With your BSc in Computer Science completed you have a ton of technical skills (ranging from coding to an in-depth understanding of computer architecture) to add to your resume. But post-graduate education looms and you’re tossing around various options, including doing an MCA (Master of computer applications).

An MCA builds on what you learned in your BSc, with fields of study including computational theory, algorithm design, and a host of mathematical subjects. Knowing that, you’re asking yourself “Can I do MCA after BSc Computer Science?” Let’s answer that question.

Eligibility for MCA After BSc Computer Science

The question of eligibility inevitably comes up when applying to study for an MCA, with three core areas you need to consider:

  • The minimum requirements
  • Entrance exams and admissions processes
  • Your performance in your BSc in Computer Science

Minimum Requirements

Starting with the basics, this is what you need to apply for to study for your MCA:

  • A Bachelor’s degree in a relevant computing subject (like computer science or computer applications.)
    • Some institutions accept equivalent courses and external courses as evidence of your understanding of computers
  • If you’re an international student, you’ll likely need to pass an English proficiency test
    • IELTS and TOEFL are the most popular of these tests, though some universities require a passing grade in a PTE test.
  • Evidence that you have the necessary financial resources to cover the cost of your MCA
    • Costs vary but can be as much as $40,000 for a one or two-year course.

Entrance Exams and Admission Processes

Some universities require you to take entrance exams, which can fall into the following categories:

  • National Level – You may have to take a national-level exam (such as India’s NIMCET) to demonstrate your basic computing ability.
  • State-Level – Most American universities don’t require state-level entrance exams, though some international universities do. For instance, India has several potential exams you may need to take, including the previously-mentioned NIMCET, the WBJECA, and the MAH MCA CET. All measure your computing competence, with most also requiring you to have completed your BSc in Computer Science before you can take the exam.
  • University-Specific – Many colleges, at least in the United States, require students to have passing grades in either the ACT or SATs, both of which you take at the high school level. Some colleges have also started accepting the CLT, which is a new test that positions itself as an alternative to the ACT or SAT. The good news is that you’ll have taken these tests already (assuming you study in the U.S.), so you don’t have to take them again to study for your MCA.

Your Performance Matters

How well you do in your computer science degree matters, as universities have limited intakes and will always favor the highest-performing students (mitigating circumstances notwithstanding). For example, many Indian universities that offer MCAs ask students to achieve at least a 50% or 60% CGPA (Cumulative Grade Point Average) across all modules before considering the student for their programs.

Benefits of Pursuing MCA After BSc Computer Science

Now you know the answer to “Can I do MCA after BSc Computer Science,” is that you can (assuming you meet all other criteria), you’re likely asking yourself if it’s worth it. These three core benefits make pursuing an MCA a great use of your time:

  • Enhanced Knowledge and Skills – If your BSc in Computer Science is like the foundation that you lay before building a house, an MCA is the house itself. You’ll be building up the basic skills you’ve developed, which includes getting to grips with more advanced programming languages and learning the intricacies of software development. Those who are more interested in the hardware side of things can dig into the specifics of networking.
  • Improved Career Prospects – Your career prospects enjoy a decent bump if you have an MCA, with Pay Scale noting the average base salary of an MCA graduate in the United States to be $118,000 per year. That’s about $15,000 more per year than the $103,719 salary Indeed says a computer scientist earns. Add in the prospect of assuming higher (or more senior) roles in a company and the increased opportunities for specialization that come with post-graduate studies and your career prospects look good.
  • Networking Opportunities – An MCA lets you delve deeper into the computing industry, exposing you to industry trends courtesy of working with people who are already embedded within the field. Your interactions with existing professionals work wonders for networking, giving you access to connections that could enhance your future career. Plus, you open the door to internships with more prestigious companies, in addition to participating in study projects that look attractive on a resume.

Career Prospects after MCA

After you’ve completed your MCA, the path ahead of you branches out, opening up the possibilities of entering the workforce or continuing your studies.

Job Roles and Positions

If you want to jump straight into the workforce once you have your MCA, there are several roles that will welcome you with open arms:

  • Software Developer/Engineer – Equipped with the advanced programming skills an MCA provides, you’re in a great position to take a junior software development role that can quickly evolve into a senior position.
  • Systems Analyst – Organization is the name of the game when you’re a systems analyst. These professionals focus on how existing computer systems are organized, coming up with ways to streamline IT operations to get companies operating more efficiently.
  • Database Administrator – Almost any software (or website) you care to mention has databases running behind the scenes. Database administrators organize these virtual “filing systems,” which can cover everything from basic login details for websites to complex financial information for major companies.
  • Network Engineer – Even the most basic office has a computer network (taking in desktops, laptops, printers, servers, and more) that requires management. A Network engineer provides that management, with a sprinkling of systems analysis that may help with the implementation of new networks.
  • IT Consultant – If you don’t want to be tied down to one company, you can take your talents on the road to serve as an IT consultant for companies that don’t have in-house IT teams. You’ll be a “Jack of all trades” in this role, though many consultants choose to specialize in either the hardware or software sides.

Industries and Sectors

Moving away from specific roles, the skills you earn through an MCA makes you desirable in a host of industries and sectors:

  • IT and Software Companies – The obvious choice for an MCA graduate, IT and software focus on hardware and software respectively. It’s here where you’ll find the software development and networking roles, though whether you work for an agency, as a solo consultant, or in-house for a business is up to you.
  • Government Organizations – In addition to the standard software and networking needs that government agencies face (like most workplaces), cybersecurity is critical in this field. According to Security Intelligence, 106 government or state agencies faced ransomware attacks in 2022, marking nearly 30 more attacks than they faced the year prior. You may be able to turn your knowledge to thwarting this rising tide of cyber-threats, though there are many less security-focused roles available in government organizations.
  • Educational Institutions – The very institutions from which you earn your MCA have need of the skills they teach. You’ll know this yourself from working first-hand with the complex networks of computing hardware the average university or school has. Throw software into the mix and your expertise can help educational institutions save money and provide better services to students.
  • E-Commerce and Startups – Entrepreneurs with big ideas need technical people to help them build the foundations of their businesses, meaning MCAs are always in demand at startups. The same applies to e-commerce companies, which make heavy use of databases to store customer and financial details.

Further Education and Research Opportunities

You’ve already taken a big step into further education by completing an MCA (which is a post-graduate course), so you’re in the perfect place to take another step. Choosing to work on getting your doctorate in computer science requires a large time commitment, with most programs taking between four and five years, but it allows for more independent study and research. The financial benefits may also be attractive, with Salary.com pointing to an average base salary of $120,884 (before bonuses and benefits) for those who take their studies to the Ph.D. level.

Top MCA Colleges and Universities

Drawing from data provided by College Rank, the following are the top three colleges for those interested in an MCA:

  • The University of Washington – A 2.5-year course that is based in the college’s Seattle campus, the University of Washington’s MCA is a part-time program that accepts about 60% of the 120 applicants it receives each year.
  • University of California-Berkeley (UCB) – UCB’s program is a tough one to get into, with students needing to achieve a minimum 3.0 Grade Point Average (GPA) on top of having three letters of recommendation. But once you’re in, you’ll join a small group of students focused on research into AI, database management, and cybersecurity, among other areas.
  • University of Illinois – Another course that has stringent entry requirements, the University of Illinois’s MCA program requires you to have a 3.2 GPA in your BSc studies to apply. It’s also great for those who wish to specialize, as you get a choice of 11 study areas to focus on for your thesis.

Conclusion

Pursuing an MCA after completing your BSc in Computer Science allows you to build up from your foundational knowledge. Your career prospects open up, meaning you’ll spend less time “working through the ranks” than you would if you enter the workforce without an MCA. Plus, the data shows that those with MCAs earn an average of about $15,000 per year more than those with a BSc in Computer Science.

If you’re pondering the question, “Can I do MCA after BSc Computer Science,” the answer comes down to what you hope to achieve in your career. Those interested in positions of seniority, higher pay scales, and the ability to specialize in specific research areas may find an MCA attractive.

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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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