Cybersecurity in 2030: What Does the Future Hold?
For the rest of this decade, cybersecurity will take centre stage in enterprise operations — with 99% of companies increasing their budgets in the next few months. You need to keep Ten key cybersecurity trends on your radar so that you invest in the right direction — here are my recommendations:
1. Secure multiparty computation (MPC)
MPC is a cryptographic technique that lets multiple parties jointly compute a function over the private inputs while keeping these inputs confidential. Each party contributes their input without revealing it to others and, through cryptographic protocols, performs computations so that only the visibility of the function’s output.
Organisations often need to analyse data collaboratively without sharing sensitive information. MPC allows them to perform computations on encrypted data, ensuring privacy. For example, healthcare institutions can analyse patient records without revealing individual health data. Financial institutions can compute aggregated statistics (e.g., average transaction amounts) without exposing individual transactions.
It allows for collaborative data analysis, machine learning, and decision-making without compromising the privacy of sensitive information. MPC protocols ensure that even if some parties are compromised or collude, the confidentiality and integrity of the data remain preserved.
2. Cyber-physical security convergence
This trend refers to integrating cybersecurity measures with physical security systems to protect interconnected cyber-physical systems (CPS) and critical infrastructure from emerging threats.
Organisations often use video surveillance systems (CCTV cameras) to monitor physical spaces. Combining VSS with access control systems is a prime example of cyber-physical security convergence. By integrating these systems, an organisation can tag live video feeds with information about physical access attempts. For instance, when someone uses an access card to enter a restricted area, the video feed can automatically associate that event with the access control system.
With the proliferation of IoT devices, smart grids, and industrial control systems (ICS), traditional boundaries between cyber and physical domains have blurred — calling for a holistic approach to security. Cyber-physical security convergence involves deploying integrated solutions that combine network monitoring, anomaly detection, access control, and physical surveillance to detect and respond to attacks.\
3. Homomorphic encryption:
It is an advanced cryptographic technique that performs computations on encrypted data without decrypting it first. In homomorphic encryption schemes, mathematical operations can be applied to encrypted data so that the results of these operations remain valid even after the encrypted data is decrypted.
It allows for secure data processing and analysis while preserving the confidentiality of sensitive information. Fully Homomorphic Encryption (FHE) has become increasingly practical for various commercial applications. FHE allows insights from multiple sensitive data sets to be derived while maintaining privacy. For instance, healthcare institutions can analyse patient data from different sources without sharing raw information. Securely combining data enhances research and decision-making.
Homomorphic encryption has applications in secure cloud computing, data outsourcing, and privacy-preserving machine learning. Data owners can delegate computations to untrusted third parties without disclosing the underlying data.
4. Post-quantum key distribution
PQKD refers to cryptographic protocols and algorithms designed to distribute cryptographic keys securely in a post-quantum computing environment.
The advent of quantum computing and traditional cryptographic algorithms, such as RSA and ECC, makes them susceptible to quantum attacks that can break their security properties. PQKD protocols utilise quantum-resistant mathematical primitives, such as lattice or hash-based cryptography, to securely generate and exchange cryptographic keys.
Lotteries and online gaming rely on random numbers to guarantee fair play. Quantum key distribution ensures complete randomness. QKD prevents tampering with the random number generation process, maintaining the integrity of these systems.
By leveraging the principles of quantum mechanics, PQKD protocols ensure that key distribution remains secure against quantum adversaries.
5. Decentralised identity management:
Decentralised identity management is a paradigm shift) that empowers individuals to control their digital identities without relying on centralised identity providers.
You own and manage your identity attributes using blockchain-based or distributed ledger technology (DLT), which provides tamper-proof and verifiable records of identity transactions. Decentralised identity solutions let you selectively disclose identity information and authenticate themselves across different services and platforms without sharing sensitive personal data.
Identity verification for digital onboarding by institutions and companies can help them verify user identities remotely and securely. Decentralised identity simplifies registering a product, renting a car, or renewing car tags.
Moreover, these systems promote interoperability and trust among diverse ecosystems, fostering innovation and collaboration in the digital economy.
6. Hyperautomation of incident response
This trend signals the fusion of advanced automation technologies with your processes covering cybersecurity incident management.
We can achieve unprecedented efficiency and agility in addressing security incidents by orchestrating robotic process automation (RPA), machine learning algorithms, and predefined response playbooks. When you integrate these technologies into your incident response workflows, you streamline the detection, analysis, containment, and remediation of security threats.
Companies like Amazon and Bank of America use AI-powered chatbots and virtual assistants to manage customer inquiries efficiently. Hyperautomation allows personalised experiences at scale, enhancing customer service. When a server goes down, AIOps (Artificial Intelligence for IT Operations) can detect the issue through specific alerts or by correlating multiple alerts that suggest a service disruption. Automated incident response ensures swift action without manual intervention.
Hyperautomation enables you to dynamically adapt your response strategies based on evolving threat landscapes — minimising the impact of security breaches on your organisation.
7. Federated security analytics
By federating security analytics across multiple entities or organisations, you can aggregate and analyse security telemetry data while preserving the privacy and sovereignty of each participant’s data. Secure protocols and distributed processing frameworks let you correlate threat indicators, detect emerging attack patterns, and share actionable insights with trusted partners or industry peers.
During the pandemic, federated data analysis played a crucial role. Researchers worldwide collaborated on COVID-19 data without centralising it. They tracked infection rates, studied transmission dynamics, and evaluated interventions by analysing data from diverse regions. Federated approaches allowed real-time insights while respecting privacy regulations.
8. Secure hardware enclaves for IoT
This trend leverages dedicated hardware-based security mechanisms to fortify connected devices against many cyber threats. By integrating trusted execution environments (TEEs), secure enclaves, and hardware-based cryptographic modules into IoT endpoints, you establish isolated execution environments for critical security functions.
Microsoft’s Azure IoT Edge platform now supports enclaves to protect sensitive assets and workloads at runtime. By deploying IoT Edge on enclave-enabled devices, proprietary algorithms, private data, and real-time computational insights remain secure even during execution. The Scalys TrustBox Edge is an Azure IoT Edge-certified device that integrates Arm® TrustZone®, NXP Layerscape®, and the Confidential Computing Consortium’s Open Enclave SDK. It ensures trusted execution within enclaves, safeguarding sensitive workloads.
Also, these enclaves enable safeguarding sensitive data, authentication of device identities, and enforcement of access control policies at the hardware level — mitigating risks of physical tampering, side-channel attacks, and malware exploitation.
9. Neural network malware detection
In many ways, neural network-based malware detection represents the pinnacle of AI-driven cybersecurity solutions. It harnesses the power of deep learning algorithms to combat ever-evolving malware.
By training neural networks on large-scale datasets of malicious and benign software samples, you can autonomously empower detection systems to learn complex patterns and behavioural characteristics indicative of malware.
FireEye’s deep learning classifier successfully identifies malware using unstructured bytes from Windows PE files. Import-based features (such as names and function call fingerprints) play a significant role in the learned features across all levels of the classifier.
Through continuous learning and refinement, these neural networks can adapt dynamically — enhancing their ability to detect zero-day exploits, polymorphic malware variants, and advanced persistent threats (APTs).
10. Augmented reality (AR) cybersecurity visualisation
AR visualisations can revolutionise your approach to situational awareness and threat intelligence analysis, providing immersive and intuitive interfaces for visualising complex cyber landscapes in three-dimensional space.
By overlaying cybersecurity data onto a physical environment through AR-enabled devices, you gain unparalleled insights into network traffic, security events, and attack vectors.
Companies are leveraging AR to enhance cybersecurity training for their employees. Imagine a new employee sitting at their desk, wearing AR glasses. The training system superimposes various cyber threat scenarios onto their real-world view. The employee interacts with these virtual threats, identifying and solving issues. This interactive approach keeps employees engaged and yields better training results.
This interactive capability facilitates three things in real-time: identifying abnormal patterns, correlating disparate data sources, and visualising attack scenarios. This trend will transform your cybersecurity operations into a dynamic and immersive experience.
These Ten cybersecurity trends aren’t lightyears away. The future is here, and organisations need to start preparing today. Fortunately, modern technologies equip us with all the tools we need to protect against a new generation of threats.
If you found this article insightful, let me know in the comments. You can also email me at Arvind@am-pmassociates.com.
