The continuous evolution of technology is one of the world’s few true constants— and with it, the changing security challenges that organizations face. In 2024 and beyond, staying ahead of emerging threats will be a key part of protecting sensitive data against potential breaches. Take a look at what our executive security team flagged as the top 10 concerns that will dominate the cybersecurity landscape:

1. AI Governance:

The widespread adoption of generative AI technologies in workplaces has raised concerns surrounding governance and control mechanisms. With the potential for AI models to access sensitive data sources, organizations face heightened risks of unintentional exposure and data breaches. Without proper oversight, the use of generative AI could lead to the accidental leakage of sensitive, personal, regulated, or critical data, posing significant security and privacy risks. In the wrong hands, exposures like that could result in severe repercussions, including data breaches and regulatory non-compliance.

To address these challenges, organizations must establish detailed governance frameworks to regulate the access and usage of data by AI applications effectively. Creating and enforcing specific AI data usage policies across all data assets is essential for detecting and mitigating policy violations effectively. In the event of an incident or policy breach, organizations must have mechanisms in place to trigger automatic remediation actions, controls, and measures to minimize the risk of unwanted exposure, unauthorized access, and misuse of data.

2. Insider Threats:

Insider threats remain one of the most challenging security concerns for organizations, primarily due to their covert nature and potential for significant damage. Detecting insider threats requires a comprehensive approach that leverages advanced technologies and methodologies to identify suspicious activities and behaviors.

Telemetry data from various log sources is a critical source of information for detecting insider threats. When security teams analyze log data from diverse sources such as network traffic, system logs, and user activity logs— organizations can gain insights into anomalous behavior patterns indicative of insider threats.

Advanced User and Entity Behavior Analytics (UEBA) models play a pivotal role in identifying anomalous behaviors that may indicate malicious intent. These models leverage machine learning algorithms to analyze user behavior across multiple data points and identify deviations from normal patterns, helping organizations detect potential insider threats proactively.

Layered security tools further enhance the detection capabilities for insider threats by providing multiple lines of defense against unauthorized activities. These tools encompass a range of security measures, including intrusion detection systems, endpoint security solutions, and data loss prevention mechanisms, working together to detect and mitigate insider threats effectively.

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3. Cloud Migrations & Cloud Data:

The ongoing shift of large enterprises from traditional on-premise data centers to cloud-based environments— commonly known as “lift and shift” — reiterates the importance of ensuring the security of cloud infrastructures. However, a significant challenge arises when organizations fail to refactor their applications to become cloud-native, often exposing themselves to additional risks. Traditional on-premise data centers operate differently from cloud-based environments, necessitating careful consideration and strategic planning during the migration process.

Refactoring applications to be compatible with cloud environments is essential to mitigate potential security vulnerabilities and minimize the introduction of new risks. Without proper adaptation, organizations may inadvertently create security holes that compromise the integrity and confidentiality of their data. Thus, ensuring that applications are effectively refactored for cloud hosting is a critical step in safeguarding against cybersecurity threats.

4. Misconfigurations:

Despite the widespread adoption of Infrastructure as Code (IaC) for deploying cloud assets, misconfigurations continue to pose significant risks to organizations’ security posture. While implementing robust security measures and validation processes during the deployment pipeline is crucial, many organizations overlook the importance of validating for configuration drifts once environments are live.

To effectively mitigate the risk of misconfigurations, organizations must prioritize continuous monitoring for configuration drifts and implement automated correction mechanisms. Organizations can identify and rectify any deviations promptly by continuously comparing the live environment against predefined baselines. This proactive approach ensures that production environments remain aligned with security best practices and regulatory requirements, reducing the likelihood of security incidents and data breaches.

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5. Biometrics & Facial Recognition:

The growing adoption of biometrics and facial recognition technologies presents significant challenges in terms of data privacy and security. As organizations increasingly leverage these technologies for authentication and identification purposes, they must confront the inherent risks associated with the collection and storage of sensitive biometric data.

One of the primary concerns surrounding biometrics and facial recognition is the potential for data breaches and unauthorized access. Unlike traditional authentication methods such as passwords or PINs, biometric data, once compromised, cannot be easily changed or revoked. This places a greater emphasis on organizations to implement stringent security measures to safeguard biometric data against unauthorized access and misuse.

Additionally, there are ethical considerations surrounding the use of biometrics and facial recognition, particularly concerning individual privacy and consent. Organizations must ensure transparency in their use of these technologies and obtain explicit consent from individuals before collecting and processing their biometric information.

6. Supply Chain Software:

The software supply chain remains one of the most formidable threats facing organizations across various industries. Recent high-profile incidents, such as the SolarWinds and Log4j vulnerabilities, have emphasized the importance of mitigating risks associated with software dependencies. These incidents have demonstrated the far-reaching implications of supply chain vulnerabilities, highlighting the potential for widespread exploitation and disruption.

The emergence of vulnerabilities like the XZ vulnerability further illustrates the persistent nature of supply chain threats, indicating that such risks are likely to persist in the long term. As cyber threats continue to evolve and adversaries exploit weaknesses in software supply chains, organizations must adopt a proactive approach to safeguarding their systems and data.

Mitigating supply chain risks demands heightened vigilance and proactive measures to secure software dependencies effectively. Organizations must implement robust strategies for vetting and managing third-party software components, ensuring that they adhere to stringent security standards and undergo thorough scrutiny before integration into critical systems. Additionally, organizations should prioritize ongoing monitoring and assessment of software supply chain activities to detect and respond swiftly to any signs of compromise or vulnerability.

7. Identity and Access Management (IAM):

In 2024, cybercriminals remain steadfast in their pursuit of user credentials and service accounts, recognizing them as lucrative targets for illicit activities. With the ongoing threat landscape, organizations must prioritize robust Identity and Access Management (IAM) practices to safeguard against unauthorized access and data breaches.

The crux of effective IAM lies in implementing principles such as least privilege, just-in-time access, and conditional and risk-based access controls. By adhering to these principles, organizations can ensure that users and service accounts are granted only the necessary permissions required to perform their designated tasks. This approach minimizes the risk of excessive access rights, limiting the potential damage that could result from compromised credentials.

IAM strategies must be applied consistently across all assets within an organization’s infrastructure. Whether accessing sensitive data repositories, critical systems, or cloud-based applications, stringent IAM controls must be enforced to maintain the integrity and confidentiality of organizational data.

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8. Software Vulnerabilities:

Identifying and patching software vulnerabilities remains critical for maintaining a secure IT environment, especially in light of ongoing challenges faced by the security industry. Software vulnerabilities persist as one of the most significant pain points, with breaches occurring due to exploitable weaknesses in commonly used software. As organizations continue to scrutinize the software supply chain in response to repeated breaches stemming from vulnerabilities, gaining visibility into the code base becomes paramount. Transparency with customers about the steps taken to address vulnerabilities is essential for building trust and reducing the risk of vulnerabilities propagating unchecked.

To address these concerns, organizations must implement robust vulnerability management processes to detect and remediate potential security flaws effectively. This involves regularly scanning codebases and software systems for vulnerabilities and prioritizing patches based on severity and potential impact. Organizations can mitigate the risks posed by software vulnerabilities and bolster trust in their products and services by staying proactive in vulnerability management and fostering transparency with stakeholders.

9. Absence of Proper SIEM Solutions:

Security Information and Event Management (SIEM) solutions are essential for monitoring and detecting security incidents. However, traditional SIEM solutions struggle to handle the volume and variety of logs generated daily. Deploying advanced SIEM solutions capable of handling large-scale data analysis is imperative for proactive threat detection. The ability to predict and detect security breaches is a critical capability in today’s threat landscape. However, organizations face significant challenges due to the sheer volume and diverse formats of logs generated daily.

Traditional Security Information and Event Management (SIEM) solutions struggle to cope with the scale and complexity of modern data environments. These solutions often fall short in ingesting, parsing, and alerting on the vast amount of log data generated across various systems and applications. As a result, organizations find themselves unable to effectively monitor their security posture and detect emerging threats in real-time.

10. Security Tool Saturation:

With recent attacks and breaches, companies are increasing their security budgets and on the other side, more security related products are popping up in the market that offer similar or equal capabilities with very small differences between them. The conjunction of these two leads companies to buy security related products just to spend the budget, which many times leads to an overlap of capabilities between the products, which in turn brings an operational challenge—what tool should be our source of truth?

Security teams must ditch the mindset of having every single tool and instead take a capabilities driven approach where they define what capabilities they want to have in place and for what and then scout the market for such capabilities. Once they find a solution they should map what other capabilities the solution offers and have a concrete map so that they have a minimal overlap between different tools.

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BigID’s Approach to Data Security

Modern organizations need flexible and scalable solutions tailored for their specific needs. BigID is the industry leading platform for data privacy, security, compliance, and AI data management, leveraging advanced AI and machine learning to give businesses the visibility into their data they need. Reacting to breaches and other cyber attacks isn’t enough. The real work starts long before.

  • Know Your Data: Automatically classify, categorize, tag, and label sensitive data with unmatched accuracy, granularity, and scale.
  • Improve Data Security Posture: Proactively prioritize and target data risks, expedite SecOps, and automate DSPM.
  • Remediate Data Your Way: Centrally manage data remediation – delegate to stakeholders, open tickets, or make API calls across your stack.
  • Enable Zero Trust: Reduce overprivileged access & overexposed data, and streamline access rights management to enable zero trust.
  • Mitigate Insider Risk: Proactively monitor, detect, and respond to unauthorized internal exposure, use, and suspicious activity around sensitive data.
  • Reduce Your Attack Surface: Shrink the attack surface by proactively eliminating unnecessary, non-business critical sensitive data

For security that adapts to evolving threats in 2024 and beyond— get a 1:1 demo with our experts today.