Why SIEM is Essential Now: Moving from Point Defense to Line-of-Sight Visibility

迎健太

Even with EDR, email security, and WAF in place, breaches still occur. How do you visualize the attack chain as a "line" when isolated, point-solution defenses only show you the "dots"?

EDR, email security, WAF, and Firewalls. Over the past decade, most Japanese companies have steadily layered these individual security products. It is natural to think: "We have products at every layer, so our defenses are sufficient." Yet, breaches continue to occur. Furthermore, it is not uncommon for a breach to take nearly a year to be detected.

The issue is not the performance of individual products. It is that a blind spot exists between them where no one is looking. This article explains why these gaps occur and why you should reconsider SIEM as a realistic option to close them.

Point-Defense Products Only Watch Their Own Turf

Email security products assess threats the moment an email is delivered. EDR monitors process behavior on endpoints, WAF inspects HTTP requests to web applications, and firewalls monitor traffic at the network perimeter.

Each product excels in its own domain. However, they do not know what is happening outside of it. An email security product has no way of knowing that the sender of a blocked email has started communicating with an internal terminal. EDR has no way of knowing that a destination IP address was blocked hours earlier as the source of a suspicious email.

Consequently, the alerts generated by each product are isolated "points." Multiplying these points is not the same as having visibility into the whole picture.

Attacks Advance in "Lines"

Consider the attacker's perspective. A typical attack chain progresses through stages: initial intrusion, privilege escalation, lateral movement, and data exfiltration. Crucially, attackers do not limit their actions to a single product or log source.

Take a concrete scenario. One morning, targeted emails are blocked by your email security product. For that product, it is a successful defense, leaving behind a single low-severity log. However, a few emails slip through, and an employee opens an attachment. Hours later, EDR detects a slightly suspicious process on that terminal, but confidence is low, and it is flagged as a low-priority alert. That night, successful authentication is logged from that terminal to a file server it rarely accesses. Days later, firewall logs record intermittent external data transmissions.

Viewed in isolation, each step of this scenario seems like an event that does not require action. However, the moment you correlate the fact that the sender IP of the blocked email matches the destination IP of the suspicious process detected by EDR, a clear attack chain emerges. This conclusion is only possible from a "line" perspective that crosses multiple log sources and correlates them chronologically.

This creates a paradox. Adding more tools increases the number of "points." Without a mechanism to connect them, you merely increase the consoles and alerts analysts must watch, which can actually decrease overall visibility.

Data Shows a Long Detection Gap

Data supports the existence of this structural issue.

According to a 2021 survey by Cyber Security Cloud analyzing over 1,000 personal data breach cases in Japan caused by unauthorized access, it took an average of 349 days from the attack to detection, and another 82 days from detection to public announcement. More than 60% of cases took over 90 days to detect. Globally, IBM's "Cost of a Data Breach Report 2025" shows that it takes an average of 181 days to identify a breach and another 60 days to contain it, totaling 241 days. While this is the shortest timeframe in nine years, it still represents eight months.

To be clear, these figures do not prove that a lack of SIEM is the cause of these delays. However, the data aligns with the point that managing alerts individually makes it difficult to see the full picture of a breach.

Meanwhile, SIEM adoption remains low in Japan. The JIPDEC and ITR "Enterprise IT Use Survey 2025" indicates that only 28.5% of companies have implemented SIEM/XDR (57.4% including planned deployments). A Nikkei Xtech survey puts adoption at just 17%. While surveys vary, the consensus is around 20% to 30%, meaning the majority of companies remain in the "point defense" phase.

"SIEM is Expensive and Complex to Operate"—A Half-Truth

The barriers to adoption are clear, and traditional SIEMs have historically presented high hurdles. Recommending SIEM without acknowledging this is unrealistic.

Traditional SIEM cost structures suffer from two issues. First, pricing models are tied to log volume. Because costs escalate as more logs are ingested, organizations limit log collection to stay within budget, creating blind spots in their "line visibility." Market rates for SaaS SIEMs are reported at 100,000 to 300,000 JPY/month for 1–5 GB/day, and 300,000 to 1,000,000 JPY/month for 10–50 GB/day, with the burden increasing alongside log volume. Second, traditional SIEMs require dedicated analysts to design correlation rules, tune systems, and perform initial alert triage. These licensing, labor, and training costs put SIEM out of reach for all but the largest enterprises.

Furthermore, operational fatigue is a known issue. According to Tines' "Voice of the SOC" survey, 81% of SOC members experience stress, and 67% report burnout. The traditional, labor-intensive operational model has proven unsustainable.

Gathering Logs Only Creates Another Alert Source

However, simply deploying a SIEM is not a silver bullet.

If you centralize logs without a system to design correlation rules and triage alerts, SIEM merely becomes another point source generating high-volume alerts. Relying on manual labor for this triage is precisely what drove the high costs and operational burdens of the past.

For SIEM to be a viable option, it must meet two conditions: it must be a low-cost platform that allows ingestion without volume-based cost worries, and it must leverage AI to handle correlation analysis and initial triage. Only then does "line visibility" stop being a luxury reserved for large enterprises. This combination is increasingly known as an "AI SOC" and is becoming the standard model for SIEM operations.

The Yagura Approach: Combining DataLake SIEM and AI SOC

Yagura offers a proprietary SIEM (DataLake platform) designed specifically to meet these two conditions.

The architecture is simple. By building the log platform on a general-purpose DataLake architecture, storage and ingestion costs are kept lower than traditional SIEMs, eliminating the dilemma of limiting logs to save costs. It is designed to ingest logs from your existing EDR, email security, WAF, firewalls, and cloud environments. Next, AI handles correlation analysis and initial alert triage, removing the need for a dedicated, round-the-clock analyst team. Humans only step in to address the small number of high-confidence incidents that the AI has correlated and escalated.

Pricing starts at approximately 300,000 JPY/month, depending on log volume and configuration. This represents an investment of a completely different scale compared to traditional "SIEM + dedicated analyst" models.

Conclusion: Don't Scrap Your Point Defenses; Add the Line

To clarify, this does not mean discarding point defenses like EDR or WAF. They are essential for detecting and stopping threats at specific stages of the attack chain, and your existing investments remain valuable. The only missing piece is a system to connect these points chronologically at a higher layer.

The fact that breach detection takes hundreds of days suggests that most organizations lack visibility into the overall attack chain. However, low adoption rates indicate that this is a common challenge—and an opportunity to gain an early advantage.

The first step does not need to be massive. We recommend starting with an inventory: map where your logs are stored across different products and determine if you have a way to correlate them. Once those gaps are clear, the decision to evaluate SIEM will stem from architectural necessity, not just industry trends.

Related Service: Click here to learn more about Yagura AI SIEM, which delivers "line" visibility through centralized log aggregation, cross-sectional AI analysis, and automated reporting.