Uncommon Cybersecurity Threats you need to avoid. The Cyber World or the Internet is a vast place where the sharing of data has its pros and cons. We all know the pros as our lives are now much easier, thanks to the Internet. However, not many of us are aware of the external cyber threats that go hand in hand with data Cybersecurity Threats.  

Learn about Cloud Jacking, The threat to IoT Devices, Deepfake, Mobile Malware, 5G-to-Wi-Fi Security Vulnerabilities, Insider Cybersecurity Threats, Application Programming Interface (API) Vulnerabilities and Breaches, Email Initiated Infections, User-Initiated Website Visit and DDoS.

If you’d like to learn more about Cybersecurity threat mitigation for your business, contact us here at Demakis Technologies.

Outsourcing IT Webinar

Outsourcing IT – Demakis Technologies Webinar

Hello everyone! Welcome to new webinar at “Tea Time With Demakis”. In this webinar you will learn more about Outsourced IT programs, outsourcing contracts, the benefits and the risks of Outsourcing that need resolution. 

Find out what are the terms Outsourcing contract and outsourced IT.  You can also learn the pros and cons of outsourcing and the benefits of IT outsourcing. The strategies, cost management, and productivity of companies were also defined.  If you’d like to learn more about outsourcing your IT, contact us here at Demakis Technologies! 

Data Mining

Data Mining

We’ve recently discussed data collection and data-selling technology on our blog. But what happens to big data once you capture it? You have to process it somehow. And that analysis and extraction of information from big data is data mining.

But understanding data mining is also more complex than that. So if you want to know more about this topic, you’ll enjoy this article. Let’s begin.

What is data mining?

Data mining is the process of analyzing large volumes of raw data (data sets) to extract information from it.

Typically, this information includes patterns, irregularities, and connections within that data.

Based on the findings, individuals and organizations can extract value from big data.

In most cases, this means generating statistical forecasts that predict risks, opportunities, and outcomes within the context of that data.

In other words: data mining is the process of finding meaningful information in big data.

How to extract data patterns in statistics?

understanding data mining

Technology is critical if you want to extract meaningful information from data sets. The reason for this is the volume, complexity, and structure of big data.

Typically, the data sets you capture can be:

  • Structured
  • Unstructured
  • Semi-structured

Even with the simplest, structured model, manually analyzing large data sets requires a lot of time and resources.

So instead, researchers use software and innovative technology like artificial intelligence (AI) and machine learning.

These technologies can automatically process and analyze data sets to uncover patterns from them.

You can then use these statistical patterns in the data and apply them practically.

For example, when launching a new product, you’ll want to know what your target audience is, and whether they’ll welcome its arrival.

On the other hand, as huge as big data is, it’s never complete. It’s always provisional. So instead of applying it directly, you may first want to test it against more or other sample data.

In the product launch example, you could examine its effectiveness against existing products through a focus group.

What are some data mining techniques?

what are some data mining techniques

New technologies contributing to data mining are continuing to evolve. As they become more accessible, data miners can use them to adopt them and develop new techniques to extract information from big data.

And according to the International Journal of Computer Applications, there are 16 different data mining techniques in use today:

  1. Data cleaning and preparation
  2. Tracking patterns
  3. Classification
  4. Association
  5. Outlier detection
  6. Clustering
  7. Regression
  8. Prediction
  9. Sequential patterns
  10. Decision trees
  11. Statistical techniques
  12. Visualization
  13. Neural networks
  14. Data warehousing
  15. Long-term memory processing
  16. Machine learning and artificial intelligence

Who can use data mining?

While you’ll need the support of managed tech services, the importance of data mining can be felt across fields and industries.

A data mining example and its common use is science.

Researchers can collect data sets from across their field and use AI and machine learning to analyze and extract crucial results and findings for their research projects (regardless of their location).

But the addition of data mining techniques and algorithms isn’t limited to science alone. And there are many other uses for it in both the private and public sectors.

Here are a few types of data mining uses:

  • People search
  • Credit reporting
  • Market testing
  • Advertising effectiveness
  • Researching political outcomes
  • Risk evaluation
  • And many others
data science news

Successful data mining steps you can take

Now, let’s take a look at how you can effectively apply data mining techniques.

Here’s a quick step-by-step guide on how you can make the best use of data mining:

#1 Choose the project carefully.

If you want to extract maximum value from big data, align your data mining goals with your top business goal.

When you know which information you need out of big data, it’s easier to collect, process, and analyze the right data to acquire it.

#2 Collect a lot of data from multiple sources

This is straightforward. The more data sets you use, the more varied the data is, and the greater the accuracy you’ll achieve for your forecasts using that information.

This step has the biggest impact on user behavior analytics and predictive analytics.

#3 Simplify your sampling strategy

Even when you use powerful data mining platforms to process large data sets, try analyzing smaller subsets of data instead.

Simplifying samples to make them clear and concise is the key to generating the best outcome from your efforts.

#4 Always use holdout samples

A holdout sample is a benchmark. It’s a reference point that you can use to evaluate the validity of your predictive models.

This ensures that your predictions aren’t based on other predictive patterns from a defined set of data. But, instead, on actual estimates from the real world.

#5 Refresh your models frequently

Once you generate a forecast or data prediction, start applying it to your research, business, or operations. But don’t hold onto it forever.

These models are only as good as the relevance of the patterns that you find. And as the data changes, it will affect the validity of your forecasts.

That’s why it’s essential to feed new data to the models every week, day, or even hour.

If you’d like to learn more about how Demakis Technologies can help you manage your data, contact us.