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We study the problem of privately emulating shared memory in message-passingnetworks. The system includes clients that store and retrieve replicatedinformation on N servers, out of which e are malicious. When a client access amalicious server, the data field of that server response might be differentthan the value it originally stored. However, all other control variables inthe server reply and protocol actions are according to the server algorithm.For the coded atomic storage (CAS) algorithms by Cadambe et al., we present anenhancement that ensures no information leakage and malicious fault-tolerance.  We also consider recovery after the occurrence of transient faults thatviolate the assumptions according to which the system is to behave. After theirlast occurrence, transient faults leave the system in an arbitrary state (whilethe program code stays intact). We present a self-stabilizing algorithm, whichrecovers after the occurrence of transient faults. This addition to Cadambe etal. considers asynchronous settings as long as no transient faults occur. Therecovery from transient faults that bring the system counters (close) to theirmaximal values may include the use of a global reset procedure, which requiresthe system run to be controlled by a fair scheduler. After the recovery period,the safety properties are provided for asynchronous system runs that are notnecessarily controlled by fair schedulers.  Since the recovery period is bounded and the occurrence of transient faultsis extremely rare, we call this design criteria self-stabilization in thepresence of seldom fairness. Our self-stabilizing algorithm uses a boundedstorage during asynchronous executions (that are not necessarily fair). To thebest of our knowledge, we are the first to address privacy andself-stabilization in the context of emulating atomic shared memory innetworked systems.

Self-Stabilizing and Private Distributed Shared Atomic Memory in Seldomly Fair Message Passing Networks