Twenty-first-century human beings spend more than 90\% of their time in indoor environments. The emergence of cyber systems in the physical world has a plethora of benefits towards optimising resources and improving living standards. However, because of significant vulnerabilities in cyber systems, connected physical spaces are exposed to privacy risks in addition to existing and novel security challenges. To mitigate these risks and challenges, researchers opt for anomaly detection techniques. Particularly in smart home environments, the anomaly detection techniques are either focused on network traffic (cyber phenomena) or environmental (physical phenomena) sensors' data. This paper reviewed anomaly detection techniques presented for smart home environments using cyber data and physical data in the past. We categorise anomalies as known and unknown in smart homes. We also compare publicly available datasets for anomaly detection in smart home environments. In the end, we discuss essential key considerations and provide a decision-making framework towards supporting the implementation of anomaly detection systems for smart homes
