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The gathering of surveillance data such as visual intelligence from potentially hostile areas has long played a pivotal role in attaining various safety and security objectives. The methodology of gathering such surveillance is increasingly shifting towards rapid-deployment autonomous networks that limit the need for human exposure, and that cover large unattended areas while operating over extended periods of time. To achieve the surveillance objectives, such networks must be dependable and secure even in the presence of a potentially hostile counter-surveillance opponent. In this work we explicitly model and consider the presence of such an opponent in the form of a hostile sensor network with eavesdropping and actuation capabilities. We present a methodology for addressing the security and dependability issues arising in such extreme settings, which we collectively refer to as G-E-M. Specifically, we wish to ensure the legitimacy and authenticity of the gathered (G-E-M) visual surveillance in the presence of a hostile network engaged in stealthy disinformation activities. We also wish to ensure that the collected surveillance can be encrypted (G-E-M) for transmission even if keys between the nodes and the sink are temporarily compromised or otherwise unavailable. Finally we wish to ensure that the network design both inherently prolongs the lifetime of the network and also mitigates (G-E-M) deliberate energy drains. These issues are not typically examined collectively though the dependability of all these components is required to maintain the functionality and longevity of the network. Though developed and presented for the case of an attacker in the form of a hostile network, the methodologies have applicability to networks with a subset of subverted nodes that behave maliciously.