The latest cybersecurity challenges

Cyber threats are growing at an exponential rate, both globally and locally. From sophisticated cyberattacks to internal vulnerabilities, threat complexity is escalating and creating pervasive and multifaceted risks. The highly dynamic nature of these challenges means that cybersecurity is critical on all business levels and needs to be intricately woven into every facet of an organisation’s operations.

Because the current security landscape is highly dynamic and complex, modern security operations require a good understanding of contemporary and future cybersecurity challenges, along with an agile approach towards the detection, interpretation, and mitigation of threats. This article will explore the latest cybersecurity challenges and show you how to translate the latest cybersecurity trends into actionable insights and best practices.

Challenge 1: Generative AI and machine learning in cybersecurity

Generative AI and machine learning (ML) have taken giant leaps forward in recent years, unlocking a wide range of new applications that have the potential to seamlessly integrate various functions and enhance user experiences across various industries. The major difference between generative and traditional AI is that the former can create entirely new data whilst the latter only uses existing information to solve problems or perform specific tasks. Generative AI and ML are also very helpful in the realm of cybersecurity. The technology can assist cybersecurity professionals in several ways. Let’s have a closer look at the most important applications and benefits of generative AI and ML in cybersecurity.

Simulation

Deep learning models have the capacity to simulate various advanced attack scenarios, allowing you to develop strong defence mechanisms against both well-known and emerging threats.

Automation

Generative AI and machine learning can be beneficial in streamlining cybersecurity workflows by automating dull and time-consuming routine security tasks that require little or no human intelligence. Configuring firewalls and scanning for vulnerabilities are prime examples of such tasks. The aid of AI and ML allows you to free human resources for the more complex issues at hand.

Enhancing threat detection and response

Generative AI and ML have the capacity to analyse huge data sets quickly and accurately. Moreover, generative AI continuously learns from data, allowing it to adapt to new and ever-evolving cybersecurity threats. This greatly enhances the capability to detect anomalies and potential breaches early on, allowing you to stay one or two steps ahead of attackers and minimise the impact of a cyberattack.

Reporting

Generative AI facilitates the creation of comprehensive, understandable cybersecurity reports. The technology can synthesise data from various sources into coherent reports, highlighting key findings, trends and potential vulnerabilities. This saves time and makes reports more accurate and informative, providing valuable insights for decision-makers.

The downside of advanced AI

But it’s not all roses in the world of advanced AI and cybersecurity. The same advanced AI capabilities that have so much potential when it comes to reinforcing cybersecurity measures are also being manipulated by cybercriminals to craft more sophisticated attacks. This includes automating targeted phishing, AI-powered deepfakes, automated hacking, and developing malware that can dynamically counteract security measures and systems.

Despite significant interest in GenAI among technology and cybersecurity executives, there hasn't been substantial evidence of its use in cyber attacks based on global incident data. So far, mentions of GenAI in criminal forums primarily relate to commercial tools or applications like AI-generated non-consensual pornography rather than sophisticated cyber attacks. Despite advancements in technology, traditional cyber threats like phishing, malware (especially ransomware), and exploitation of zero-day vulnerabilities remain potent and effective. The effectiveness of these attacks suggests that while GenAI may offer new capabilities, it may not necessarily lead to a dramatic increase in successful attacks.

There is evidence of state-sponsored threat actors using GenAI technologies for activities like “learning how to code”. However, this hasn't yet translated into major breakthroughs in cyber attacks. Deepfake technology, a subset of GenAI, has already been exploited for fraud and misinformation, indicating potential future threats in this area.

While there is certainly interest and some early-stage experimentation among threat actors, the actual impact on cyber threats remains limited at present. Traditional methods such as social engineering and malware are still highly effective and the adoption of GenAI in malicious activities has not yet reached a critical tipping point. Some caution against the hype surrounding AI threats is warranted, since its transformative impact on cybersecurity remains speculative. Continued monitoring and adaptation of defence strategies are essential as this technology matures and potentially introduces new challenges in the threat landscape.

Continue reading about the benefits and dangers of AI.

Challenge 2: Quantum computing and encryption

A second big challenge in the field of cybersecurity is the advent of quantum computing. Quantum computers use quantum physics to access different and more advanced computational abilities in comparison to traditional computers. Quantum computing brings a significant shift in computational power, allowing users to solve complex problems that classical computers can’t manage efficiently.

Although quantum key distribution protocols, part of quantum security, have the potential to enable the secure exchange of cryptographic keys between parties, quantum computing also poses a threat to traditional cryptographic systems. Current quantum computing technology is not yet advanced enough to break the best available cryptography standards, but experts warn that this could change within less than a decade.

In response to this newly emerging threat, the cybersecurity community is proactive in developing quantum-resistant algorithms. Post-quantum cryptography (PQC) is a good example. PQC standards are based on mathematical problems that cannot effectively be cracked by quantum computers. These new standards are essential to ensure that your data remains secure against potential quantum-level decryption tactics.

The Netherlands is actively investing (the government has allocated €273 million to the project Quantum Delta NL) in post-quantum cryptography to ensure its digital security infrastructure is future-proof against the potential threats posed by quantum computing. The Quantum Delta NL program plans to scale up to 100 startups, train 2,000 PhDs and engineers, and establish three large corporate R&D labs by 2027.

The quantum internet is another key component in the shift toward a quantum-secure future, facilitating secure, end-to-end quantum communication that would be resilient against both classical and quantum computational threats. This infrastructure will play a critical role in enabling robust quantum key distribution and other quantum-based security protocols.

It’s definitely wise to prepare your organisation for the future by planning a migration to quantum-resistant cryptography. This involves:

• Identifying your highest priority use cases. Proactively list the critical data and systems in your environment needing quantum resistance. Also talk to your technology vendors about developing and implementing quantum-resistant protections across the products and solutions you use.

• Make sure you have a plan to protect your IT systems against the quantum threat in the timescale you need.

Challenge 3: Ransomware evolution and cybercrime-as-a-service (CaaS)

Ransomware attacks and tactics have evolved beyond simple data lockdowns to more complex double or even triple extortion schemes. These involve not only encrypting the victim’s data, but also stealing it and threatening to release it unless a ransom is paid. This adds another level of pressure to the ransomware attack. Classical ransomware often targets individuals, encrypting personal files and demanding relatively modest ransom sums. Nowadays, attackers have increasingly shifted their focus towards medium-sized businesses and enterprises, employing advanced techniques like exploiting network vulnerabilities for widespread infection.

An additional problem is that cybercrime-as-a-service (CaaS) has made powerful cybercrime tools more accessible than ever. CaaS is a lucrative business model for ransomware developers. They sell or lease their malicious software to other criminals, enabling a growing number of hackers and cyber crooks to launch sophisticated ransomware attacks with a minimum of technical expertise. The ransomware developers often get a decent cut of the ransom payments as a reward for their services. In recent years, CaaS has led to an increase in the scale and sophistication of cyber threats.

Challenge 4: Regulatory changes affecting cybersecurity

Keeping up with regulatory changes concerning cybersecurity is also a big challenge for many organisations. Recent implementations of the NIS2 and Cyber Resilience Act have introduced significantly more stringent cybersecurity requirements across various sectors. These frameworks are designed to strengthen the security and resilience of networks and information systems.

The new regulations oblige organisations to be fully compliant and upgrade their security measures. NIS2 and Cyber Resilience Act compliance involves conducting thorough audits and adjusting policies to meet the heightened standards.

Challenge 5: Supply chain security

Modern supply chains are often highly specialised, complex and interwoven, with goods often having to pass through multiple stages before finally reaching the end consumer. The interconnected nature of today’s digital supply chains means a single breach (according to Verizon’s latest Data Breach Investigation Report, system Intrusion continues to be the top pattern from a breach perspective) can have cascading effects across multiple organisations. A single vulnerability in the supply chain can compromise all connected entities. This was highlighted by the Okta breach, a cybersecurity incident that was traced back to a single compromised employee account affecting numerous downstream clients.

The nature of modern supply chains calls for good mitigation strategies, such as implementing robust access controls, performing regular security assessments, and fostering transparency between all parties and stakeholders. Safeguarding supply chain security calls for the extension of cybersecurity protocols beyond your immediate operations to include all partners in the supply chain.