Data is a powerful asset, yet many security teams are not fully leveraging its potential. Why? These teams operate under tight time constraints, with limited resources and a need to prioritize urgent issues first. This often leaves minimal time for in-depth vetting and analysis of information, allowing valuable insights to go unnoticed. To help security teams make the most of their data, strengthen defenses, and minimize risks, focus on these four key areas.
#1: Prioritize Data Reliability
While each tip is vital, reliable data remains paramount. Accurate intelligence empowers decision-makers to craft effective strategies under high-stakes conditions, while unreliable data can lead to costly missteps.
According to a Tech Target article on data, “Raw data can lead to useful insights only if it has been carefully collected and stored to ensure its reliability when needed. If it is not reliable, it becomes more difficult — if not impossible — to derive meaningful information from the data.”
For security teams struggling to manage a comprehensive list of data sources, partnering with an external provider can be a strategic solution. A well-curated, thoroughly vetted source list is essential for ensuring data reliability.
One effective approach to accessing reliable, credible data is drawing from high-quality curated collections. The best collections thoroughly vet sources and platforms to determine which consistently deliver valuable, accurate information. Organizations want to draw from various sources, including social media, international, national, and local news outlets, official agencies such as government and emergency services, as well as activist and extremist platforms. Culling data from a range of sources helps to avoid gaps in knowledge and establish accuracy in information.
Reliable data is a significant advantage for leaders who are responsible for making important decisions. But faulty data is dangerous; it could lead to unsound decisions and strategies from leaders, putting people, assets, and operations at risk, as well as wreak havoc among private citizens who decide to protest or contribute to unrest because of false information they believe is truth.
The concept of misinformation has existed since humans began communicating with each other, and the proliferation of social media and other technology platforms and programs have enabled invalid information to spread more quickly now – passing from one unverified source to another at viral speeds.
AI is a true game-changer for businesses, particularly in this area. It offers many positive benefits but also can present false news as very convincing fact, further complicating the intelligence industry and making the process of prioritizing data reliability even more critical than before.
#2: Prioritize Historical Data
While it is important to stay informed of breaking news and events, it is equally important to be aware of past incidents to identify trends. By analyzing past incidents, media coverage, and social media sentiment, security teams gain insights into patterns and underlying factors influencing current events, which enables them to spot recurring issues, emerging risks, and real, but undetected vulnerabilities that may not be obvious when leveraging only current data. Once teams identify holes in their strategies and operations, they can course correct to improve their organization’s real-time security posture and long-term planning capabilities.
#3: Prioritize Noise Reduction
An excess of alerts can be overwhelming, making it difficult to discern critical data points, and leading to delayed responses as actionable information gets buried. Yet receiving too few alerts can lead to gaps in knowledge. The answer lies in identifying the right alert tools for your specific needs.
For organizations monitoring multiple regions or locations, advanced alerting tools are essential. The most effective tools offer the ability to set thresholds, categories, or severity levels to ensure that only alerts relevant to your operational priorities are delivered. This customization allows security teams to remain informed on a variety of locations and threats while minimizing distractions.
The goal is to implement a system that filters out unnecessary noise, allowing teams to focus solely on information requiring immediate attention and action. Effective noise reduction not only improves response times but also enhances situational awareness, enabling teams to act faster with greater precision.
#4: Prioritize Data Contextualization
Real-time information is clearly important. However, knowing why a disruptive event is occurring or is anticipated to occur is just as important to protecting an organization’s people and operations.
Technologies like AI are indispensable for staying informed of breaking events; they are the ultimate time-savers when it comes to pulling open-source data. But people are the ones who add context, evolving the data from information to insight. When contextual insights are applied to raw data, that intelligence becomes even more powerful – it becomes actionable insight.
In addition to adding context and breaking down the nuance of current events, human analysts can assist in data validation, which directly ties in with Tip #1 and assist in avoiding misinformation and disinformation.
Human experts keep an eye on the machines, verifying the information and vetting key facts and events to ensure that only accurate details are shared with decision makers. This unique blending of technology plus expert insights is a security team’s ultimate answer to receiving timely, relevant, and contextual intelligence.
Let Intelligence Be Your Data Differentiator
While leveraging data is critical to an organization’s security plans, a successful strategy involves more than just receiving every alert that appears relevant and centers around prioritizing data reliability, acknowledging the importance of historical data, focusing on noise reduction, and applying context to data. In some cases, organizations need to expand bandwidth and partner with an outside expert to accomplish these activities.
Seerist was founded for this exact task and is passionate about leveraging human experts to validate data and provide context based on on-the-ground knowledge. There is great power in fusing technology with human experts; while AI fundamentally lacks experience, judgment, and nuanced understanding, human analysts are able to bring this key information to decision makers.
The strongest risk mitigation strategy is rooted in data confidence; contextualizing intelligence is paramount. If your organization needs to strengthen its data contextualization, or better ensure its data is properly vetted by local experts, it might be time to align with a partner focused on these very tasks. To learn more, or to trial the Seerist platform, contact us today.
