In the dynamic realm of Smart Healthcare Systems (SHS), the integration of IoT devices has revolutionized conventional practices, ushering in an era of real-time data collection and seamless communication across the healthcare ecosystem. Amidst this technological shift, the paramount concern remains the security of sensitive healthcare data within intricate networks. Several cryptographic algorithms have been proposed for smart healthcare systems for the protection of critical and sensitive data in SHS, however, the majority of newly proposed algorithms have shortcomings in terms of resource utilization and the level of security that they provide. Our research delves into the existing highly secure cryptographic algorithms and provides a comparative analysis of two popular and secure cryptographic algorithms viz N-th Degree Truncated Polynomial Ring (NTRU) and Elliptic Curve Cryptography (ECC) and verifies their applicability in SHS. Recognizing ECC's compact key sizes and its vulnerability to quantum computing threats, our study finds NTRU as a resilient and quantum-resistant alternative, providing a robust defense mechanism in the evolving landscape of healthcare cybersecurity. Key findings underscore the efficacy of NTRU in safeguarding healthcare data, emphasizing its superior performance compared to ECC, especially in the face of emerging quantum computing challenges. The comparative analysis depicts that ECC excels in key generation speed, delivering efficient and swift key creation. However, it requires larger keys to withstand potential quantum computing vulnerabilities. On the other hand, the key generation time in NTRU is slightly more than ECC but being quantum-resistant, it provides high security.

The modern communication networks have evolved from simple-static systems to highly flexible and adaptive systems facilitating dynamic programmability and reconfiguration. This network evolution has influenced the lowest level of packet processing in data plane to highest level of network control and management functions. It has also influenced the overall network design and architecture which is clearly evident from the emergence of SDN and NFV. With the wide-spread acceptance of SDN, a novel networking paradigm, the network programmability has re-appeared as a top research area in networking and numerous programming languages have been proposed. In this paper, we present a systematic review of various state-of-the-art SDN programming languages used to program different network planes. We follow a top-down approach, starting with the high-level or top-tier programming languages followed by the data plane or bottom-tier programming languages. We have provided an in-depth analysis of various top-tier and bottom-tier programming languages and compared them in terms of most prominent features and supported abstractions. In addition to it, we have elaborated various programming models used in different bottom-tier programming languages which provide necessary abstractions for mapping diverse functionalities of data plane algorithms splendidly onto the specialized hardware like ASICs. Lastly, we have highlighted the research challenges in SDN programming languages like cross platform programming, necessary language libraries, support for network verification, NFV, stateful and inline packet processing, which need to be incorporated into existing programming languages to support diverse functions required in next generation networks.

As the information put together by the blend of smartphones, the cloud, the IOT, and ubiquitous computing continue to expand at an alarming rate, a data breach increases. Today, users' strong authentication and authorization approaches are increasingly important to secure sensitive, confidential, secret information. Possession and knowledge-based authentication techniques for computers, the internet, email accounts, etc., are commonly used to access vital information; they do not link a user to an established identity, resulting in most security vulnerabilities. Biometric authentication, on the other hand, has the privilege of being more reliable than traditional authentication as biometric characteristics of a person can’t be lost; they are tough to distribute, exchange or duplicate; and it requires the user to be present during the authentication process, thereby relating the users to established identities. Biometrics provides a higher level of assurance that the individual attempting to ascertain is the individual in question. Thus, resulting in a more reliable, usable, and cost-effective model with a higher level of protection to deter an attacker from obtaining entry to a computer or network and gaining access to confidential data. This paper introduces a novel fingerprint-based authentication scheme for mobile environments, enabling user authentication based on fingerprint features using a challenge-response-based authentication process. In this study, the proposed authentication system has been developed on a real Android-based smartphone, tested on actual users, and performance analysis has been carried out; empirical results reveal that the proposed authentication scheme achieves increased performance. Moreover, a usability analysis has been done to determine efficiency, effectiveness, and user satisfaction. The evaluation results indicate its feasibility to use it as an effective authentication mechanism for mobile phone environments.

The ever-increasing demands of Internet services like video on demand, big data applications, IoE and multi-tenant data centers have compelled the network industry to change its conventional non-evolving network architecture. Software Defined Network (SDN) has emerged as a promising network architecture which provides necessary abstractions and novel APIs to facilitate network innovations and simplifies network resource management by breaking the conventional network into multiple planes. All these SDN planes interact through open interfaces or APIs which are commonly categorized into southbound, northbound and west/eastbound interfaces. In this manuscript, we have identified and emphasized various communication protocols used at south and northbound interfaces. We have provided a taxonomy of south and northbound communication protocols based on their dependence, capabilities and properties. The pros and cons associated with each communication mechanism are highlighted and the numerous research challenges and open issues involved at these two interfaces are elucidated. In addition to it, we have proposed the necessary abstractions and extensions required in communication protocols at these two interfaces to simplify real-time monitoring and virtualization in next generation networks.

This paper presents two segmentation algorithms for MR spine image segmentation helping in on time diagnosis of the spine hernia and surgical intervention whenever required. One is level set segmentation and another one is watershed segmentation algorithm. Both of these methods have been widely used before (Aslan, Farag, Arnold and Xiang, 2011) (Pan, et al., 2013) (Silvia, España, Antonio, Estanislao , and David, 2015) (Erdil, Argun?ah, Ünay and Çetin, 2013) (Claudia. Et al, 2007). In our approach we have used the concept of variational level set method along with a signed distance function and is compared with the watershed segmentation which we have already implemented before on a different dataset (Hashia, Mir, 2014). In order to check the efficacy of the algorithm it is again implemented in this paper on the sagittal T2-weighted MR images of the spine. It can be seen that both these methods can become very much valuable to help the radiologists with the on time segmentation of the vertebral bodies as well as of the intervertebral disks with relatively much less effort. They both are later compared with the golden standard using dice and jaccard coefficients.

Wireless Sensor Nodes (SNs), the key elements for building Internet of Things (IOT) have been deployed widely in order to get and transmit information over the internet. IPv6 over low power personal area network (6LoWPAN) enabled their connectivity with IPV6 networks. 6LoWPAN has mobility and it can find an extensive application space only if provides mobility support efficiently. Existing mobility schemes are focused on reducing handoff (HO) latency and pay less attention towards packet loss and signaling cost. In time critical applications under IOT, packet loss and excessive signaling cost are not acceptable. This paper proposes a scheme based on advanced mobility prediction for reducing extra signaling cost and packet loss that incurs due to connection termination in traditional schemes such as Proxy Mobile IPv6 (PMIPv6) handover. In our proposed scheme 6LoWPAN WSN architecture with IPv6 addressing is presented. Based on this architecture the mobility algorithm is proposed for reducing signaling cost, packet loss by buffering mechanism and HO latency in particular. In the algorithm layer 2 (L2) and layer 3 (L3) HO is performed simultaneously with prior HO prediction with no Care of Address (CoA) configuration which also reduces signaling cost to some extent. The proposed scheme is analyzed theoretically and evaluated for different performance metrics. Data results showed significant improvements in reducing packet loss, signaling cost and HO latency when compared to standard PMIPv6 in time critical scenarios.