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Terrorism research has begun to focus on the issue of radicalization, or the acceptance of ideological belief systems that lead toward violence. There has been particular attention paid to the role of the Internet in the exposure to and promotion of radical ideas. There is, however, minimal work that attempts to model the ways that messages are spread or how individual participation in radical on-line communities operates. In this paper, we present a stochastic linear system to represent the evolution of contribution to a sample of 126 threads in an on-line forum where individuals discuss radical belief systems. To estimate or predict the time-varying contributions of agents for given onlineforum data, each agent’s contribution has been modeled as a state variable. We then use the expectation-maximization (EM) algorithm to identify the model parameters including the adjacency matrix of the graph constructed among participating agents along with measurement and system uncertainty levels in online-postings. Our approach reveals the identified dynamical influences among agents in the time-varying shaping of the contribution in a datadriven fashion. We use the real-world data from online-postings to demonstrate the usefulness of our approach, and its application toward on-line radicalization.

In this paper we argue that understanding terrorism within the new cyber environment of the twenty-first century is paramount for the intelligence services in the dawn of the 21st century. We believe that the intelligence services will have to confront this new trend in terrorism tactics in years to come whether they are fully prepared or not. This new type of threat will be one of the principal questions for intelligence services in the 21st Century.

The technological age has forced the U.S. to engage a new set of national security challenges. Several potential adversaries have cyberspace capabilities comparable to those of the U.S., and are constantly conducting surveillance, gathering technical information, and mapping critical nodes that could be exploited in future conflicts. How can the U.S. government best defend against future cyber attacks? Recent policy documents set out a strategy for securing all of cyberspace, which experts argue is impossible to implement, but also unnecessary. This thesis seeks to move the discussion beyond this stalemate by undertaking an analysis of the vulnerability of cyberspace to terrorist attacks. The first analysis examines the Code Red Worm and the Slammer Worm. These two worms were selected because they were highly destructive and spread faster than normal worms, making them well suited for assessing the existing security of computers and networks. The next analysis examines a staged cyber attack on critical infrastructure, entitled Attack Aurora. In the staged Aurora attack, researchers from the Department of Energy’s Idaho lab hacked into a replica of a power plant’s control system. This attack is the most recent staged attack and facilitates an analysis of vulnerabilities of critical infrastructures to cyberterrorism.

VOX-Pol Blog Post.

Digital platforms enabled the disturbing rise of domestic extremism, culminating with the January 6 attack on the U.S. Capitol. Militia groups use social media networks to plan operations, recruit new members, and spread anti-democracy propaganda, a new Digital Citizens Alliance (Digital Citizens) and Coalition for a Safer Web (CSW) investigation has found.

The latest Digital Citizens Alliance investigation exposes the fallacy that
much, if anything, has changed. Partnering with the Global Intellectual Property
Enforcement Center (GIPEC), Digital Citizens has reviewed dozens of examples
of how terrorist organizations continue to rely on digital platforms such as
Google, Facebook, YouTube and Instagram to promote hate speech and recruit.
What it underscores is that the problem is not a surface issue that can be
solved simply through greater vigilance or the hiring of more content monitors.
The true cause of these troubling issues is the business model of these
platforms. When Cambridge Analytica inappropriately received the personal
information of at least 87 million Americans harvested by Facebook there was
no breach—Facebook turned that information over to the company because its
business model is to monetize users’ personal information with advertisers and
third parties.