The Kairos Research Team, together with our partners at the University of Arkansas at Little Rock (UALR), proposes to develop an intuitive web-based Twitter Follower / Friend Assessment (TWIFFA) tool and associated app that can identify bots and bot-assisted accounts within a users network of followers and friends. TWIFFA will enable a user to input their Twitter credentials, scan followers and friends for signs of bots or bot-assisted accounts, and assess the level of threat associated with flagged accounts. Innovative features of TWIFFA include: (1) explainable, multi-class bot detection algorithms that utilize a tiered approach to achieve high accuracy without sacrificing scalability; (2) frequent retraining of detection algorithms via user feedback to ensure robustness against constantly evolving bot behaviors; (3) multi-level threat assessment combining network-level focal structure analysis (FSA) with individual-level measures of a nodes power and role within the network; (4) operational response capabilities such as the ability to monitor, block and unfollow bot and bot-assisted accounts in batches, as well as the ability to label and track watchlists of suspected botnets involved in coordinated information campaigns.
Benefit: The increasing adoption of social media platforms has led to dramatic increases in the number of synthetic accounts, or bots, masquerading as humans and interacting with other users (both human and bot). While bots are often little more than a nuisance (e.g. spam bots), a substantial amount of bot activity occurs as part of coordinated information campaigns; e.g., a foreign adversarys attempt to manipulate crowd opinion. With over 320 million active monthly users, the microblogging platform Twitter is especially fertile ground for bot-driven disinformation campaigns. The ability to detect harmful bots and mitigate the influence of bad faith actors whether on Twitter or other platforms is therefore of great importance to the national security sector especially. In addition, this capability can also address demands in a wider variety of industries with social media presences, including technology, retail, and education. Reflecting this need, the overall cyber security market is predicted to reach $172 billion by 2025 with a compound annual growth rate of 10%. The specific market of social media security is predicted to reach $2.72 billion by 2025 with a compound annual growth rate of 17.57%. Within this segment, the market for bot detection tools is predicted to reach $1.19 billion by 2023 with a compound annual growth rate of 42.2%.
Keywords: Twitter, Twitter, Bot, information warfare, Botnet, fake news, Sybils, bot detection, social bots
