National University of Computer and Emerging Sciences

About: National University of Computer and Emerging Sciences is a education organization based out in Islamabad, Pakistan. It is known for research contribution in the topics: Computer science & The Internet. The organization has 1506 authors who have published 2438 publications receiving 26786 citations.

Intelligent Control and Security of Fog Resources in Healthcare Systems via a Cognitive Fog Model

Abstract: 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).

A cluster-based key agreement scheme using keyed hashing for Body Area Networks

Abstract: In recent years, Body Area Networks (BANs) have gained immense popularity in the domain of healthcare as well as monitoring of soldiers in the battlefield. Security of a BAN is inevitable as we secure the lives of soldiers and patients. In this paper, we propose a security framework using Keyed-Hashing Message Authentication Code (HMAC-MD5) to protect the personal information in a BAN. We assume a network in which nodes sense physiological variables such as electrocardiography (EKG), electroencephalography (EEG), pulse oximeter data, blood pressure and cardiac output. Heterogeneous wireless sensor network is considered which consists of a powerful High-end sensor (H-sensor) and several Low-end sensors (L-sensors). EKG is used for secure communication between nodes as it introduces plug and play capability in BANs. The process is made secure by applying HMAC-MD5 on EKG blocks. Key agreement is done by comparing HMAC of feature blocks between sensors resulting in a more secure network. The analysis is done by calculating the entropy of keys and checking the randomness of EKG data using NIST-randomness testing suite.

Contemporary cybercrime: A taxonomy of ransomware threats & mitigation techniques

Abstract: An ever-increasing number of Internet-enabled devices over the past decade have highlighted the requirement for robust cybersecurity primitives to effectively deal with contemporary forms of cybercrime. Among the recent cybercrime threat canvass, ransomware has come to limelight as a prominent form of crypto-virus, aiming to hamper everyday user device operation through unsolicited encryption of device data. The perpetrators on successfully encrypting user data, require a payment or ransom, often in the form of digital currencies to furnish a decryption key. Depending on the urgency and criticality of data restoration, both novice users as well as corporate organizations have been observed to pay significant compensations for reinstating normal operation, often without any post-payment assurances. The present paper seeks to review the history and recent evolution of ransomware attacks, providing a detailed taxonomic classification of the inherent attack vectors and currently available mitigation techniques. Furthermore, preventive recommendations are discussed to aid users and organizations in securing devices against ransomware threats. Finally, financial and long-term implications of making ransom payments, along with online resources made available by security and law-enforcement concerns are overviewed to increase end user awareness and equip them against this increasingly successful form of recent cybercrime.

State-of-the-Art Clustering Schemes in Mobile Ad Hoc Networks: Objectives, Challenges, and Future Directions

Abstract: Mobile ad hoc networks (MANETs) are self-organized networks without any fixed infrastructure. The topology changes are very frequent in MANETs due to nodes’ mobility. The topology maintenance creates an extra overhead, as the mobility information of a single node is shared with all nodes in the network. To address the topology maintenance overhead problem in MANETs, the researchers proposed different cluster-based algorithms to reduce the size of a routing table. The clusters are formed to locally adjust the topology changes within the cluster. If a node wants to communicate with a node outside the cluster, it only communicates with its cluster head (CH). The CH communicates with other CHs to transmit data toward the destination. To efficiently utilize the clustering mechanism in MANETs, stable and balanced clusters are required. To form good quality and optimized clusters, some metrics, such as relative mobility (node speed and direction), node degree, residual energy, communication workload, and neighbor’s behavior, are required. In this paper, we present a comprehensive survey of recent CAs in MANETs. We also present the objectives, goals, and contributions of recent research. Similarly, the findings, challenges, and future directions are stated. The validation of each proposed work is analyzed critically in terms of the mobility model, the simulation tool used during simulation, simulation metrics, and the performance metrics used in the validation process.

IRoSim: Industrial Robotics Simulation Design Planning and Optimization platform based on CAD and knowledgeware technologies

Abstract: This paper presents Industrial Robotics Simulation Design Planning and Optimization platform named IRoSim, which is based on SolidWorks Application Programming Interface (API) to offer an intuitive and convertible environment for designing and simulating robotized tasks. The core idea is to integrate features of mechanical CAD and robotics CAD into the same platform to facilitate the development process through the designed Graphical User Interface (GUI) which permits user friendly interaction. The platform includes various 3D models that are essential for developing any robotized task and offers possibility to integrate new models in simulation. Robotic manipulator library is one such example which contains several types of serial arms with different combinations of revolute and prismatic joints. The platform provides most important steps such as defining the task, CAD learning of the end-effector's trajectory, checking the manipulator's reachability to perform a task, simulating the motion and finally validating the manipulator's trajectory to avoid possible collisions. To demonstrate the efficiency of the proposed approach, two frequent and important tasks (spot welding and painting) using a 6-Degree Of Freedom (DOF) industrial robotic manipulator have been considered. The output of the proposed strategy provides collision-free trajectory of the manipulator's motion which can be directly mapped to a real site. Moreover, the approach permits addressing the problems related with the real implementation of robotized tasks.