Table of Contents Introduction Historical Overview Tradecraft Evolution Defining an Analytical Framework Next Steps: Testing and Refining the Model Conclusion End Notes About the Authors Canadian Global Affairs Institute Introduction The weaponization of disinformation that Russia practises has achieved substantial recognition in recent years. A historical constant for over a century, these activities were most recently popularized after Russia’s 2014 annexation of Crimea and progressively so in light of the 2016 U.S. election. Today, they are one of the most important components of Russia’s hybrid warfare toolbox in relation to the West and Russia’s near-abroad.1 The difficulty of proving a falsehood drives their success, and this difficulty is due largely to Russia’s ability to hide its role as originator, particularly in cyber-space.2 This paper confronts the problem by theorizing a framework through which attribution may be achieved. We begin by mapping key Russian disinformation waypoints, from its origins in Soviet-era counterintelligence doctrine to early post-Soviet usage in the First and Second Chechen Wars, retooling in Georgia and at-scale deployment in Ukraine. We frame this review with three useful first principles, or characteristics, of disinformation: Truth seeding, which we define as splicing, or combining facts with fiction to legitimize disinformation and confuse target audiences; Network effects, the deliberate repetition of chosen narratives through multiple, seemingly distinct conduits to increase disinformation’s traction in a given community; Chaotic ambiguity, or the spreading of multiple, often contradictory narratives to obfuscate reality and draw focus away from the underlying truth. We also call attention to an inherent trait of Russian disinformation: anonymity. While anonymity contributes to the problem of attribution, it is also paradoxically a limitation because it substantially mitigates the power of a given narrative. Next, we discuss the challenges of uncovering present-day disinformation campaigns given their residency on and exploitation of social media platforms that assist in obfuscating truth. To solve these challenges, we propose a framework that draws on big-data analytics, anchored in the need for gathering and storing large amounts of data (the sheer volume of social media data makes this first task critical), followed by a refining or filtering step that ensures data are structured uniformly so that efforts to uncover the identified first principles are possible. Finally, an emphasis is placed on the importance of a mechanism to frequently query data, given the exponential rate at which new data appear on social media
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