4 Emerging Cybersecurity Threats in 2024

April 05 2024

4 Emerging Cybersecurity Threats in 2024

Cybersecurity is a dynamic field. Staying informed and vigilant about emerging threats is of paramount importance to safeguard the digital assets and privacy of the organisation.

Top Cybersecurity Threats anticipated in 2024 are:

Generative AI (GenAI) Adoption

Generative AI (GenAI) is expected to revolutionise the cybersecurity landscape. It will emerge as a big player in augmenting human capabilities.

By 2028, GenAI could eliminate the need for specialized education in 50% of entry-level cybersecurity positions. Consequently, it is highly suggested that organisations start focusing on internal use cases, coordinate with HR partners, and identify adjacent talent required for critical cybersecurity roles.

Unsecure Employee Behaviour

Despite technological advancements, human behaviour remains a critical factor in security.
Combining GenAI with an integrated platforms-based architecture in security behaviour and culture programs (SBCP) can lead to 40% fewer employee-driven cybersecurity incidents. Experts feel that personalised engagement and hyper-personalised content can encourage secure behaviours among employees.

Third-Party Risks

Organisations increasingly rely on third-party vendors and partners. However, these are relationships that can introduce vulnerabilities.

Ensuring robust third-party risk management processes is crucial to prevent data breaches and supply chain attacks.

Continuous Threat Exposure

Cyber threats evolve rapidly. Organisations must be constantly on the alert and adopt proactive measures to stay ahead.
Cybersecurity threats like quantum computing, AI-powered attacks, and C demand constant vigilance and adaptive security strategies.

Methods Currently in Use to Counter Cybersecurity Threats

Zero Trust Security

Zero Trust Security is a cybersecurity framework based on the principle of "never trust, always verify." In traditional network security models, once users and devices are inside the corporate network perimeter, they are often granted extensive access to resources and systems. However, with the increasing prevalence of cyber threats and the growing complexity of IT environments, this approach has become inadequate for protecting sensitive data and critical systems.

The Zero Trust Security model advocates for the following key principles:

Verify Identity: Instead of assuming trust based on network location, Zero Trust requires verifying the identity of users and devices before granting access to resources.
Least Privilege Access: Zero Trust limits access privileges to the minimum level necessary for users and devices to perform their tasks.
Micro-Segmentation: Zero Trust divides the network into smaller, isolated segments to contain and limit the spread of cyber threats.
Continuous Monitoring: Zero Trust emphasizes continuous monitoring of user and device behaviour to detect and respond to anomalies and security incidents in real-time.
Encryption: Zero Trust encourages the use of encryption to protect data both in transit and at rest.
Dynamic Policy Enforcement: Zero Trust employs dynamic policy enforcement to adapt security controls based on contextual factors such as user roles, device status, and network conditions.

Implementing a Zero Trust Security model requires a holistic approach that involves people, processes, and technology. It requires collaboration across different teams within an organization, including IT, security, and compliance, to define policies, implement controls, and continuously monitor and improve security posture. Zero Trust Security offers a proactive and adaptive approach to cybersecurity that helps organisations better protect their critical assets and data in today's increasingly complex and dynamic threat landscape.

AI Employment

AI (Artificial Intelligence) has become increasingly prevalent in the field of cybersecurity due to its ability to analyze vast amounts of data, detect anomalies, and respond to threats in real time.

Here, we look at some ways in which AI is utilised in cybersecurity:

Threat Detection and Prevention: AI-powered systems can analyze network traffic, user behaviour, and system logs to identify potential threats such as malware, phishing attacks, and insider threats.
Endpoint Security: AI-based endpoint security solutions monitor and protect individual devices (such as computers, smartphones, and IoT devices) from malware and other cyber threats.
Network Security: AI is used to monitor network traffic and detect unusual activity that may indicate a cyberattack, such as unauthorised access attempts or data exfiltration. AI-powered intrusion detection systems (IDS) and intrusion prevention systems (IPS) can automatically block suspicious traffic and prevent security breaches.
Behavioural Analysis: AI can analyze user behaviour to identify deviations from normal patterns, which may indicate a compromised account or insider threat.
Vulnerability Management: AI can assist in identifying and prioritising security vulnerabilities in software and systems.
Automated Response: AI-powered security systems can automatically respond to cyber threats in real-time, reducing the time it takes to detect and mitigate security incidents.
Threat Intelligence: AI can analyze large volumes of threat intelligence data to identify emerging threats and trends in cyberattacks.
Cybersecurity Analytics: AI-driven analytics platforms can provide insights into security incidents, help identify root causes of breaches, and assist in improving overall security posture.
Security Orchestration, Automation, and Response (SOAR): AI-powered SOAR platforms help streamline and automate security operations by integrating security tools, orchestrating incident response workflows, and automating repetitive tasks. SOAR platforms leverage machine learning to improve incident response times and reduce manual intervention.

AI is playing an increasingly important role in cybersecurity by enabling organisations to detect and respond to cyber threats more effectively, enhance their security posture, and mitigate risks in an ever-evolving threat landscape. However, it's important to note that while AI can significantly improve cybersecurity capabilities, it is not a silver bullet and should be used in conjunction with other security measures and best practices.

Become an ethical hacker

Use of IoT in Cybersecurity

IoT (Internet of Things) devices are becoming increasingly prevalent in both consumer and industrial environments. However, they are bringing with them a host of security challenges. Securing IoT devices is crucial to prevent potential threats such as unauthorised access, data breaches, and disruption of critical services.

Here are some key aspects of IoT security:

Device Authentication and Access Control: IoT devices should implement strong authentication mechanisms to ensure that only authorised users and systems can access them. This may include password authentication, digital certificates, and biometric authentication.
Data Encryption: Data transmitted between IoT devices and backend systems should be encrypted to prevent eavesdropping and tampering. Secure communication protocols such as TLS (Transport Layer Security) should be used to encrypt data in transit, while data at rest should be encrypted to protect against unauthorised access if the device is compromised.
Firmware Updates and Patch Management: IoT devices often run on firmware that may contain vulnerabilities. Regular firmware updates and patch management processes should be implemented to address security vulnerabilities and ensure that devices are running the latest, most secure software versions.
Secure Boot and Trusted Execution Environments: IoT devices should implement secure boot mechanisms to ensure that only authenticated and trusted software components are loaded during the boot process.
Network Segmentation and Isolation: IoT devices should be segmented and isolated from critical network segments to limit the potential impact of security breaches. Network segmentation can help contain the spread of attacks and prevent unauthorised access to sensitive systems and data.
Monitoring and Anomaly Detection: Continuous monitoring of IoT devices and network traffic can help detect suspicious activities and potential security incidents in real-time. Anomaly detection techniques, such as machine learning-based analytics, can identify deviations from normal behaviour patterns and alert security teams to potential threats.
Supply Chain Security: Organisations should ensure the security of the entire IoT supply chain, from device manufacturing and distribution to deployment and disposal.
User Awareness and Education: End-users and administrators of IoT devices should be educated about best practices for IoT security, including password management, device configuration, and software updates.

In essence, securing IoT devices requires a comprehensive approach that addresses both technical and organisational aspects of security. By implementing robust security controls, monitoring solutions, and risk management practices, organisations can mitigate the risks associated with IoT deployments and protect their critical assets and data from potential cyber threats.

Quantum Computing: Is it the Future of Cybersecurity?

Quantum computing has the potential to revolutionise many aspects of cybersecurity, both by enabling more powerful encryption algorithms and by posing new challenges to existing cryptographic systems. Here's a breakdown of how quantum computing intersects with cybersecurity:

Breaking Traditional Encryption: One of the most significant impacts of quantum computing on cybersecurity is its potential ability to break widely used cryptographic algorithms such as RSA and ECC (Elliptic Curve Cryptography).
Post-Quantum Cryptography (PQC): To address the threat posed by quantum computing to traditional encryption schemes, researchers have been developing post-quantum cryptographic algorithms that are believed to be secure against quantum attacks.
Quantum Key Distribution (QKD): Quantum computing also offers new opportunities for secure communication through quantum key distribution (QKD) protocols. QKD leverages the principles of quantum mechanics to establish secure cryptographic keys between two parties, with the security guaranteed by the laws of quantum physics. Unlike classical key exchange protocols.
Quantum-Safe Cryptography Adoption: As the threat of quantum computing to traditional cryptographic systems becomes more apparent, there is a growing emphasis on the adoption of quantum-safe cryptographic algorithms and protocols. Organisations are encouraged to assess their current cryptographic infrastructure and transition to quantum-safe alternatives to ensure the long-term security of their data and communications.

Challenges and Considerations:

Despite the potential benefits of quantum computing for cybersecurity, there are several challenges and considerations that need to be addressed. These include the practical realisation of large-scale quantum computers, the development and standardisation of quantum-safe cryptographic algorithms, the integration of quantum-safe solutions into existing systems, and the need for robust security measures to protect quantum computing technologies from attacks and vulnerabilities.

In summary, quantum computing has profound implications for cybersecurity, both in terms of its potential to break existing cryptographic systems and its promise to enable new paradigms of secure communication. By advancing research and development in post-quantum cryptography and quantum-safe technologies, organisations can prepare for the future security landscape shaped by quantum computing advancements.

Cloud Security for Countering Cybersecurity: What are its unique challenges?

Cloud security encompasses the protection of data, applications, and infrastructure in cloud computing environments. While cloud computing offers numerous benefits such as scalability, flexibility, and cost-efficiency, it also poses unique security challenges.

Here are some of the key aspects and challenges of cloud security:

Data Security: Protecting data is a critical aspect of cloud security. Challenges include ensuring data confidentiality, integrity, and availability.
Identity and Access Management (IAM): Managing user identities and controlling access to cloud resources is a significant challenge.
Compliance and Governance: Compliance with regulations and industry standards is a key concern for organisations using cloud services.
Shared Responsibility Model: Cloud security follows a shared responsibility model, where the cloud provider is responsible for securing the underlying infrastructure, while customers are responsible for securing their data and applications.
Data Loss and Leakage: Data loss and leakage are significant risks in the cloud. Misconfigurations, human errors, insider threats, and malicious attacks can lead to the exposure of sensitive data.
Network Security: Securing network traffic between cloud resources and users, as well as between different cloud services, is crucial. Challenges include securing virtual networks, implementing network segmentation, and protecting against network-based attacks such as distributed denial-of-service (DDoS) attacks.
Incident Response and Forensics: Detecting and responding to security incidents in the cloud requires specialised tools and processes. Challenges include identifying and investigating security incidents across complex and dynamic cloud environments, as well as preserving evidence for forensic analysis.
Vendor Lock-In and Interoperability: Vendor lock-in and interoperability challenges arise when organisations use multiple cloud providers or migrate between cloud platforms. Ensuring compatibility and portability of applications and data, managing dependencies on proprietary cloud services, and avoiding vendor-specific security solutions are essential considerations here.

Addressing these challenges requires a comprehensive approach to cloud security that incorporates technology, processes, and people.

Get trained in AWS from industry experts

It is worthwhile to remember that organisations must continuously assess their security posture, adapt to evolving threats and regulatory requirements, and implement best practices for securing their environments. Additionally, collaborating with cybersecurity providers, leveraging security-as-a-service offerings, and investing in employee training and awareness programs can help in effectively mitigating such risks.

Also read: Brute Force Attack & Dictionary Attack: Difference and Prevention Methods

Comments ()

Your email address will not be published. Required fields are marked*

4 Emerging Cybersecurity Threats in 2024