Data management is one of the biggest challenges for modern businesses. The more information that enters a company, the harder it is to stay on top of all of it. However, successful owners wouldn’t be where they are if they threw in the towel. They go out of their way to find a solution to solve this problem.

Enter database management systems (DBMSs). A database management system is a program that allows you to store and organize information more easily.

The importance of a DBMS can’t be overstressed. It can be a light at the end of the tunnel for many organizations. For example, it helps optimize performance across the board, increase productivity, and reduce cybersecurity risks.

This article will take a closer look at database management systems. We’ll explore the concept of database management systems, the basic principles of database management systems, and other essential aspects.

Types of Database Management Systems

We’ve defined a “database management system.” Next, it only seems natural to kick this introduction to database systems off with an examination of the types of software that address this issue.

Hierarchical DBMS

Much of today’s world is about hierarchies. There are hierarchies in your family, in the sequence of actions when starting a car, and in many other aspects of life.

Hierarchy also permeates data in the form of hierarchical database management systems. These solutions typically use tree-like formats to organize data from top to bottom or from bottom to top. Each approach is characterized by “parent and children” information.

Regardless of the approach, one thing’s for sure – children can’t have multiple parents, but parents can have multiple children. The same rings true for data points, meaning they can’t have three or four “parents.”

Network DBMS

A network database management system is similar to the hierarchical type. However, the two aren’t carbon copies of each other. The biggest difference is that “child” data can have more “parents” in a network DBMS. It allows IT professionals to accommodate complex information clusters.

Relational DBMS

The DBMS market is expected to soar to over $150 billion by 2030. You might think that such a valuable industry is only home to advanced solutions, but that’s not quite true.

Relational database management systems have a relatively simple premise – organizing data in columns and rows. In this respect, they work like Microsoft Excel and some other basic programs.

Object-Oriented DBMS

Object-oriented models use, well, models. They store all sorts of user information in structures known as classes.


Google and other internet giants process billions of terabytes of data daily. They need a robust database management solution that lets them stay on top of such vast quantities.

Salvation comes in the form of NoSQL. This system is incredibly scalable and flexible because it doesn’t require data set combinations. Therefore, it’s perfect for large-scale, big-data operations.


Finding a perfect database management system sometimes feel like looking for a needle in a haystack. However, it becomes an easier task if you have clear priorities. If you want a platform that combines the scalability of NoSQL and ACID compliance, check out NewSQL. It offers unrivaled data integrity, which also increases security.

Components of a Database Management System

Our introduction to database management systems has covered the DBMS definition, which answers the question “What is DBMS?” We’ve also explored various types of database management systems. Now let’s delve into the components of these solutions.

Database Engine

The engine of a database is like the foundation of a house. This core element processes every information and query that enters the system.

Data Definition Language (DDL)

You can’t have a house without a foundation, and you can’t build one without a roof either. That’s how important a DDL is to a database. It ensures pieces of information can interact with each other and facilitates data retrieval. It also allows you to modify certain parts of the structure.

Data Manipulation Language (DML)

The four basic operations of a database system are create, read, update, and delete. The DML is responsible for executing these tasks.

Data Control Language (DCL)

You’ve constructed the foundation of your house, but you need to keep intruders from entering with a door. A database also needs a door, and a DCL is the best solution. It determines who can access your system.

Transaction Management

Internal transactions are common in all databases. A transaction management system controls them to ensure ACID compliance.

Database Recovery

Database failure is like a devastating house fire that destroys everything – you don’t give up and do nothing. Instead, you rebuild the structure.

Database recovery works the same. It’s a set of tools that enables you to reconstruct your database from scratch.

Applications of Database Management Systems

A DBMS, especially a DBMS full form, has a wide range of applications. The technology is as versatile as a hybrid vehicle, meaning you can use it practically anywhere. Here’s where you can regularly find database management systems:

  • Banking and finance – Financial institutions need a fully functional DBMS to process loan, account, and deposit information.
  • Healthcare – Hospitals and other healthcare organizations have numerous patient records. Managing them is much easier with a DBMS.
  • Telecommunications – Have you ever thought about how your cell phone carrier maintains your information and that of millions of others? The answer lies in a DBMS. It stores phone records and bills, among other crucial information.
  • Education – If you’re a student, your school or college needs to keep track of your attendance, marks, and assignments. The best way to do so is to set up a database management system.
  • E-commerce – How do various e-commerce platforms streamline your shopping experience? They implement a DBMS to recommend products and services, record your habits, and memorize your payment information.
  • Government and public sector – The applications of database management systems for government are virtually endless. These include national security, voter registration, and social security.

Principles of Database Management Systems

Although there are numerous database management systems, they take the same approach to storing and organizing information. Each platform needs to follow these principles:

  • Data independence – This principle is pretty self-explanatory. If you can change a piece of information in your database, your structure is independent.
  • Data consistency – You might store the same folder in different locations on your computer for backup purposes. You should be able to do the same with data in your database without altering the information. If the data appears differently in various locations, it’s inconsistent.
  • Data integrity – The last thing you want is to work with corrupt information. It can affect the rest of the database and grant unauthorized personnel access to your data. But none of this is an issue if your system has high data integrity.
  • Data security – Data security is like home security – you don’t want invaders to steal your possessions. On the same note, you don’t want cyber criminals to tap into the system and compromise sensitive information.
  • Data recovery – If your system shuts down unexpectedly, you need to be able to retrieve your information in its last saved state.
  • Concurrency control – A database management system isn’t designed to perform just one operation. It can run numerous tasks simultaneously, which is why you need concurrency control to manage the execution of those operations.

Examples of Popular Database Management Systems

Here are some of the most common database management systems:

  • Oracle database – A relational system that comes in two versions: cloud and on-premises.
  • Microsoft SQL server – Another relational program, which is built on the SQL architecture.
  • MySQL – Companies with large databases use MySQL to organize and control massive amounts of information.
  • PostgreSQL – This is an object-relational database that complies with the SQL environment.
  • MongoDB – A scalable and flexible system with optimized indexing and queries.
  • IBM Db2 – If you’re looking for a platform developed by a tech giant, IBM Db2 is a great choice. It’s perfect for real-time information analysis.

Notes and Basics of Database Management Systems

To wrap up the discussion about database systems, we’ll cover the basics of database management systems and database management system notes:

  • Importance of data modeling – Just as you tidy up your room to find clothes more easily, you want to model data to retrieve information effortlessly. The process eliminates redundant details for easier management.
  • Database normalization – Another great way to reduce errors in a DBMS is to perform database normalization. It allows for accurate modifications and helps improve your workflow.
  • Indexing and query optimization – By indexing the data in your system, you decrease the information your queries need to analyze. In turn, this leads to higher database efficiency.
  • Backup and recovery strategies – IT professionals must have sound backup and recovery strategies in place. They reduce downtime associated with information loss after shutdowns or errors.
  • Database administration and maintenance – A database administrator should formulate the overall strategy for the entire system. It simplifies maintenance and lowers the risk of errors.

The Concept of DBMS Demystified

Much of cutting-edge technology is an enigma, but hopefully, that’s no longer the case with database management systems. Hierarchical, network, relational, and other systems are instrumental in organizing information and making it more accessible. The onus is on IT professionals to master each solution applicable to their industry to improve their company’s workflows.

Future trends may put extra emphasis on this need. As most databases migrate to the cloud and organizations prioritize cyber security, IT experts will need to adapt their approach to database management.

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Cyber Threat Landscape 2024: Human-Centric Cyber Threats
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 17, 2024 9 min read

Human-centric cyber threats have long posed a serious issue for organizations. After all, humans are often the weakest link in the cybersecurity chain. Unfortunately, when artificial intelligence came into the mix, it only made these threats even more dangerous.

So, what can be done about these cyber threats now?

That’s precisely what we asked Tom Vazdar, the chair of the Enterprise Cybersecurity Master’s program at the Open Institute of Technology (OPIT), and Venicia Solomons, aka the “Cyber Queen.”

They dedicated a significant portion of their “Cyber Threat Landscape 2024: Navigating New Risks” master class to AI-powered human-centric cyber threats. So, let’s see what these two experts have to say on the topic.

Human-Centric Cyber Threats 101

Before exploring how AI impacted human-centric cyber threats, let’s go back to the basics. What are human-centric cyber threats?

As you might conclude from the name, human-centric cyber threats are cybersecurity risks that exploit human behavior or vulnerabilities (e.g., fear). Even if you haven’t heard of the term “human-centric cyber threats,” you’ve probably heard of (or even experienced) the threats themselves.

The most common of these threats are phishing attacks, which rely on deceptive emails to trick users into revealing confidential information (or clicking on malicious links). The result? Stolen credentials, ransomware infections, and general IT chaos.

How Has AI Impacted Human-Centric Cyber Threats?

AI has infiltrated virtually every cybersecurity sector. Social engineering is no different.

As mentioned, AI has made human-centric cyber threats substantially more dangerous. How? By making them difficult to spot.

In Venicia’s words, AI has allowed “a more personalized and convincing social engineering attack.”

In terms of email phishing, malicious actors use AI to write “beautifully crafted emails,” as Tom puts it. These emails contain no grammatical errors and can mimic the sender’s writing style, making them appear more legitimate and harder to identify as fraudulent.

These highly targeted AI-powered phishing emails are no longer considered “regular” phishing attacks but spear phishing emails, which are significantly more likely to fool their targets.

Unfortunately, it doesn’t stop there.

As AI technology advances, its capabilities go far beyond crafting a simple email. Venicia warns that AI-powered voice technology can even create convincing voice messages or phone calls that sound exactly like a trusted individual, such as a colleague, supervisor, or even the CEO of the company. Obey the instructions from these phone calls, and you’ll likely put your organization in harm’s way.

How to Counter AI-Powered Human-Centric Cyber Threats

Given how advanced human-centric cyber threats have gotten, one logical question arises – how can organizations counter them? Luckily, there are several ways to do this. Some rely on technology to detect and mitigate threats. However, most of them strive to correct what caused the issue in the first place – human behavior.

Enhancing Email Security Measures

The first step in countering the most common human-centric cyber threats is a given for everyone, from individuals to organizations. You must enhance your email security measures.

Tom provides a brief overview of how you can do this.

No. 1 – you need a reliable filtering solution. For Gmail users, there’s already one such solution in place.

No. 2 – organizations should take full advantage of phishing filters. Before, only spam filters existed, so this is a major upgrade in email security.

And No. 3 – you should consider implementing DMARC (Domain-based Message Authentication, Reporting, and Conformance) to prevent email spoofing and phishing attacks.

Keeping Up With System Updates

Another “technical” move you can make to counter AI-powered human-centric cyber threats is to ensure all your systems are regularly updated. Fail to keep up with software updates and patches, and you’re looking at a strong possibility of facing zero-day attacks. Zero-day attacks are particularly dangerous because they exploit vulnerabilities that are unknown to the software vendor, making them difficult to defend against.

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Nurturing a Culture of Skepticism

The key component of the human-centric cyber threats is, in fact, humans. That’s why they should also be the key component in countering these threats.

At an organizational level, numerous steps are needed to minimize the risks of employees falling for these threats. But it all starts with what Tom refers to as a “culture of skepticism.”

Employees should constantly be suspicious of any unsolicited emails, messages, or requests for sensitive information.

They should always ask themselves – who is sending this, and why are they doing so?

This is especially important if the correspondence comes from a seemingly trusted source. As Tom puts it, “Don’t click immediately on a link that somebody sent you because you are familiar with the name.” He labels this as the “Rule No. 1” of cybersecurity awareness.

Growing the Cybersecurity Culture

The ultra-specific culture of skepticism will help create a more security-conscious workforce. But it’s far from enough to make a fundamental change in how employees perceive (and respond to) threats. For that, you need a strong cybersecurity culture.

Tom links this culture to the corporate culture. The organization’s mission, vision, statement of purpose, and values that shape the corporate culture should also be applicable to cybersecurity. Of course, this isn’t something companies can do overnight. They must grow and nurture this culture if they are to see any meaningful results.

According to Tom, it will probably take at least 18 months before these results start to show.

During this time, organizations must work on strengthening the relationships between every department, focusing on the human resources and security sectors. These two sectors should be the ones to primarily grow the cybersecurity culture within the company, as they’re well versed in the two pillars of this culture – human behavior and cybersecurity.

However, this strong interdepartmental relationship is important for another reason.

As Tom puts it, “[As humans], we cannot do anything by ourselves. But as a collective, with the help within the organization, we can.”

Staying Educated

The world of AI and cybersecurity have one thing in common – they never sleep. The only way to keep up with these ever-evolving worlds is to stay educated.

The best practice would be to gain a solid base by completing a comprehensive program, such as OPIT’s Enterprise Cybersecurity Master’s program. Then, it’s all about continuously learning about new developments, trends, and threats in AI and cybersecurity.

Conducting Regular Training

For most people, it’s not enough to just explain how human-centric cyber threats work. They must see them in action. Especially since many people believe that phishing attacks won’t happen to them or, if they do, they simply won’t fall for them. Unfortunately, neither of these are true.

Approximately 3.4 billion phishing emails are sent each day, and millions of them successfully bypass all email authentication methods. With such high figures, developing critical thinking among the employees is the No. 1 priority. After all, humans are the first line of defense against cyber threats.

But humans must be properly trained to counter these cyber threats. This training includes the organization’s security department sending fake phishing emails to employees to test their vigilance. Venicia calls employees who fall for these emails “clickers” and adds that no one wants to be a clicker. So, they do everything in their power to avoid falling for similar attacks in the future.

However, the key to successful employee training in this area also involves avoiding sending similar fake emails. If the company keeps trying to trick the employees in the same way, they’ll likely become desensitized and less likely to take real threats seriously.

So, Tom proposes including gamification in the training. This way, the training can be more engaging and interactive, encouraging employees to actively participate and learn. Interestingly, AI can be a powerful ally here, helping create realistic scenarios and personalized learning experiences based on employee responses.

Following in the Competitors’ Footsteps

When it comes to cybersecurity, it’s crucial to be proactive rather than reactive. Even if an organization hasn’t had issues with cyberattacks, it doesn’t mean it will stay this way. So, the best course of action is to monitor what competitors are doing in this field.

However, organizations shouldn’t stop with their competitors. They should also study other real-world social engineering incidents that might give them valuable insights into the tactics used by the malicious actors.

Tom advises visiting the many open-source databases reporting on these incidents and using the data to build an internal educational program. This gives organizations a chance to learn from other people’s mistakes and potentially prevent those mistakes from happening within their ecosystem.

Stay Vigilant

It’s perfectly natural for humans to feel curiosity when it comes to new information, anxiety regarding urgent-looking emails, and trust when seeing a familiar name pop up on the screen. But in the world of cybersecurity, these basic human emotions can cause a lot of trouble. That is, at least, when humans act on them.

So, organizations must work on correcting human behaviors, not suppressing basic human emotions. By doing so, they can help employees develop a more critical mindset when interacting with digital communications. The result? A cyber-aware workforce that’s well-equipped to recognize and respond to phishing attacks and other cyber threats appropriately.

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Cyber Threat Landscape 2024: The AI Revolution in Cybersecurity
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 17, 2024 9 min read

There’s no doubt about it – artificial intelligence has revolutionized almost every aspect of modern life. Healthcare, finance, and manufacturing are just some of the sectors that have been virtually turned upside down by this powerful new force. Cybersecurity also ranks high on this list.

But as much as AI can benefit cybersecurity, it also presents new challenges. Or – to be more direct –new threats.

To understand just how serious these threats are, we’ve enlisted the help of two prominent figures in the cybersecurity world – Tom Vazdar and Venicia Solomons. Tom is the chair of the Master’s Degree in Enterprise Cybersecurity program at the Open Institute of Technology (OPIT). Venicia, better known as the “Cyber Queen,” runs a widely successful cybersecurity community looking to empower women to succeed in the industry.

Together, they held a master class titled “Cyber Threat Landscape 2024: Navigating New Risks.” In this article, you get the chance to hear all about the double-edged sword that is AI in cybersecurity.

How Can Organizations Benefit From Using AI in Cybersecurity?

As with any new invention, AI has primarily been developed to benefit people. In the case of AI, this mainly refers to enhancing efficiency, accuracy, and automation in tasks that would be challenging or impossible for people to perform alone.

However, as AI technology evolves, its potential for both positive and negative impacts becomes more apparent.

But just because the ugly side of AI has started to rear its head more dramatically, it doesn’t mean we should abandon the technology altogether. The key, according to Venicia, is in finding a balance. And according to Tom, this balance lies in treating AI the same way you would cybersecurity in general.

Keep reading to learn what this means.

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Implement a Governance Framework

In cybersecurity, there is a governance framework called ISO/IEC 27000, whose goal is to provide a systematic approach to managing sensitive company information, ensuring it remains secure. A similar framework has recently been created for AI— ISO/IEC 42001.

Now, the trouble lies in the fact that many organizations “don’t even have cybersecurity, not to speak artificial intelligence,” as Tom puts it. But the truth is that they need both if they want to have a chance at managing the risks and complexities associated with AI technology, thus only reaping its benefits.

Implement an Oversight Mechanism

Fearing the risks of AI in cybersecurity, many organizations chose to forbid the usage of this technology outright within their operations. But by doing so, they also miss out on the significant benefits AI can offer in enhancing cybersecurity defenses.

So, an all-out ban on AI isn’t a solution. A well-thought-out oversight mechanism is.

According to Tom, this control framework should dictate how and when an organization uses cybersecurity and AI and when these two fields are to come in contact. It should also answer the questions of how an organization governs AI and ensures transparency.

With both of these frameworks (governance and oversight), it’s not enough to simply implement new mechanisms. Employees should also be educated and regularly trained to uphold the principles outlined in these frameworks.

Control the AI (Not the Other Way Around!)

When it comes to relying on AI, one principle should be every organization’s guiding light. Control the AI; don’t let the AI control you.

Of course, this includes controlling how the company’s employees use AI when interacting with client data, business secrets, and other sensitive information.

Now, the thing is – people don’t like to be controlled.

But without control, things can go off the rails pretty quickly.

Tom gives just one example of this. In 2022, an improperly trained (and controlled) chatbot gave an Air Canada customer inaccurate information and a non-existing discount. As a result, the customer bought a full-price ticket. A lawsuit ensued, and in 2024, the court ruled in the customer’s favor, ordering Air Canada to pay compensation.

This case alone illustrates one thing perfectly – you must have your AI systems under control. Tom hypothesizes that the system was probably affordable and easy to implement, but it eventually cost Air Canada dearly in terms of financial and reputational damage.

How Can Organizations Protect Themselves Against AI-Driven Cyberthreats?

With well-thought-out measures in place, organizations can reap the full benefits of AI in cybersecurity without worrying about the threats. But this doesn’t make the threats disappear. Even worse, these threats are only going to get better at outsmarting the organization’s defenses.

So, what can the organizations do about these threats?

Here’s what Tom and Venicia suggest.

Fight Fire With Fire

So, AI is potentially attacking your organization’s security systems? If so, use AI to defend them. Implement your own AI-enhanced threat detection systems.

But beware – this isn’t a one-and-done solution. Tom emphasizes the importance of staying current with the latest cybersecurity threats. More importantly – make sure your systems are up to date with them.

Also, never rely on a single control system. According to our experts, “layered security measures” are the way to go.

Never Stop Learning (and Training)

When it comes to AI in cybersecurity, continuous learning and training are of utmost importance – learning for your employees and training for the AI models. It’s the only way to ensure all system aspects function properly and your employees know how to use each and every one of them.

This approach should also alleviate one of the biggest concerns regarding an increasing AI implementation. Namely, employees fear that they will lose their jobs due to AI. But the truth is, the AI systems need them just as much as they need those systems.

As Tom puts it, “You need to train the AI system so it can protect you.”

That’s why studying to be a cybersecurity professional is a smart career move.

However, you’ll want to find a program that understands the importance of AI in cybersecurity and equips you to handle it properly. Get a master’s degree in Enterprise Security from OPIT, and that’s exactly what you’ll get.

Join the Bigger Fight

When it comes to cybersecurity, transparency is key. If organizations fail to report cybersecurity incidents promptly and accurately, they not only jeopardize their own security but also that of other organizations and individuals. Transparency builds trust and allows for collaboration in addressing cybersecurity threats collectively.

So, our experts urge you to engage in information sharing and collaborative efforts with other organizations, industry groups, and governmental bodies to stay ahead of threats.

How Has AI Impacted Data Protection and Privacy?

Among the challenges presented by AI, one stands out the most – the potential impact on data privacy and protection. Why? Because there’s a growing fear that personal data might be used to train large AI models.

That’s why European policymakers sprang into action and introduced the Artificial Intelligence Act in March 2024.

This regulation, implemented by the European Parliament, aims to protect fundamental rights, democracy, the rule of law, and environmental sustainability from high-risk AI. The act is akin to the well-known General Data Protection Regulation (GDPR) passed in 2016 but exclusively targets the use of AI. The good news for those fearful of AI’s potential negative impact is that every requirement imposed by this act is backed up with heavy penalties.

But how can organizations ensure customers, clients, and partners that their data is fully protected?

According to our experts, the answer is simple – transparency, transparency, and some more transparency!

Any employed AI system must be designed in a way that doesn’t jeopardize anyone’s privacy and freedom. However, it’s not enough to just design the system in such a way. You must also ensure all the stakeholders understand this design and the system’s operation. This includes providing clear information about the data being collected, how it’s being used, and the measures in place to protect it.

Beyond their immediate group of stakeholders, organizations also must ensure that their data isn’t manipulated or used against people. Tom gives an example of what must be avoided at all costs. Let’s say a client applies for a loan in a financial institution. Under no circumstances should that institution use AI to track the client’s personal data and use it against them, resulting in a loan ban. This hypothetical scenario is a clear violation of privacy and trust.

And according to Tom, “privacy is more important than ever.” The same goes for internal ethical standards organizations must develop.

Keeping Up With Cybersecurity

Like most revolutions, AI has come in fast and left many people (and organizations) scrambling to keep up. However, those who recognize that AI isn’t going anywhere have taken steps to embrace it and fully benefit from it. They see AI for what it truly is – a fundamental shift in how we approach technology and cybersecurity.

Those individuals have also chosen to advance their knowledge in the field by completing highly specialized and comprehensive programs like OPIT’s Enterprise Cybersecurity Master’s program. Coincidentally, this is also the program where you get to hear more valuable insights from Tom Vazdar, as he has essentially developed this course.

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