Superhydrophobicity is of interest for practical applications such as water repellency, self-cleaning, stain resistance, antibacterial properties, and oil−water separation. In this work, a superhydrophobic coating on cotton fabric is prepared by simple immersion in TiO 2 nanoparticles and perfluorodecyltriethoxysilane solution. Its antiwetting properties, surface morphology, and functionality are characterized. The cotton fabric shows superhydrophobicity with a water static contact angle of 169.3 ± 2.1°and tilt angle of 6.3 ± 2.0°. The coating is also characterized by performing stability tests, and it shows excellent mechanical durability, chemical stability, and thermal stability. Additionally, the water droplet dynamic on the coated surface is also studied. The coated cotton fabric exhibits excellent self-cleaning, stain resistance, rust stain resistance, anti-water absorption, and antibacterial properties. It can also be used in oil−water separation with a high separation efficiency and excellent reusability.
The widespread adoption of Internet of Things has led to many security issues. Post the Mirai-based DDoS attack in 2016 which compromised IoT devices, a host of new malware using Mirai's leaked source code and targeting IoT devices have cropped up, e.g. Satori, Reaper, Amnesia, Masuta etc. These malware exploit software vulnerabilities to infect IoT devices instead of open TELNET ports (like Mirai) making them more difficult to block using existing solutions such as firewalls. In this research, we present EDIMA, a distributed modular solution which can be used towards the detection of IoT malware network activity in large-scale networks (e.g. ISP, enterprise networks) during the scanning/infecting phase rather than during an attack. EDIMA employs machine learning algorithms for edge devices' traffic classification, a packet traffic feature vector database, a policy module and an optional packet sub-sampling module. We evaluate the classification performance of EDIMA through testbed experiments and present the results obtained.
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