The Electronic Hive Mind and Cybersecurity: Mass-Scale Human Cognitive Limits to Explain the “Weakest Link” in Cybersecurity

Introduction

Online is where a large portion of the world’s population live and breathe and have their being. As the cyber footprint is broadened—through mobile devices, locational apps, games, smart cars, medical devices, and the Internet of Things (IoT)—there are that many more potential attack surfaces through which people may be affected negatively through hacks and cyberattacks. Adam Segal (2016) writes: “An estimated 75 percent of the world’s population now has access to a mobile phone, and the Internet connects 40 percent of the planet’s population, roughly 2.7 billion people. Information and communications networks are embedded in our political, economic, and social lives.” (p. 1). He predicts an intensification of the battle over cyberspace, with Year Zero of this battle starting June, 2012 or June, 2013, given a number of high profile uses of cyberattacks by nation states. In 2016, there were four billion cyberattacks, a major jump from the 600 million in 2015 (IBM, as cited in Balaish, Aug. 21, 2017). By 2021, cyber crime is estimated to cost US$2 trillion (Cybersecurity Ventures, as cited in Balaish, 2017). Cybersecurity efforts focus on preventing the illegal exploitation of technology systems and the protection of data integrity, among other things.

In cybersecurity studies and practices, humans are known as “the weakest link” (Belbey, 2015); their decisions and actions put their information at risk and also those of others. Humans will use and re-use weak passwords or leave passwords unchanged from factory defaults; they over-share with friends, family, and strangers; they click unthinkingly on risky links and download files (with malware) from others; they will receive emails from strangers or apparent colleagues and click on links or download files without thinking; they’ll receive USB drives at conferences and use these in their laptops and desktops; they’ll download apps from unknown websites; they will visit the Web’s dark spaces to buy illicit goods; they’re prone to being social engineered; and they do not begin to understand the “cyber” threats arrayed against them.

One way to begin to understand why people are so vulnerable to cyber-exploitation is to not only explore people and their individual cognitive limits and biases but also to explore the “electronic hive mind” around cybersecurity to understand mass-scale human cognitive limits and biases. A “mind” refers to consciousness, thinking, intellect, and will. A “hive mind” refers “group intelligence” (Jones, 2011, p. 2). A hive mind refers to the consciousness, thinking, intellect, and will of a collective of people. Such collectives occur organically, with people coming together around shared interests. A core purpose of a hive mind is to learn from the environment, from others outside the hive, and from each other. Bloom’s taxonomy of learning domains types (1956) can apply to group intelligence: the steps include remembering, understanding, applying, analyzing, evaluating, and creating. (Conceptualize teams collaborating around shared research and design and development work.) As in learning communities, consensus and dissensus are both important. Certainly, if hive minds can function like individual ones, they can also be misled, misinformed, irrational, and deluded.

A hive mind does not have centralized control; rather, control is distributed and devolved, with each member and small groups within the collective making decisions, sharing ideas, and taking actions. How these hive minds coalesce and evolve is determined in part by the group impetuses and interests, and evolved social norms. Hive minds can be informed by co-created culture. In the same that that the cultural features of a society may head off some possible futures and make others more likely (Dieffenbach, 1992), how “hive” populations evolve may also change.