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The proposed work on the automatic multispectral retinal blood vessel analysis for detecting eye diseases uses the Discrete Wavelet Transform and Local Binary Patterns for feature extraction procedure. The sub-bands of the Discrete Wavelet Transform provide the horizontal, vertical and diagonal details of the image under analysis at different frequency levels. The resulting horizontal, vertical and diagonal sub-bands are then given to the Local Binary Patterns module that generates the local features of the directional wavelet sub-bands. The classification in healthy and glaucomatous images is done using Support Vector Machines. The obtained results show better performance than state of the art algorithms found in the literature for the High-Resolution Fundus image database. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper the problem of face recognition under variable illumination conditions is considered. Most of the works in the literature exhibit good performance under strictly controlled acquisition conditions, but the performance drastically drop when changes in pose and illumination occur, so that recently number of approaches have been proposed to deal with such variability. The aim of this work is to introduce an efficient local appearance feature extraction method based steerable pyramid (SP) for face recognition. Local information is extracted from SP sub-bands using LBP(Local binary Pattern). The underlying statistics allow us to reduce the required amount of data to be stored. The experiments carried out on different face databases confirm the effectiveness of the proposed approach. Keywords--Face recognition (FR), Steerable pyramid (SP), local Binary Pattern (LBP)., I. Introduction IN the last two decades, several studies have proposed to deploy multi-resolution feature extraction algorithms in face recognition. Among multi-resolution algorithms, the most popular are Discrete Wavelet transform [...]

Biometric authentication systems raise certain concerns with regard to security, violation of privacy, and storage issues of biometric templates. This paper proposes a protection approach of biometric templates storage in a multimodal biometric system while ensuring both the cancelability of biometric templates and the efficiency of the authentication process. We propose applying a chaotic maps-based transform on the biometric features to address the cancelability issue. We used Logistic map and Torus Automorphism to generate cancelable biometric features of the face and fingerprint minutia points, respectively. Both transformed features would be concatenated and saved in the database of the system instead of the original features. In the authentication stage, the similarity scores of both transformed face and fingerprint templates are computed and fused using the weighted sum rule. The results of the experimentation, conducted using images from the ORL face and FVC2002 DB1 fingerprint databases, demonstrated the higher performance of the proposed approach achieving a genuine accept rate equal to 100 % . Moreover, the obtained results confirmed the soundness of the proposed cancelable technique to satisfy the biometric systems' requirements (i.e., security, revocability, and diversity). [ABSTRACT FROM AUTHOR]

Image authentication is an important field that employs many different approaches and has several significant applications. In the proposed approach, we used a combination of two techniques to achieve authentication. Image watermarking is one of the techniques that has been used in many studies but the authentication field still needs to be studied. Blockchain technology is a relatively new technology that has significant research potential related to image authentication. The watermark is embedded into the third-level discrete wavelet transform (DWT) in the middle frequency regions to achieve security and imperceptibility goals. Peak signal-to-noise ratio PSNR, structural similarity matrix (SSIM), normalized correlation coefficient (NCC), and bit error rate (BER) are used to measure the performance of image watermarking. We used blockchain technology to avoid involving a trusted third party for authentication. Secure Hash Algorithm 256 (SHA-256) is applied on the watermark to save it into the blockchain. The watermark is encrypted using Advanced Encryption Standard (AES) and embedded into the image. The proposed method is tested on the USP SICI database and the MedPix medical image database. Ethereum blockchain is used to provide security, anonymity, and integrity of data with no third-party intervention. The proposed solution demonstrates enhanced security for image authentication compared with the state-of-the-art. [ABSTRACT FROM AUTHOR]

In the last decade, mobile devices become a storage place for highly sensitive information such as authentication credentials, bank account information, etc. However, smartphones are more likely to be lost or stolen than desktops or even laptops, putting user data at a high risk of being compromised. Malware and legitimate vulnerable applications can also be a threat to data disclosure. Therefore, this work focuses on preserving the confidentiality of the information stored in mobile devices from unauthorized access and specifically in the Android platform using a fuzzy vault-based key binding algorithm. The proposed approach aims to conceal the cryptographic key with the user's fingerprint such that only the genuine user will be authorized to access the secret key. [ABSTRACT FROM AUTHOR]

Biometric template disclosure starts gaining an important concern in deploying practical biometric authentication systems, where an assailant compromises the database for illegitimate access. To protect biometric templates from disclosure attacks, biometric authentication systems should meet these four requirements: security, diversity, revocability, and performance. Different methods have been suggested in the literature such as feature transformation techniques and biometric cryptosystems. However, no single method could satisfy the four requirements, giving rise to the deployment of hybrid mechanisms. In this context, the current paper proposes a hybrid system for multimodal biometric template protection to provide robustness against template database attacks. Herein, a secure sketch method is first applied to secure the fingerprint modality. Subsequently, a Dual-Tree Complex Wavelet Transform Discrete Cosine Transform (DTCWT-DCT) based watermarking is employed to entrench the fingerprint sketch into the face image. However, a 3D chaotic-map-based encryption method is employed to protect the watermarked facial image in order to offer an added security level. The experimentation performed using the ORL face database and three Fingerprint Verification Competition (FVC) fingerprint databases showed the approach's efficiency in withstanding standard digital image watermarking attacks, brute force attacks, and information leakage. Moreover, the results revealed that the approach achieves high performance, and satisfies diversity and revocability requirements. [ABSTRACT FROM AUTHOR]

The broad adoption of smartphones has superseded the desktop computers and laptops as a primary computing platform, due to mobility, constant connectivity and application diversity. Mobile devices encompass storage of extensive information including sensitive ones such as authentication credentials, pictures, videos, personal data, work information, and many more. Thus, securing data stored on mobile devices becomes a critical issue. In this review, we investigate the security of Android storage model between 2013 and 2018. Several threats are found in the literature that can be categorized as physical or software threats. Additionally, the existing solutions for each category are highlighted. Although Android provides valuable encryption systems including full disk encryption and keychain to enhance the data storage security, the encryption key, which is stored in the device, is still vulnerable to physical threats. [ABSTRACT FROM AUTHOR]

There are a number of issues related to the development of biometric authentication systems, such as privacy breach, consequential security and biometric template storage. Thus, the current paper aims to address these issues through the hybrid approach of watermarking with biometric encryption. A multimodal biometric template protection approach with fusion at score level using fingerprint and face templates is proposed. The proposed approach includes two basic stages, enrollment stage and verification stage. During the enrollment stage, discrete wavelet transform (DWT) is applied on the face images to embed the fingerprint features into different directional sub-bands. Watermark embedding and extraction are done by quantizing the mean values of the wavelet coefficients. Subsequently, the inverse DWT is applied to obtain the watermarked image. Following this, a unique token is assigned for each genuine user and a hyper-chaotic map is used to produce a key stream in order to encrypt a watermarked image using block-cipher. The experimentation results indicate the efficiency of the proposed approach in term of achieving a reasonable error rate of 3.87%. [ABSTRACT FROM AUTHOR]

In health sector, trust is considered important because it indirectly influences the quality of health care through patient satisfaction, adherence and the continuity of its relationship with health care professionals and the promotion of accurate and timely diagnoses. One of the important requirements of TRSs in the health sector is rating secrecy, which mandates that the identification information about the service consumer should be kept secret to prevent any privacy violation. Anonymity and trust are two imperative objectives, and no significant explicit efforts have been made to achieve both of them at the same time. In this paper, we present a framework for solving the problem of reconciling trust with anonymity in the health sector. Our solution comprises Anonymous Reputation Management (ARM) protocol and Context-aware Trustworthiness Assessment (CTA) protocol. ARM protocol ensures that only those service consumers who received a service from a specific service provider provide a recommendation score anonymously with in the specified time limit. The CTA protocol computes the reputation of a user as a service provider and as a recommender. To determine the correctness of the proposed ARM protocol, formal modelling and verification are performed using High Level Petri Nets (HLPN) and Z3 Solver. Our simulation results verify the accuracy of the proposed context-aware trust assessment scheme. [ABSTRACT FROM AUTHOR]

Demand Response (DR) programs under the umbrella of Demand Side Management (DSM) tend to involve end users in optimizing their Power Consumption (PC) patterns and offer financial incentives to shift the load at "low-priced" hours. However, users have their own preferences of anticipating the amount of consumed electricity. While installing an Energy Management System (EMS), the user must be assured that this investment gives optimum comfort of bill savings, as well as appliance utility considering Time of Use (ToU). Moreover, there is a difference between desired load distribution and optimally-scheduled load across a 24-h time frame for lowering electricity bills. This difference in load usage timings, if it is beyond the tolerance level of a user, increases frustration. The comfort level is a highly variable phenomenon. An EMS giving optimum comfort to one user may not be able to provide the same level of satisfaction to another who has different preferences regarding electricity bill savings or appliance utility. Under such a diversity of human behaviors, it is difficult to select an EMS for an individual user. In this work, a numeric performance metric,"User Comfort Level (UCL)" is formulated on the basis of user preferences on cost saving, tolerance in delay regarding use of an appliance and return of investment. The proposed framework (UCL) allows the user to select an EMS optimally that suits his.her preferences well by anticipating electricity bill reduction, tolerable delay in ToU of the appliance and return on investment. Furthermore, an extended literature analysis is conducted demonstrating generic strategies of EMSs. Five major building blocks are discussed and a comparative analysis is presented on the basis of the proposed performance metric. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper, a novel routing strategy to cater the energy consumption and delay sensitivity issues in deep underwater wireless sensor networks is proposed. This strategy is named as ESDR: Event Segregation based Delay sensitive Routing. In this strategy sensed events are segregated on the basis of their criticality and, are forwarded to their respective destinations based on forwarding functions. These functions depend on different routing metrics like: Signal Quality Index, Localization free Signal to Noise Ratio, Energy Cost Function and Depth Dependent Function. The problem of incomparable values of previously defined forwarding functions causes uneven delays in forwarding process. Hence forwarding functions are redefined to ensure their comparable values in different depth regions. Packet forwarding strategy is based on the event segregation approach which forwards one third of the generated events (delay sensitive) to surface sinks and two third events (normal events) are forwarded to mobile sinks. Motion of mobile sinks is influenced by the relative distribution of normal nodes. We have also incorporated two different mobility patterns named as; adaptive mobility and uniform mobility for mobile sinks. The later one is implemented for collecting the packets generated by the normal nodes. These improvements ensure optimum holding time, uniform delay and in-time reporting of delay sensitive events. This scheme is compared with the existing ones and outperforms the existing schemes in terms of network lifetime, delay and throughput. [ABSTRACT FROM AUTHOR]

Biometric recognition has been proven to offer a reliable solution to authenticate the identity of the legitimate user. Because of the inherent nature of biometrics, which involves the practice of digitally scanning the physiological or behavioral characteristics of individuals as a means of identification, the biometric trait employed is associated permanently with an individual and cannot be modified. This paper proposes a multimodal biometric template protection algorithm for the security of stored biometric templates in a database. The proposed algorithm is based on watermarking, shuffling process, Hadamard matrix and chaotic map. The security of the algorithm depends on the secrecy of the keys and the chaotic map. Watermarking based on Discrete Wavelet Transform-Singular Value Decomposition has been applied to fuse the features of face and fingerprint in order to improve the security of biometric data. To satisfy the requirements of a biometric template protection algorithm, each genuine user is assigned a unique key for the shuffling process and a unique code is generated using Hadamard matrix. Hadamard matrix is used to provide orthogonality and chaotic map for randomization. The identification process is carried out using Hamming distance. The experimental results give a good performance in terms of achieving a minimum value of FRR and FAR in comparison with previous studies. [ABSTRACT FROM AUTHOR]

Biometric systems are developed in order to replace traditional authentication. However, protecting the stored templates is considered as one of the critical steps in designing a secure biometric system. When biometric data is compromised, unlike passwords, it can't be revoked. One methodology for biometric template protection is 'Biometric Cryptosystem'. Biometric cryptosystems benefit from both fields of cryptography and biometrics where the biometrics exclude the need to remember passwords and the cryptography provides high security levels for data. In order to, develop these systems, Fuzzy Commitment Scheme (FCS) is considered as well known approach proposed in the literature to protect the user's data and has been used in several applications. However, these biometric cryptosystems are hampered by the lack of formal security analysis to prove their security strength and effectiveness. Hence, in this paper we present several metrics to analyze the security and evaluate the weaknesses of biometric cryptosystems based on FCS. [ABSTRACT FROM AUTHOR]

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 intrinsicallymotivating 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. [ABSTRACT FROM AUTHOR]

With the exponential increase in the dependence onmobile devices in everyday life, there is a growing concern related to privacy and security issues in theGulf 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 biometricmobile 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. [ABSTRACT FROM AUTHOR]

Personal authentication systems based on biometrics have given rise to new problems and challenges related to the protection of personal data, issues of less concern in traditional authentication systems. The irrevocability of biometric templates makes biometric systems very vulnerable to several attacks. In this paper we present a new approach for biometric template protection. Our objective is to build a non-invertible transformation, based on random projection, which meets the requirements of revocability, diversity, security and performance. In this context, we use the chaotic behavior of logistic map to build the projection vectors using a methodology that makes the construction of the projection matrix depend on the biometric template and its identity. The proposed approach has been evaluated and compared with Biohashing and BioPhasor using a rigorous security analysis. Our extensive experimental results using several databases (e.g., face, finger-knuckle and iris), show that the proposed technique has the ability to preserve and increase the performance of protected systems. Moreover, it is demonstrated that the security of the proposed approach is sufficiently robust to possible attacks keeping an acceptable balance between discrimination, diversity and non-invertibility. [ABSTRACT FROM AUTHOR]

The IPv4 addressing scheme, which was proposed by IETF in 1981, provides 4.3 billion unique 32-bit IP addresses but has been fully exhausted in Feb, 2011. This exhaustion of unique IP addresses poses significant challenges to the addition of new devices to the Internet as well as offering new services. Internet of Things, which provides interconnected uniquely identifiable devices in the existing Internet infrastructure, will be greatly affected by the lack of unique IP addresses. In order to connect to the existing Internet infrastructure, every new device needs a uniquely identified IP address for communication. It has been estimated that by the year 2020 more than 30 billion devices would be connected to the Internet. In order to meet the challenge of such vast requirement of unique IP addresses, the devices in IoT will have to adopt IPv6, which is the latest version of Internet Protocol. IPv6 uses 128-bit IP addresses and offers 2128 unique IP addresses. Therefore, it expands IPv4 and provides new features of end to end connections as well as new services. In this paper, the various challenges with respect to providing connectivity, security, mobility, etc., have been discussed and how IPv6 helps in meeting those challenges. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this article, to monitor the fields with square and circular geometries, three energy-efficient routing protocols are proposed for underwater wireless sensor networks. First one is sparsity-aware energy-efficient clustering, second one is circular sparsity-aware energy-efficient clustering, and the third one is circular depth–based sparsity-aware energy-efficient clustering routing protocol. All three protocols are proposed to minimize the energy consumption of sparse regions, whereas sparsity search algorithm is proposed to find sparse regions and density search algorithm is used to find dense regions of the network field. Moreover, clustering is performed in dense regions to minimize redundant transmissions of a data packet, while sink mobility is exploited to collect data from sensor nodes with an objective of minimum energy consumption. A depth threshold ( d th ) value is also used to minimize number of hops between source and destination for less energy consumption. Simulation results show that our schemes perform better than their counter-part schemes (depth-based routing and energy-efficient depth-based routing) in terms of energy efficiency. [ABSTRACT FROM AUTHOR]

Highlights: [•] A new approach for fingerprint template protection is proposed. [•] A new representation is used instead of the traditional minutiae-based representation. [•] Requirements of revocability, diversity, security and performance are achieved. [•] The approach is sufficiently robust to the zero effort and brute force attacks. [Copyright &y& Elsevier]