Table 3 Using Lambda architecture to address big data issues
From: An ensemble deep learning based IDS for IoT using Lambda architecture
Research work | Application area | Relevant to IoT | Weaknesses |
|---|---|---|---|
Ma (2020) | Smart home environments | \(\checkmark\) | Does not address security and network attacks. Focuses on data processing, management and storage |
Roopak et al. (2019) | Smart road environments | \(\checkmark\) | Does not address security and network attacks. Focuses on quality assessment using large-scale data |
Diro and Chilamkurti (2018) | Smart manufacturing environments | \(\checkmark\) | Does not address security and network attacks. Focuses on real-time visualization of sensors generated data |
Amanullah et al. (2020) | Security operations centre (SOC) | x | Does not employ simple or deep-ensemble based approaches. Not designed for IoT environments |
Patan and Babu (2018) | Cloud-based snort network IDS | x | Not designed for IoT environments |
Lopez et al. (2018) | Network threat detection | x | Not designed for IoT environments |
Kayode (2020) | Cloud-based security solution | x | Not designed for IoT environments |
Tangsatjatham and Nupairoj (2016) | Log anomaly detection technique | x | Not designed for IoT environments |