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Recently Edge Computing paradigm has gained significant popularity both inindustry and academia. With its increased usage in real-life scenarios,security, privacy and integrity of data in such environments have becomecritical. Malicious deletion of mission-critical data due to ransomware,trojans and viruses has been a huge menace and recovering such lost data is anactive field of research. As most of Edge computing devices have compute andstorage limitations, difficult constraints arise in providing an optimal schemefor data protection. These devices mostly use Linux/Unix based operatingsystems. Hence, this work focuses on extending the Ext4 file system to APEX(Adaptive Ext4): a file system based on novel on-the-fly learning model thatprovides an Adaptive Recover-ability Aware file allocation platform forefficient post-deletion data recovery and therefore maintaining data integrity.Our recovery model and its lightweight implementation allow significantimprovement in recover-ability of lost data with lower compute, space, time,and cost overheads compared to other methods. We demonstrate the effectivenessof APEX through a case study of overwriting surveillance videos by CryPymalware on Raspberry-Pi based Edge deployment and show 678% and 32% higherrecovery than Ext4 and current state-of-the-art File Systems. We also evaluatethe overhead characteristics and experimentally show that they are lower thanother related works.

APEX: Adaptive Ext4 File System for Enhanced Data Recoverability in Edge Devices