Biometric Security Through Visual Encryption for Fog Edge Computing

Fog and mobile edge computing have gained considerable attention from the research and development community. The problems related to security and privacy of biometric content are simpler to solve through edge computing resulting in improved security and privacy of biometric and other critically private information. Zero-watermarking has been proposed as a solution to help protect the ownership of multimedia content that is easy to copy and distribute. Visual cryptography is another approach to secure data that is to be shared through generating multiple shares. This paper is concerned with developing a biometric security solution for face images, using visual cryptography and zero-watermarking, that does not adversely impact the visual quality of the image. The original face image is not modified through the zero-watermarking and visual encryption procedures and this in turn does not adversely impact the recognition rate

Balanced Transmissions Based Trajectories of Mobile Sink in Homogeneous Wireless Sensor Networks

Mobile Sink (MS) based routing strategies have been widely investigated to prolong the lifetime of Wireless Sensor Networks (WSNs). In this paper, we propose two schemes for data gathering in WSNs: (i) MS moves on random paths in the network (RMS) and (ii) the trajectory of MS is defined (DMS). In both the schemes, the network field is logically divided into small squares. The center point of each partitioned area is the sojourn location of the MS. We present three linear programming based models: (i) to maximize network lifetime, (ii) to minimize path loss, and (iii) to minimize end to end delay. Moreover, a geometric model is proposed to avoid redundancy while collecting information from the network nodes. Simulation results show that our proposed schemes perform better than the selected existing schemes in terms of the selected performance metrics

Context-aware pending interest table management scheme for NDN-based VANETs

In terms of delivery effectiveness, Vehicular Adhoc NETworks (VANETs) applications have multiple, possibly conflicting, and disparate needs (e.g., latency, reliability, and delivery priorities). Named Data Networking (NDN) has attracted the attention of the research community for effective content retrieval and dissemination in mobile environments such as VANETs. A vehicle in a VANET application is heavily reliant on information about the content, network, and application, which can be obtained from a variety of sources. The information gathered can be used as context to make better decisions. While it is difficult to obtain the necessary context information at the IP network layer, the emergence of NDN is changing the tide. The Pending Information Table (PIT) is an important player in NDN data retrieval. PIT size is the bottleneck due to the limited opportunities provided by current memory technologies. PIT overflow results in service disruptions as new Interest messages cannot be added to PIT. Adaptive, context-aware PIT entry management solutions must be introduced to NDN-based VANETs for effective content dissemination. In this context, our main contribution is a decentralised, context-aware PIT entry management (CPITEM) protocol. The simulation results show that the proposed CPITEM protocol achieves lower Interest Satisfaction Delay and effective PIT utilization based on context when compared to existing PIT entry replacement protocols

Inter-Communication Classification for Multi- View Face Recognition

Abstract: In this paper we present a new multi-view face recognition approach. Besides the recognition performance gain and the computation time reduction, our main objective is to deal with the variability of the face pose (multi-view) in the same class (identity). Several new methods were applied on face images to calculate our biometric templates. The Laplacian Smoothing Transform (LST) and Discriminant Analysis via Support Vectors (SVDA) have been used for the feature extraction and selection. For the classification, we have developed a new inter-communication technique using a model for the automatic pose estimation of the head in a face image. Experimental results conducted on UMIST database show that an average improvement for face recognition performance has been obtained in comparison with several multi-view face recognition techniques in the literature. Moreover, the system maintains a very acceptable running time and a high performance even in uncontrolled conditions

From Mobile to Wearable System: A Wearable RFID System to Enhance Teaching and Learning Conditions

Over the last decade, wearable technology has seen significant developments, making it possible to enhance our lives. One of the areas in which wearable technology can cause large changes is education, where it can be used to make educational experiences intrinsically motivating and more relevant to youth culture. In this paper, we focus on the use of wearable technology to improve the educational environment. The quantity of electronic assets used in the learning environment is rising, which presents a managerial problem when these devices are nonfunctioning. Therefore, we present a mobile application to solve this problem. The suggested approach consists of creating a mobile application named classroom clinic (CRC) to help faculty members and students locate the closest maintenance technician via wearable radio frequency identification (RFID) technology and to provide fast responses to the problems alerted to in the classroom, thereby avoiding any disturbances or delays during the lecture. Moreover, this application allows the maintenance service to efficiently manage any malfunctions of classroom electronic devices. To evaluate the CRC application, a pilot study was conducted at the College of Computer and Information Sciences, female campus of King Saud University, with 15 faculty members and students and 5 clinic members. The results showed high usability rates and generally positive attitudes towards using the app

Trace Attack against Biometric Mobile Applications

With the exponential increase in the dependence on mobile devices in everyday life, there is a growing concern related to privacy and security issues in the Gulf countries; therefore, it is imperative that security threats should be analyzed in detail. Mobile devices store enormous amounts of personal and financial information, unfortunately without any security. In order to secure mobile devices against different threats, biometrics has been applied and shown to be effective. However, biometric mobile applications are also vulnerable to several types of attacks that can decrease their security. Biometric information itself is considered sensitive data; for example, fingerprints can leave traces in touched objects and facial images can be captured everywhere or accessed by the attacker if the facial image is stored in the mobile device (lost or stolen). Hence, an attacker can easily forge the identity of a legitimate user and access data on a device. In this paper, the effects of a trace attack on the sensitivity of biometric mobile applications are investigated in terms of security and user privacy. Experimental results carried out on facial and fingerprint mobile authentication applications using different databases have shown that these mobile applications are vulnerable to the proposed attack, which poses a serious threat to the overall system security and user privacy