Diana Waithanji
Diana Waithanji believes data privacy is a human right. She works as a cybersecurity professional at SAP specifically SAP Cloud Infrastructure in Germany. She is a TechWomen USA fellow 2025 at Google and an AFRIKA KOMMT Germany alumni 2022. Diana sits in two technical committees at the Kenya Bureau of Standards (KEBS) and serves as a board member at Nivishe Foundation. Diana is also a founder of Wahandisi La Femme, an initiative that mentors girls in rural Kenya to get into tech and engineering.
Sessions
This Birds of a Feather session will focus on how AI tools are being used to secure environments, the training necessary for teams to identify security issues and the impact of AI on job security for security jobs. Participants will discuss and share experiences on:
- AI Tools in Cybersecurity: Explore how AI tools are currently enhancing security and the most effective tools available today.
- Training and Skill Development: Discuss recommended training programs and certifications that help teams leverage AI in cybersecurity.
- Job Security and AI: Debate whether AI will replace certain roles or create new opportunities, and how professionals can stay relevant.
At the end of this session, participants will leave with ideas on using AI tools, available training for their teams, and strategies to remain irreplaceable in an AI-driven world.
This open discussion invites all cybersecurity professionals regardless of the experience level.
The purpose of this panel is discuss where the participants see the still-young, still-emergent discipline of Detection Engineering going.
The tools and know-how presented over the last 2 days in the village will be pitted against ideas from Diana (moderator) and the audience.
The panelists will try to explore together how the detection engineering landscape might evolve over the next few years,
As AI systems evolve, integrating security from the design phase is crucial, following the "shift left" approach to prevent vulnerabilities. This session offers an overview of threat modeling for AI systems, including organizing engaging sessions, using appropriate tools, and applying methodologies such as STRIDE. Participants will learn to proactively address security concerns and in turn ensure robust protection by identifying and mitigating potential threats specific to AI technologies - with reference to OWASP research. The session will also provide tips on making threat modeling sessions interesting and interactive in order to ensure active participation and effective outcomes. The goal is to make security a foundational element in AI system development rather than an afterthought.