Gender and Intersectional Bias in Cybersecurity for Next Generation Wireless Networks

The advancement of wireless networks towards sixth-generation (6G) and pervasive artificial intelligence (AI) underscores critical barriers to trustworthy cybersecurity, notably algorithmic bias, workforce underrepresentation, and the neglect of intersectional gender perspectives. Current cybersecurity research predominantly emphasizes algorithmic performance, often overlooking broader societal impacts such as equity and inclusivity. This paper addresses this gap by synthesizing interdisciplinary lessons from emerging technology deployments, critically examining risks inherent in AI-driven 6G security, and articulating the urgent need for an “Equity by Design” approach. We introduce a comprehensive roadmap to embed intersectional equity into cybersecurity processes—from policy-making and technical development to real-world deployment. Utilizing the BEiNG-WISE COST Action as a best-practice case study, we demonstrate how explicit gender-inclusive and participatory methodologies can effectively operationalize equity, transparency, and diversity. Our findings illustrate that integrating social and technical dimensions is essential for building secure, resilient, and equitable digital futures.