Internet of things (IoT) is playing a pivotal role in bringing comfort and ease in human lives by connecting billions of devices across the globe. Innovation and development in IoT have established new ways to analyze patient data in healthcare systems. Currently, IoT and cloud-based solutions are available to process and analyze patient data, but cloud computing causes large end-to-end delay and network usage problems while processing huge amounts of data. Efficiency and security are still a challenge in IoT-based healthcare systems. Fog computing is introduced to overcome the issues of cloud computing by providing computing and storage services at the edge of the network. In this article, first we present a fog based efficient architecture for IoT-based healthcare systems. Then we present the user authentication method through identity management to prevent security breaches. The fog based architecture for healthcare includes the idea of a virtual machine (VM) partitioning in fog node to smoothly run the body sensor network and medical IoT devices data. The Elliptic Curve Cryptography technique is used to generate the output token for the user authentication method.

A smart city is developed, deployed and maintained with the help of Internet of Things (IoT). The smart cities have become an emerging phenomena with rapid urban growth and boost in the field of information technology. However, the function and operation of a smart city is subject to the pivotal development of security architectures. The contribution made in this paper is twofold. Firstly, it aims to provide a detailed, categorized and comprehensive overview of the research on security problems and their existing solutions for smart cities. The categorization is based on several factors such as governance, socioeconomic and technological factors. This classification provides an easy and concise view of the security threats, vulnerabilities and available solutions for the respective technologies areas that are proposed over the period 2010-2015. Secondly, an IoT testbed for smart cities architecture, i.e., SmartSantander is also analyzed with respect to security threats and vulnerabilities to smart cities. The existing best practices regarding smart city security are discussed and analyzed with respect to their performance, which could be used by different stakeholders of the smart cities.

Glaucoma is an eye disease that can cause loss of vision by damaging the optic nerve. It is the world’s second leading cause of blindness after cataracts. Early diagnosis of glaucoma is a key to prevent permanent blindness as it has no noticeable symptoms in its early stages. Color fundus photography is used for examining the optic disc (OD) which is an important step in the diagnoses of glaucoma. This is done by estimating the cup-to-disc ratio (CDR). In this paper, we proposed a Cup Disc Encoder Decoder Network (CDED-Net) for the joint segmentation of optic disc (OD) and optic cup (OC). We have eradicated the pre-processing and post-processing steps to reduce the computational cost of the overall system. Segmentation of (OD) and OC is modeled as a semantic pixel-wise labeling problem. The model was trained on the DRISHTI-GS, RIM-ONE and REFUGE datasets. Experiments show that our CDED-Net system achieves state-of-the-art OD and OC segmentation results on these datasets.

Android has become the most popular smartphone operating system. This rapidly increasing adoption of Android has resulted in significant increase in the number of malwares when compared with previous years. There exist lots of antimalware programs which are designed to effectively protect the users’ sensitive data in mobile systems from such attacks. In this paper, our contribution is twofold. Firstly, we have analyzed the Android malwares and their penetration techniques used for attacking the systems and antivirus programs that act against malwares to protect Android systems. We categorize many of the most recent antimalware techniques on the basis of their detection methods. We aim to provide an easy and concise view of the malware detection and protection mechanisms and deduce their benefits and limitations. Secondly, we have forecast Android market trends for the year up to 2018 and provide a unique hybrid security solution and take into account both the static and dynamic analysis an android application.