Top Five Popular Cybersecurity Certifications and Courses for 2024

In today’s world, where cyber attacks are becoming more sophisticated day by day, cybersecurity is becoming an essential aspect of running a business. Looking at the scenario, organizations hire cybersecurity professionals to upgrade their business security. They will look for individuals who are cybersecurity certified, along with having knowledge and experience on the subject, to perform their tasks well.

Therefore, to climb the career ladder and carve out a niche in cybersecurity, you need to find the right certification course that can make a difference in this competitive market. For a better understanding, AI Tech Park brings you the top five most popular cybersecurity certifications and courses for 2024.

CompTIA Security+

The CompTIA Security+ is a globally recognized cybersecurity certificate that measures and assesses candidates to level up their skills and validate their qualifications for cybersecurity professionals. The course allows IT professionals to understand topics on cyber attacks, incident response, architecture and design, governance and compliance, risk management, and cryptography. The exam structure is well-designed and updated annually according to the latest trends and techniques that will come in handy to solve complex issues.

Offensive Security Certified Professional (OSCP)

The OSCP program is specially designed for application security analysts, penetration testers, and ethical hackers who are directly dealing with the domain of penetration testing. This course will help you acquire in-depth knowledge of ethical hacking notions and expertise in compromising a series of target machines using multiple exploration steps. To apply for the OSCP program, candidates need to be familiar with offensive security and different operating systems; they must also be well-versed in Bash scripting, Python, and Linux.

Certified Information Systems Auditor (CISA)

The CISA was developed by ISACA, a well-respected membership organization committed to the advancement of digital trust. The course is designed for IT professionals with at least five years of professional experience in information systems auditing, control, or security work. The CISSP covers a broader scope of IT security that will help IT professionals show their expertise in evaluating security vulnerabilities, reporting on compliance, implementing and designing controls, etc.

In today’s interconnected world, the internet connects everything; therefore, businesses need to safeguard themselves from cyber attacks such as hacking, phishing, and remote access to devices. Therefore, cybersecurity certifications can help cyber experts understand the challenges and gain significant knowledge and skills in the field of cybersecurity.

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Tomorrow’s Transportation Will Rely on AI-Driven Cybersecurity’s Success

In an era where technology seamlessly integrates into every facet of our lives, the vision of the future of transportation, once dreamt in the mid-20th century, is becoming a reality. Landscapes are evolving, with the promise of enhanced connectivity, ease of travel, and the development of sprawling metropolises aimed at fostering a more harmonised society. This transformative period in transportation is not just about sleek designs, improved fuel efficiency, or advanced safety systems; it is about the underlying digital revolution that has turned vehicles from mechanical wonders into sophisticated, software-driven entities.

The marvel of modern vehicles extends far beyond their aesthetic appeal or physical innovations.  Today, vehicles are commonly referred to as data centres on wheels, equipped with digital interfaces that constantly communicate with manufacturers, receive over-the-air (OTA) software updates, and integrate advanced safety features, like LIDAR systems, to navigate complex environments. The once direct mechanical connection between the accelerator and the engine has been replaced by a digital command centre, where a simple press of a pedal is translated into a series of computations that ensure optimal performance and safety.

However, this digital evolution brings with it a looming shadow of vulnerability. The very systems that make modern vehicles a marvel of technology also exposes them to a myriad of cybersecurity threats. In recent years, the automotive industry has witnessed a concerning trend: an increase in cyber-attacks targeting not just the vehicles but the entire ecosystem surrounding their development, production, and maintenance. The 2021 attack on KIA Motors by the DopplePaymer group is a stark reminder of the potential consequences of inadequate cybersecurity measures. While no direct harm to drivers was reported, the incident underscored the risks of operational downtime, revenue loss, and eroding customer trust.

The question then becomes, what lies ahead? The potential targets for cyber-attacks are not limited to consumer vehicles but extend to government and municipal mass transit systems. The stakes are exponentially higher, with the threat landscape encompassing espionage, state-sponsored activities, and the emerging menace of AI-driven cyber threats. The complexity of modern vehicles, often containing upwards of 100 endpoints, including infotainment systems that store personal data, demands a cybersecurity strategy that transcends traditional approaches and international borders.

Protecting this data requires a proactive approach, one that involves hunting for threats, deceiving potential attackers, and adopting a mindset that places vehicle cybersecurity on par with data security across the rest of the organisation. It’s about creating a resilient shield around the digital and physical aspects of transportation, ensuring that innovation continues to drive us forward, not backward into an age of vulnerability.

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Decoding the Exponential Rise of Deepfake Technology

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Analyzing the Rapid Growth of Deepfake Technology

In the last few years, we have witnessed that the digital landscape’s boundary between reality and fiction has become increasingly blurred thanks to the advent of deepfake technology. While the intention of developing deep fake technology was purely for entertainment and other legitimate applications, in recent times it has become infamous for spreading misinformation. This technology can also manipulate the cybersecurity domain by confusing or influencing users, exploiting their trust, and bypassing traditional security measures.

Numerous cybersecurity experts have raised questions about deep fake technology playing a multifaceted role and risking national security and prohibited information sources.

Today’s exclusive AITech Park article will explore the nature, risks, real-life impacts, and measures needed to counter these advanced threats.

Decoding DeepFakes

At its core, deep fakes are a part of artificial intelligence (AI) and machine learning (ML) that leverages sophisticated AI algorithms to superimpose or replace elements within audio, video, or images and develop hyper-realistic simulations of individuals saying or doing things they never did.

As the availability of personal information rises online, cybercriminals are investing in technology to exploit deep fake technology, especially with the introduction of social engineering techniques for phishing attacks, as it can mimic the voices and mannerisms of trusted individuals. Cyber attackers orchestrate complicated schemes to mislead unsuspecting targets into revealing sensitive information or transferring funds.

The Progression of Deep Fakes

Deepfakes have opened a new portal for cyber attackers, ranging from suave spear-phishing to the manipulation of biometric security systems. Spear phishing is a common form of deep fake phishing that develops near-perfect impersonation of trusted figures, making a gigantic leap by replicating writing style, tonality, or mincing exact email design. This realistic initiation of visuals and voice can tend to pose an alarming threat to organizations and stakeholders, raising serious concerns about privacy, security, and the integrity of digital content.

For instance, there are cases registered where cyber attackers impersonate business associates, vendors, suppliers, business partners, or C-level executives and make payment requests, demand bank information, or ask for invoices and billing addresses to be updated to steal sensitive data or money. Another example is business email compromise (BEC), which is a costlier form of cybercrime, as these scams are possibly conducted for financially damaging organizations or individuals.

In this era of digitization, we can say that we are navigating the uncharted territory of generative AI (GenAI), where we need to understand the importance of collaboration, stay vigilant, and take measures to combat the threat of deepfakes. The question here shouldn’t be whether we can completely eradicate the threat but how we acclimate our strategies, systems, and policies to mitigate deepfake threats effectively.

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Revolutionizing Mental Healthcare with Artificial Intelligence

With the dawn of the COVID-19 pandemic, mental health has become an area of concern, as more than 1 billion humans every year seek help from clinicians and therapists to cure problems such as depression, anxiety, and suicidal thoughts. This inevitable growing pressure has stretched healthcare and therapeutic institutes to choose smarter technologies such as artificial intelligence (AI) and machine learning (ML) to interact with patients and improve their mental health.

According to new studies found in the Journal of the American Medical Association (JAMA), advanced AI and LLM models can enhance mental health therapies on a larger scale by analyzing millions of text conversations from counseling sessions and predicting patients’ problems with clinical outcomes.

Hence, for a more accurate diagnosis, AI in mental wellness has the potential to lead to a positive transformation in the healthcare sector.

Today’s exclusive AI Tech Park article explores the transformative potential of AI in mental healthcare.

Decoding Mental Health Therapies With AI

In contrast to physical health specialties such as radiology, cardiology, or oncology, the use of AI in mental healthcare has been comparatively modest; where the diagnosis of chronic conditions can be measured by laboratory tests, mental illness requires a complex and higher degree of pathophysiology, which includes a major understanding of genetic, epigenetic, and environmental and social determinants of a patient’s health. To gain more accurate data, mental healthcare professionals need to build a strong and emotional rapport with the patient while being observant of the patient’s behavior and emotions. However, mental health clinical data is quite subjective, as data comes in the form of patient statements and clinician notes, which affect the quality of the data and directly influence AI and ML model training.

Despite these limitations, AI technologies have the potential to refine the field of mental healthcare with their powerful pattern recognition technologies, streamlining clinical workflow, and improving diagnostic accuracy by providing AI-driven clinical decision-making.

The Dilemma of Ethical Considerations

As the world moves towards digitization, it is quite noteworthy that the mental healthcare sector is gradually adopting AI and ML technologies by understanding the technicalities, adhering to rules and regulations, and comprehending the safety and trustworthiness of AI.

However, it is often witnessed that these technologies come with drawbacks of varying accuracy in finding the correct psychiatric applications; such uncertainty triggers dilemmas in choosing the right technology as it can hamper patients’ health and mental well-being.

In this section, we will highlight a few points where mental healthcare professionals, AI professionals, and data engineers could collaborate to eliminate ethical issues and develop trustworthy and safe AI and ML models for patients.

Overall, the promising development of AI in healthcare has unlocked numerous channels, from cobots helping surgeons perform intricate surgeries to aiding pharmaceutical companies and pharmaceutical scientists to develop and discover new drugs without any challenges.

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Unveiling the Potential and Perils of AI in Cybersecurity

Artificial Intelligence (AI) has been developing at a rapid pace and has been integrated into a growing number of applications across every industry. AI continues to widen its capabilities to assist in a variety of daily tasks but, as can be expected with any Internet-based technology, AI also has a dark side. As cyberattacks have grown in volume and complexity over the last few years due to Covid-19, what could cybersecurity and AI look like going forward? If you want to know more about how Covid-19 affected cybersecurity, check out our blog “Cybersecurity in the post Covid-19 world.”

Preserving Privacy Around Artificial Intelligence

The cost of implementation for these types of integrated AI systems can be very high, making it an unattainable option for smaller businesses. Unfortunately, on the threat front, cybercriminals can use AI to devise and launch increasingly more complex cyber attacks. A study from 2023 by Blackberry stated that 51% of IT decision makers believe there will be a successful cyberattack credited to ChatGPT within the year.

Some malware architects have used AI to recreate malware strains and techniques described only in research publications, introducing an entirely new level of cyberattacks. For example, Chat GPT has successfully written functional malware that is capable of stealing sensitive files, encrypting hard drive content, and more. While this malware is not yet sophisticated, the speed and scale at which it can be produced is alarming. Additionally, other AI models have the capability to make attacks even more sophisticated by impersonating the voices of people and demanding money transfers. We can expect to see more attacks that are highly targeted social engineering attacks. Cybersecurity experts also state that AI-created deep fakes are finding ways to bypass biometric authentication, thus gaining access to protected systems.

We are still in the early stages of AI. These AI integrated systems need to be constantly monitored as they are far from perfect and can be prone to errors and biases. But it is clear AI products will continue to improve with time. When AI is used for corporate purposes, it is important that businesses which incorporate these AI systems ensure the technology is used for ethical purposes. These AI systems must be monitored to prevent them from being engineered to act against the corporate assets, and are not used to invade user privacy or circumvent traditional security measures – the  double-edged sword when it comes to security. While AI can provide benefits in threat detection and response capabilities, it can also pose a significant threat – be sure that your data is protected.

Simplify your data security needs. Encryptionizer is easy to deploy. It is a cost-effective way to proactively and transparently protect your sensitive data that allows you to quickly and confidently meet your security requirements. With budget considerations in mind, we have designed an affordable data security platform that protects, manages, and defends your data, while responding to the ever changing compliance requirements.
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Building a Fortified Wall: Effective Third-Party Risk Management Against Cyber Threats

In today’s interconnected business environment, companies regularly rely on third parties for critical business functions like supply chain, IT services, and more. While these relationships can provide efficiency and expertise, they also introduce new cybersecurity risks that must be managed. More than 53% of businesses worldwide have suffered at least one cyber attack in the past 12 months and one in five firms attacked said it was enough to threaten the viability of the business. Recent high-profile breaches like the SolarWinds attack have highlighted the dangers of supply chain compromises. Implementing a comprehensive third party risk management program is essential for security. In this post, we’ll explore key strategies and best practices organizations can use to defend against cyber threats from third party relationships.

Limit Access and Segment Third Parties

Once a third party relationship is established, limit their access to only what is required for their role. Segment them into their own virtual network or cloud environment isolated from your core infrastructure. Implement the principle of least privilege access for their credentials. Disable unnecessary ports, protocols, and services. Lock down pathways between your network and the third party. The goal is to reduce their potential impact and restrict lateral movement if compromised.

Continuously Monitor for Threats

Monitor third party networks vigilantly for signs of compromise. Deploy tools like intrusion detection systems that generate alerts for anomalous behavior. Monitor for unusual data transfers, unauthorized changes, malware, and other IOCs. Conduct vulnerability scans and penetration testing against your third parties’ environments. Audit their logs and security events for issues impacting your security posture. The goal is early detection that can limit damage from a third party breach.

Practice Incident Response Plans

Even rigorous security can still experience incidents. Develop plans for quickly responding to a breach impacting a third party. Define escalation protocols and response team roles. Maintain contacts for your third parties’ security staff. Institute plans for containment, eradication, and recovery activities to limit the impact on your organization. Practice responding to mock third party breach scenarios to smooth out the process. Effective incident response can significantly reduce the damage from real world attacks.

Foster Strong Relationships with Third Parties

While security requirements and controls are critical, also focus on building strong relationships with your vendors, suppliers, and partners. Collaborate to improve security on both sides. Offer guidance and training to enhance their practices and controls. Recognize those who exceed expectations. Build rapport at the executive level so security is taken seriously. Cybersecurity does not have to be adversarial – work together to protect against shared threats.

Third party risk management is essential in modern interconnected business ecosystems. Businesses can no longer rely solely on their own security – all external connections must be assessed and managed.
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What is ACI

Navigating the Future of Generative AI

As the number of generative AI tools continues to proliferate, companies must determine the risks and rewards of using the technology as well as design a framework for implementation

When it comes to generative artificial intelligence (GAI), there is no going back. The genie is out of the bottle and companies must now grapple with a number of big questions. For example, what guardrails should be put in place for employees looking to take advantage of AI’s tremendous potential? Do the risks associated with the emerging technology outweigh the benefits? Is there a way for humans and machines to co-exist in a mutually beneficial relationship?

GAI is different from what many people think of when it comes to AI. Instead of the human-like robots that are often portrayed in movies and the media, generative AI is a form of machine learning that can produce content – including audio, code, images, text, simulations, and videos – more quickly than humans can on their own. Which makes their use enticing.

Guidance principles for corporate use of AI

Implementing appropriate guidelines allows companies to use the power of generative AI while reducing the risk of being affected by its negative aspects. While no set standard will work for all companies, guidelines should adhere to three principles.

Principle 1: Be AI-safe and secure

When you submit a question to tools like ChatGPT, Google Bard, and Claude AI, that information is stored and used to train it further. Once businesses send information to these tools, they effectively hand over that data to an external entity and lose control over its use. And that has consequences.

“If you’re in healthcare, finance, or any other regulated environment, there are severe implications for misuse of the information you’re in charge of,” says Post. “Those types of organizations should not jump in until they have been properly trained and have guardrails put in place.”

LLMs can also open the door to intellectual property theft because people unwittingly give them proprietary information such as trade secrets, company financial data, personally identifiable information from clients, and customers, and much more.

Safety, security, and privacy comprise the first guiding principle and ensure employees do not input anything into a generative AI tool that they should not share.

A collaboration between bytes and brain

The guidance principles are meant to raise awareness about the current state of AI tools. Humans will need to learn to work with AI, not rebel against it.

“It’s a bytes and brains collaboration,” says Dr. Norrie. “We must figure out the machine instead of letting the machine figure us out. It is best to establish your AI guidelines while you’re developing your own knowledge and understanding of how you plan to govern and regulate its use.”

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Holiday Shopping Safety Guide: Protect Yourself from Black Friday and Cyber Monday Scams

The shopping season has approached, and customers are already planning their holiday splurges for the end of the year. If you are one of those 334 million Americans who are going to be part of Black Friday and Cyber Monday, you might want to take a glance at your emails and discount links for more details about the retail and e-commerce stores and make a shopping list before the sale.

However, all these moves are frequently being tracked by criminals to get your information and benefit themselves. There are numerous ways that cybercriminals take undue advantage of these rush hours, from spam, and clickbait to duping URLs, and one wrong move may put your valuable information in the wrong hands.

In today’s article, let’s focus on the best practices that customers can use to defend themselves from common cyber threats and other malicious activities.

Check Twice Before Giving Out Credit Card Information

Credit card information can be stolen in several ways by cybercriminals during this festive season.

Here are a few things you must check before giving your credit card information:

Read for customer reviews and double-check the URL before making any online payments.

According to global sources, around 65% of users face irregular pop-up purchases while using credit cards or other modes of e-payment. Take note of how much personal information you are providing to any website before checking out.

Don’t Shop on Hotspots

Even though open hotspots are free and easy to use, customers should be aware of safety and security before connecting to the public Wi-Fi network.

Avoid shopping on public Wi-Fi networks, like in airports, coffee shops, or shopping malls. Open hotspots are extremely dangerous, as it is the perfect time for hackers to get into your PC, tablet, and mobile devices.

Hackers generally use open hotspots to intercept communications between you and the connection point, so instead of interacting directly with the hotspots, you send your information to the hacker.

It is always recommended to use a VPN (virtual private network) service, which creates a secured and private tunnel between your device and open hotspots.

Gone are those days when you had to stand in long queues to shop and get your billing processes done. Today, times have changed and the last few decades have witnessed a drastic change in the way we shop. Globally, we have entered the world of digitization, where everything from shopping to checking works on artificial intelligence (AI) and machine learning (ML), and you can get your package delivered to your home in just a few clicks.

For secure online shopping, you need to simply follow the above best practices that will make your shopping experience stress-free and smooth as butter.

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Cyber Savvy Shopping: Protect Yourself from Black Friday Scams

Black Friday and Cyber Monday are excellent opportunities for customers to get hold of some great deals, while for retailers, it is an outstanding time to clear up their stocks. But, unfortunately, even cybercriminals utilize this time to execute scams and crimes that affect businesses.

According to global collective research in 2022, there is $41 billion in fraud damages reported from the e-commerce industry. However, it is anticipated that by the end of 2023, the loss will surpass $48 billion.

As cyber criminals initiate new routine scams around the time of these events, it is the right time for CISOs and other IT teams to step up their vigilance plan of action to counter such malicious attacks and protect their business as well as the interest of their valued customers.

With the help of this article, we will delve deep into some useful tips to create a secure online shopping experience.

Key Actions for Black Friday Cybersecurity

During such frenzied festive seasons, the CISOs and IT managers should be cautious as threat actors are on their toes to ruin businesses with their scams and deceiving tactics.

So, to prevent such incidents here are four essential key actions you can conduct:

Create a Robust Cybersecurity Plan

Planning a robust cybersecurity plan during events and festivals, like Black Friday or Cyber Monday can involve multiple approaches. It has been witnessed that cyber actors are ahead in the game by using tactics like:

Custom site designs for the event or early bird deals to fool customers into clicking on them and impersonating them as your customers.

It has been seen that customers are attracted to clickbait that forces your company to get their sensitive information, like credit or debit card details, addresses, mobile numbers, and many more.

Thus, chalking out the areas where monitoring is needed or what steps and protocols are needed to eliminate these incidents will save you valuable money and resources in turn giving your customers the retail therapy they deserve.

Implement Automated Data Security and Compliance

You need to ensure that your website or application follows all the rules and regulations in terms of data security and compliance.

Implement automated data security and compliance services that scan your network and notify you in real-time of any suspicious activity, which allows you to promptly act before any damage occurs.

Automated solution tools like Scrut, Vanta, Drata, and Tugboat Logic help employees monitor and report threats promptly.

The only standard approach to implement these tools would require adequate routine team training with appropriate knowledge transfer for personnel to operate these tools and defeat cyber criminals ahead of time!

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Quick Guide to Endpoint Security

In today’s increasingly complex threat landscape, traditional antivirus solutions are no longer enough to protect organizations from cyber attacks. Attackers are constantly evolving their tactics, and sophisticated malware and ransomware are becoming more prevalent. As a result, businesses need to take a more proactive approach to security, and Endpoint Detection and Response (EDR) is emerging as a critical tool in the fight against cybercrime.

What is Endpoint Detection and Response?

Endpoint Detection and Response (EDR) refers to a type of cybersecurity technology that focuses on detecting and responding to security threats on individual devices, such as laptops, desktops, and mobile devices. EDR tools provide advanced monitoring and analytics capabilities, which allows security teams to detect suspicious behavior on endpoints, such as malware infections, unauthorized access attempts, and data exfiltration.

The goal of EDR is to provide real-time visibility into endpoint activity and help security teams quickly identify and respond to potential security incidents. Some common features of EDR tools include:

Real-time monitoring and analysis of endpoint activity, including network traffic, system logs, and user behavior. Automated threat detection and response, which can help security teams quickly identify and respond to potential security incidents.

Advanced analytics and machine learning capabilities, can help identify patterns of behavior that may be indicative of an attack.

Integration with other security tools, such as firewalls, intrusion detection systems, and security information and event management (SIEM) platforms.

Why is EDR important?

EDR is important because it provides a proactive approach to endpoint security that can help organizations identify and respond to threats before they cause damage. Traditional antivirus solutions are reactive, meaning they can only detect known threats and may not be effective against newer or more sophisticated attacks.

In contrast, EDR tools are designed to be more agile and flexible, allowing security teams to quickly adapt to new threats and respond accordingly. By monitoring endpoint activity in real-time, EDR tools can help detect and respond to potential security incidents before they escalate into major breaches.

EDR also helps organizations meet compliance requirements and improve their overall security posture. Many regulations, such as the General Data Protection Regulation (GDPR) and the Payment Card Industry Data Security Standard (PCI DSS), require organizations to have robust security controls in place to protect sensitive data. EDR can help organizations meet these requirements by providing enhanced visibility and control over endpoint activity.

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