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How Data Security Standards Are Likely to Change in Coming Years

Explore how data security standards are set to evolve in the coming years, reflecting on past advancements and predicting future trends.

data security standards
Bingle Flickerini

May 14, 2024

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The digital age is here – now what? Robust data security standards are the frontline of defense to safeguard privacy and protect sensitive information from ever-evolving cyber threats. While the risks of technology impact everyone, it is critical businesses adapt to changing data-security trends, to safeguard clients from data breaches and prevent cyber attacks crippling their operations. In this blog, the Lightyear team will look at some of the ways data security standards are evolving, and how it impacts business operations.

The Foundations of Data Security Standards

As technology becomes more complex and pivotal to how we live, work, and play, data security standards must evolve to keep pace. However, the idea of data security itself is not new – it can be traced back to the earliest days of computing, when security concerns mostly revolved around physical access to large mainframe computers.

As networking began to emerge in the 1970s, the need for standardized security measures became more pressing. This led to the development of early encryption protocols and techniques – the foundation of modern data encryption. The 1980s saw the first comprehensive set of US data security standards, the Federal Information Processing Standards (FIPS). Its focus was sensitive government information, but this spurred the private sector to adopt new encryption and authentication for their data, too.

When the 90s dawned, and the internet rolled out globally, we saw these tactics evolve to international standards, such as the Data Encryption Standard (DES) and its successor, the Advanced Encryption Standard (AES), focused on online communication. The e-commerce boom of the 2000s then brought us the Payment Card Industry Data Security Standard (PCI DSS) to protect online credit card information. Plus, we started to see the rise of industry-specific regulatory frameworks (Think of HIPAA in healthcare and SOX in finance), mandating stricter data security measures in sensitive environments.

Recent Advances in Data Security Standards

That’s the past, but what about now? Today, we face a world where cloud computing, mobile devices, and the IoT are rapidly evolving. Data security standards have adapted to new threats and challenges, with a heightened emphasis on encryption, data control, and data integrity. Standards bodies and industry consortia continue to update and refine these standards to keep pace with evolving technology and emerging threats.

These new technologies “expand the attack surface,” which simply means there are several more vectors by which cybercriminals can access and tamper with data. Cloud services, in particular, demand the most robust encryption and access control. Hence the evolution of ISO 27001. AI amplifies this risk further, requiring AI-specific security measures which are still in their infancy. 

Modern threats, including ransomware and the hidden, but important, threat of social engineering, have spurred standards like NIST SP 800-53 to prioritize incident response and user training. As each new cyber threat emerges, evolving data security standards rise to counteract them. With anything from under a quarter to less than 10% of cyber attacks being divulged, data security is more important than ever.

The Role of AI and Machine Learning

AI and machine learning (ML) are something of a double-edged sword in this battle. While they introduce new weaknesses, they can also help fortify data security. Both can enhance data security, being able to analyze vast data sets to detect anomalies and even predict potential weaknesses or threats. This allows for automated threat detection, identifying patterns of malicious activity faster, and allowing for a near real-time response. 

AI-powered solutions can greatly expand intrusion detection systems, better authenticate users through behavioral analysis, and even help optimize security configurations quickly as new threats emerge. Machine learning algorithms improve over time, adapting to new attack vectors and reinforcing defense mechanisms.

Increasing Importance of Cloud Security

As we move toward cloud computing, unique security challenges rise, primarily because of the shared infrastructure and implicit reliance on third-party providers for services. This makes keeping your cloud data safe trickier, as well as raising privacy and compliance issues, particularly around securing the transmission of this information over the public internet. 

We’re already seeing a move to new standards and practices specifically focused on cloud security. Perhaps the most interesting is the CSA’s Cloud Controls Matrix. Of course, tighter encryption key management helps as well, ensuring data protection and regulatory compliance in the cloud. 

Like AI, the cloud brings new challenges, but also solutions. The nature of data colocation in the cloud system is useful for data recovery, for example. It allows for automated offsite backups (skipping the risk of human failure), builds in fantastic redundancy through geographically distributed servers, and makes for an effective disaster recovery solution. So, the cloud is one of our greatest new tools to ward off data loss and allow rapid restoration after an emergency.

Emerging Threats to Data Security

Sadly, criminals with a mission are some of the most creative and formidable people. In recent years, cyber threats have become sophisticated, bringing serious challenges. In particular, the rise of ransomware and phishing scams, exploiting human weakness. We also see the following.

  • Supply chain attacks, where vendors/suppliers are leveraged to attack other networks.

  • Zero-day exploits, which target tech vulnerabilities before patches are released.

  • Fileless malware, which leaves no trace for traditional antivirus tools to detect.

  • Identity theft/credential stuffing, which leverages stolen data for further attacks.

  • Advanced persistent threats, which are a tool of well-funded cybercriminal groups and need a prolonged infiltration of the network.

  • AI and IoT-specific attack strategies.

This is why adaptable, agile data security protocols for the internet and our networking applications are essential.

Ransomware and Phishing Scams

Ransomware and phishing attacks have become increasingly more sophisticated, using social engineering, advanced encryption, and even marketing-style tactics to bypass security. Today’s ransomware attacks can evade early detection and encrypt data across entire networks in the blink of an eye. Phishing has evolved from painfully obvious attempts to highly convincing fake email and website spoofing.

These “advances” challenge existing data security standards, requiring continuous updates and improvements to encryption protocols, authentication mechanisms, and employee training. Robust incident response plans and regular security assessments are critical to reduce their impact. 

IoT and Endpoint Security Challenges

Remember, we’re now dealing with an “increased attack surface” – multiple points where an unauthorized person could gain access to sensitive and private data. Few of us think of our TV or fridge as a potential data security threat, but as we move into the era of the IoT, we need to. IoT devices often lack built-in security features, making them susceptible to exploitation by cybercriminals for botnets, data breaches, or surveillance. It’s made harder by inherent vulnerabilities (again, a fridge is hardly the most sophisticated tech out there) and diverse ecosystems.

This makes endpoint security more critical than ever before, needing robust device authentication, encryption, and continuous monitoring. Endpoint security, like zero-trust network access, ensures IoT devices are adequately protected against unauthorized access and malicious activities, safeguarding sensitive data and maintaining the integrity of interconnected networks. It’s only as strong as its users are savvy, however, and regular patching and vulnerability assessments should now be routine. 

The Future of Data Security Standards

Of course, that’s the data threats we face now. Technology is still evolving, and so will the criminals that prey on its weaknesses. As quantum computing becomes a reality, so will quantum computing-powered attacks, needing the adoption of quantum-resistant encryption algorithms. 

AI-driven cybersecurity and increased IoT device security with greater emphasis on privacy and accountability will undoubtedly become a focus. Blockchain technology is set to play a larger role in data integrity verification, while biometric authentication methods may become more prevalent. Especially if “wearable technology” and implantable human-device interfaces come to fruition. As advanced, persistent cyber threats grow, we will likely also see standards prioritize global cooperation and information sharing to combat them.

Naturally, while our newly emerging technology will bring its own security worries, it will also power how we shape future data security standards – as with quantum computing. Much of it starts with a robust network and trustworthy data partners. If you’re ready to find solutions that work for you, why not let the Lightyear platform help you shape the best possible data security for your needs?

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