Implementing intelligence software for security is now an initiative for organizations undergoing digital transformation, and the main subsection of analytics tools deployed in organizations is cyber threat Intelligence tools. These tools help to provide visibility into an organization’s digital footprint, attack surface, and connectivity to the malicious digital footprint threatening its organization. It helps organizations improve security operations, accelerate incident response, and provides analysts the critical information required to disrupt threat actors. By being able to visualize and understand this data, security personnel can make more informed decisions and mitigate financial and operational threats to their organization. With the amount of public data associated with an organization, it is an absolute necessity that they implement the proper software to understand better where threats and vulnerabilities are present and act on that data.
Key Benefits of Security Intelligence Software
- Quickly discover and understand organization digital footprint, attack surface, and threat landscape.
- Connect layers of sources into a single platform to illuminate unseen risks and connections.
- Enable data-driven decision making for security process optimizations.
- Discover new insights that can enable the organization to take proactive security measures.
Why Use Security Intelligence Software?
In today’s big data world, every organization is generating a vast and expansive digital footprint. Inside this data are insights that can make or break organization security. The question should not be why use this software, but why not use security intelligence software? There are infinite insights a security and risk professionals can pull from their data, but here are five essential reasons to use intelligence software purpose built for security.
Information Discovery and Real-time Alerting
The most basic way to use security intelligence software is for open source intelligence. Most security teams use the software for specific use cases such as event intelligence, brand intelligence, protective intelligence, or vulnerability intelligence. Security teams collect data, and the security intelligence software system correlates information using machine learning methods and rule-based policies. Because the system normalizes all the unstructured data collected, the newly organized data can be processed to alert security analysts of threats and events of interest. Alerts will trigger when information passing through the system triggers a policy or when the native intelligence capabilities of the software expose a vulnerability or discover a threat. While the software processes this threat data, the system will label the information as an alert and end-users, who enabled the policy are alerted.
Data-Driven Security Decision-Making
A key component of digital transformation is to become a data-driven organization. Becoming data-driven also applies to security and digital risk management teams. By using data to drive every security decision the organization makes, it can optimize security processes and achieve its fullest resiliency potential. Organizations should be leveraging security analytics and intelligence tools to understand all the digital risks impacting the organization, including threat intelligence, which risk events are becoming trends, which threats to focus on first, and process optimization. Each security decision made around prioritizing digital threats and vulnerabilities will use threat data and security intelligence software. Every security manager and leader will be asking what intelligence data helped determine a major security decision or action.
Measure and Understand External Risk
Another main reason that organizations adopt security intelligence tools is for tracking and measurement of external risk. Data visualization will track key risk indicators in real-time. Security intelligence platforms and self-service security intelligence software will determine then if the risk is exceeding or below critical risk thresholds. By developing an acute understanding of how and why the threat landscape is shifting, the security team will adjust and mitigate a threat quickly. So if a security team is unwittingly failing on covering an area of risk or a significant event breaks, they can recalibrate their time and effort. There is also a considerable difference in knowing where to discover digital risk and understanding the impact of unmitigated digital risk.
Discover New Actionable Insights
Security intelligence tools combine data from a variety of sources. Security analysts can use this integrated data to find correlations between different layers and act on previously hidden risk insights. For example, security analysts can uncover exposures that are being driven by well-intended revenue-driving processes. The security team will discover the use of cloud service domains in the organization and reveal the use of shadow-IT. Security teams are generally siloed from business units and do not have access to real-time digital business information. These risk insights have traditionally been challenging to discover and have a material impact on security if not mitigated promptly. However, by using intelligence software properly, organizations are at a proactive advantage to reduce digital risk at the speed of change they never had in the past.
Support Compliance and Fill Security Gaps
Many industries have specific compliance requirements determined by various governing bodies, but security intelligence software can be used across several industries to maintain compliance standards. Many different industry-specific compliance requirements exist. Still, most of them require security teams to ensure the confidentiality of sensitive data, acute knowledge of digital assets is maintained. Digital systems and processes, such as social media usage and the organization’s digital attack surface on the cloud, must be consistently monitored. For example, security intelligence systems help maintain GDPR compliance by verifying external security controls, facilitating visibility into the security state of sub-processors, and alarming security staff of security threats, as is required by GDPR.
Another example would be used in the health care sector to maintain HIPAA compliance. Security intelligence systems should enable ta healthcare organization audit and monitor for private data exposures on the public internet. Organizations will ensure no external attacks are abusing the brand, no organizational data leaked or for sale on the dark web, and alert users to cyber vulnerabilities and emerging threats that would immediately impact the organization’s cyber exposure.