#aiforensics

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Bias in Forensic Evidence Evaluation #researchawards #fosawards #sciencefather

This topic explores how bias influences the evaluation of forensic evidence, from traditional expert analysis to modern AI-based decision systems. It examines human cognitive biases, algorithmic bias in forensic technologies, and strategies for ensuring objectivity, transparency, and fairness in digital and physical evidence interpretation.

Nomination Link: https://forensicscientist.org/award-nomination/?ecategory=Awards&rcategory=Awardee

Website: https://forensicscientist.org/

Forensic Detection vs Anti-Forensics in GAN Images #researchawards #sciencefather #fosawards

This study explores the intricate balance between forensic detection methods and anti-forensic strategies in GAN-generated images. It examines how synthetic shadows and image artifacts influence authenticity assessments, highlighting advancements in digital forensics, AI image analysis, and counter-forensic techniques that challenge detection accuracy.

Nomination Link: https://forensicscientist.org/award-nomination/?ecategory=Awards&rcategory=Awardee

Website: https://forensicscientist.org/

AI-Driven Mobile Forensics Datasets via LLM Storyboards #researchawards #fosawards #sciencefather

"Explore how AI and Large Language Models (LLMs) can revolutionize mobile forensics by generating rich, realistic datasets using storyboard-driven techniques. This approach accelerates analysis, testing, and training of forensic tools with synthetic yet contextually accurate data."

Nomination Link: https://forensicscientist.org/award-nomination/?ecategory=Awards&rcategory=Awardee

Website: https://forensicscientist.org/

AI-Enhanced Zero-Knowledge Proofs for Privacy in Cloud Forensics #researchawards #fosawards

This research explores the integration of artificial intelligence with zero-knowledge proofs to enable privacy-preserving digital forensics in cloud environments. By leveraging AI-driven analysis while maintaining data confidentiality, the framework ensures secure evidence collection, verification, and investigation without exposing sensitive information, enhancing trust and compliance in cloud-based forensic operations.

Nomination Link: https://forensicscientist.org/award-nomination/?ecategory=Awards&rcategory=Awardee

Website: https://forensicscientist.org/

A Systematic Literature Review of Deepfakes in Forensic Science #researchawards #sciencefather

This systematic literature review explores the emerging role of deepfakes in forensic science, focusing on their implications for criminal investigations, digital evidence authentication, and legal proceedings. By analyzing scholarly research, the study highlights both the opportunities and challenges posed by synthetic media technologies. It examines forensic detection methods, ethical considerations, and the need for advanced AI-driven tools to safeguard justice systems from misinformation and fabricated evidence. The review also identifies research gaps and provides future directions for strengthening forensic capabilities in the digital era.

Nomination Link: https://forensicscientist.org/award-nomination/?ecategory=Awards&rcategory=Awardee

Website: https://forensicscientist.org/

This case study explores the forensic analysis of leading conversational AI models—ChatGPT, Gemini, Copilot, and Claude. It examines their response behavior, data handling, ethical considerations, and potential forensic applications. The study highlights how these AIs process queries, maintain contextual accuracy, and manage privacy, offering insights into their role in digital investigations and AI accountability.

Nomination Link: https://forensicscientist.org/award-nomination/?ecategory=Awards&rcategory=Awardee

Website: forensicscientist.org