  Despite society's strong dependence on electricity, power outages remain
prevalent. Standard methods for directly measuring power availability are
complex, often inaccurate, and are prone to attack. This paper explores an
alternative approach to identifying power outages through intelligent
monitoring of IP address availability. In finding these outages, we explore the
trade-off between the accuracy of detection and false alarms.
  We begin by experimentally demonstrating that static, residential Internet
connections serve as good indicators of power, as they are mostly active unless
power fails and rarely have battery backups. We construct metrics that
dynamically score the reliability of each residential IP, where a higher score
indicates a higher correlation between that IP's availability and its regional
power. We monitor specifically selected subsets of residential IPs and evaluate
the accuracy with which they can indicate current county power status.
  Using data gathered during the power outages caused by Hurricane Florence, we
demonstrate that we can track power outages at different granularities, state
and county, in both sparse and dense regions. By comparing our detection with
the reports gathered from power utility companies, we achieve an average
detection accuracy of $90\%$, where we also show some of our false alarms and
missed outage events could be due to imperfect ground truth data. Therefore,
our method can be used as a complementary technique of power outage detection.
