Secure provenance using an authenticated data structure approach

Data provenance is information used in reasoning about the present state of a data object, providing details such as the inputs used, transformations it underwent, entities responsible, and any other information that had an impact on its evolution. With a plethora of uses consisting of but not limited to provision of trust, gauging of quality, detecting intrusion and system changes, solving attribution problems, regulations compliance and in legal proceedings etc., provenance information needs to be secured. On the other hand use of tampered provenance information could lead to erroneous judgments and serious implications in many situations. The difference in sensitivity levels of provenance and the underlying data coupled with its DAG (Directed Acyclic Graph) structure leads to the need for a tailored security model. To date, proposed secure provenance schemes such as the Onion scheme, PKLC scheme, Mutual agreement scheme, rely on transitive trust; consecutive participating entities do not collude to attack the provenance chain. Furthermore, these schemes suffer from attacks such as ownership and lone attacks on provenance records. We propose a secure provenance scheme that uses the auditor as a witness to the chain build process whereby a verification tree is incrementally built by the auditor which serves as his view of the chain. Our scheme removes the transitive trust dependency hence collusion attacks by consecutive participating entities are successfully detected. Additionally, our scheme captures the DAG structure of provenance information and achieves secure provenance requirements; integrity, availability and confidentiality. Security analysis and empirical results show that the scheme provides better security guarantees than the previously proposed schemes with reasonable overheads involved that can be outweighed by the protection capabilities provided and removal of transitive trust which may not be feasible.