3 Major Defense Intelligence Trends from DoDIIS

Earlier this month we attended the Department of Defense Intelligence Information System (DoDIIS) Worldwide Conference, and did a demonstration of Kyndi’s Anticipatory Computing Environment. This year’s theme was “cybersecurity” and featured senior leaders from the Intelligence Community, Department of Defense, and partnering civilian, military and industry solutions providers. We were excited to participate in the event and extend our gratitude to Carahsoft for hosting us in their booth.

The Defense Intelligence Agency  Director, Lieutenant General Vincent R. Stewart, commented prior to the event: “Traditional cybersecurity is passive and reactive. Together, with our government and private sector partners, we must develop new and better ways to respond to threats, not just monitor them.”

Melvin Cordova, a defense intelligence expert and Kyndi Innovation Advisor, joined us at DoDIIS and noted that there were three key trends in cybersecurity that received significant attention this year.

Preventing Strategic Surprise

While agencies can effectively collect data and information to assess a situation in retrospect, effective and efficient use of that data to anticipate and prevent situations remains elusive. Data analysis solutions that provide targeted results, while improving the timeliness and relevance of information, are especially attractive within the Intelligence community. As Cordova noted, “We are in a knowledge-intense completion era, and whoever connects the dots, creates knowledge, and achieves a decision cycle faster than the adversary wins.”

Monitoring Intent

In cybersecurity, knowing and learning more about the person behind the keyboard is an increasingly valuable advantage. Intelligence solutions that facilitate large-scale evaluation and monitoring of personnel, particularly focused on insider threats, are earning attention. Knowing the integrity and trustworthiness of staff in anticipation of threats requires having the ability to assess intent. Solutions that can create models for assessing intent are therefore seeing more demand.

Identifying Behavior

Many constituents within the Intelligence Community are specifically seeking models and algorithms that can identify “rogue and illicit behavior” in cyberspace. Moving beyond intent and into action, these threats may be “unknown unknowns,” requiring anticipatory modeling for identification.

Kyndi’s AI-based solutions are aligned with all three of these key Intelligence trends, particularly Kyndi’s Quantum-inspired algorithms which are language and data domain agnostic and capable of weak-signal analysis for semantics. Cordova commented on how Kyndi’s models can, for example, “examine the relationship between specific types of emotional sentiments” including “specific linguistic and grammatical markers of deception across languages.” Kyndi can use unstructured source material across decades, countries, cultures, and languages to identify threats before they occur and provide clear strategic advantages to U.S. Intelligence agencies.