Intelligent control and security of fog resources in healthcare systems via a cognitive fog model

There have been significant advances in the field of Internet of Things (IoT) recently, which have not always considered security or data security concerns: A high degree of security is required when considering the sharing of medical data over networks. In most IoT-based systems, especially those within smart-homes and smart-cities, there is a bridging point (fog computing) between a sensor network and the Internet which often just performs basic functions such as translating between the protocols used in the Internet and sensor networks, as well as small amounts of data processing. The fog nodes can have useful knowledge and potential for constructive security and control over both the sensor network and the data transmitted over the Internet. Smart healthcare services utilise such networks of IoT systems. It is therefore vital that medical data emanating from IoT systems is highly secure, to prevent fraudulent use, whilst maintaining quality of service providing assured, verified and complete data. In this paper, we examine the development of a Cognitive Fog (CF) model, for secure, smart healthcare services, that is able to make decisions such as opting-in and opting-out from running processes and invoking new processes when required, and providing security for the operational processes within the fog system. Overall, the proposed ensemble security model performed better in terms of Accuracy Rate, Detection Rate, and a lower False Positive Rate (standard intrusion detection measurements) than three base classifiers (K-NN, DBSCAN and DT) using a standard security dataset (NSL-KDD)

The anti-tumor efficacy of nanoparticulate form of ICD-85 versus free form

Biodegradable polymeric nanoparticles (NPs) have been intensively studied as a possible way to enhance anti-tumor efficacy while reducing side effects. ICD-85, derived from the venom of two separate species of venomous animals, has been shown to exhibit anti-cancer activity. In this report polymer based sodium alginate nanoparticles of ICD-85 was used to enhance its therapeutic effects and reduce its side effects. The inhibitory effect was evaluated by MTT assay. The necrotic effect was assessed using LDH assay. The induction of apoptosis was analyzed by caspase-8 colorimetric assay kit. Cytotoxicity assay in HeLa cells demonstrated enhanced efficacy of ICD-85 loaded NPs compared to the free ICD-85. The IC50 values obtained in HeLa cells after 48 h, for free ICD-85 and ICD-85 loaded NPs were 26±2.9μg ml-1 and 18±2.5μg ml-1, respectively. While it was observed that free ICD-85 exhibits mild cytotoxicity towards normal MRC-5 cells (IC50>60μg ml-1), ICD-85 loaded NPs was found to have higher efficacy in anti-proliferative activity on HeLa cells in vitro without any significant cytotoxic effect on normal MRC-5 cells. The apoptosis-induction mechanism by both form of ICD-85 on HeLa cells was found to be through activation of caspase-8 with approximately 2 fold greater of ICD-85 loaded NPs as compared to free ICD-85. Our work reveals that although ICD-85 in free form is relatively selective to inhibit the growth of cancer cells via apoptosis as compared to normal cells, but nanoparticulate form increases its selectivity towards cancer cells