<![CDATA[The integration of information systems and big data in the public sector creates opportunities to improve government service quality, operational efficiency, and data-driven decision-making. However, rapid technological adoption generates increasingly complex challenges related to data ethics and citizen information security, particularly amid the growth of generative artificial intelligence and hybrid cloud computing. This study aims to identify, analyze, and map the ethical and data security challenges faced by public institutions in adopting integrated big data ecosystems. The study employed a systematic literature review (SLR) with a qualitative descriptive approach, examining 58 relevant scientific publications published between 2020 and 2025. The literature was analyzed using thematic synthesis through systematic coding, categorization, and grouping of recurring findings into major themes. The findings identify five major challenges: (1) privacy violations arising from mass data collection and citizen profiling without explicit consent; (2) increased cybersecurity risks within integrated information infrastructures; (3) algorithmic bias and unfairness in AI-based automated decision-making; (4) gaps in the implementation of personal data protection regulations at the regional level; and (5) weak cross-institutional data governance. Unlike previous reviews that tend to examine data ethics, cybersecurity, or digital transformation separately, this study develops an integrated framework linking ethical challenges, security risks, regulatory gaps, and governance weaknesses. This contribution provides a comprehensive foundation for future research and policy development. The study recommends strengthening data governance, implementing Privacy by Design and Security by Default, adopting AI ethics frameworks, and developing human resource capacity.]]>
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