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In wireless sensor networks, energy consumption is one of the main constraints that limit the effects of their applicabilities. Clustering provides a practical solution to improve energy efficiency. However, the loads of each cluster head are not balance. Thus, the energy cannot be consumed evenly in each cluster head. To overcome this problem, we propose a distributed load balancing clustering algorithm (DLBCA). Without relying on central nodes, the sensor nodes can separately determine their roles (cluster heads or cluster members) and the clustering structure. The determination of cluster heads is based on the residual energy of sensor nodes and the distance to other nodes. DLBCA defines three matrixes (DD, Flag and FlagDis), which are related to the clustering. Through the matrixes, DLBCA can assign balanced and appropriate member nodes for the CHs. Our experimental results show that the DLBCA has better load balancing, longer life cycle and higher energy efficiency compared with existing algorithms. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a growing paradigm that is revolutionary for information and communication technology (ICT) because it gathers numerous application domains by integrating several enabling technologies. Outlier detection is a field of tremendous importance, including in IoT. In previous works on outlier detection, the proposed methods mainly tackled the efficacy and the efficiency challenges. However, a growing interest in the interpretation of the detected anomalies has been noticed by the research community, and only a few works have contributed in this direction. Furthermore, characterizing anomalous events in IoT-related problems has not been conducted. Hence, in this paper, we introduce our modified Local Outlier Factor (LOF)–based outlier characterization approach and apply it to enhance the IoT security and reliability. Experiments on both synthetic and real-world datasets show the good performance of our solution. [ABSTRACT FROM AUTHOR]

In this paper, a blind dual watermarking scheme for color images is proposed by embedding an invisible robust watermark to protect copyright, as well as a fragile watermark is embedded for image authentication. For the purpose of copyright protection, the robust watermark is embedded into the blue channel of RGB color space based on DWT, HVS and SVD domains using a specialized PSO optimization to balance the trade-off between robustness and imperceptibility. In addition, the robust watermarking capacity in SVD is doubled by inserting two robust watermark bits into each selected blocks and the robust watermark can be extracted blindly. For the purpose of authentication, a fragile watermark is embedded into all channels of RGB color space using a new way to manipulate the diagonal singular values. The authenticity of a suspected image can be verified in the absence of original watermark and host images. The combination of robust and fragile watermarking in the proposed scheme provides a suitable mechanism to protect valuable and original color images. According to the experimental and comparative results, the proposed scheme provides superior outcomes with high robustness, imperceptibility, and capacity along with a good accuracy rate in locating the tampered area of an image. [ABSTRACT FROM AUTHOR]

This paper presents a new intelligent image watermarking scheme based on discrete wavelet transform (DWT) and singular values decomposition (SVD) using human visual system (HVS) and particle swarm optimization (PSO). The cover image is transformed by one-level (DWT) and subsequently the LL sub-band of (DWT) transformed image is chosen for embedding. To achieve the highest possible visual quality, the embedding regions are selected based on (HVS). After applying (SVD) on the selected regions, every two watermark bits are embedded indirectly into the U and V t components of SVD decomposition of the selected regions, instead of embedding one watermark bit into the U component and compensating on the V t component that results in twice capacity and reasonable imperceptibility. In addition, for increasing the robustness without losing the transparency, the scaling factors are chosen automatically by (PSO) based on the attacks test results and predefined conditions, instead of using fixed or manually set scaling factors for all different cover images. Experimental and comparative results demonstrated the stability and improved performance of the proposed scheme compared to its parents watermarking schemes. Moreover, the proposed scheme is free of false positive detection error. [ABSTRACT FROM AUTHOR]

These days, researchers have used many techniques in e-multimedia data for intellectual property protection. One of these important techniques is watermarking which is superior to Digital Signature because it does not rise overhead and it can prevent unauthorized users from misusing digital information. However, the number of attacks with aim of distorting watermark signal or disturbing watermarks detecting are exploding. Consequently, the watermark techniques have became more complicated, but still they are not fully robust against some geometric distortions. To overcome this issue and to be enough robust against the malicious attacks, and provide a high level of imperceptibility,the watermark schemes have discovered and developed the advantages by means of Singular-value decomposition. Therefore, in recent decades there has been a significant increasing in using of SVD domain in many new image watermarking schemes, which show high robustness and imperceptibility. This discussion of SVD in image watermarking schemes included: a concise overview on watermarking systems, a brief review on SVD properties in image processing and its weaknesses, the concept of SVD components, the main classification of different SVD based image-watermarking schemes; a brief summary of various secure SVD-based watermarking techniques and all major SVD coefficients modifying strategies are presented. In addition, potential issues and some existing solutions and guidelines are provided. Furthermore, the performance comparisons of the discussed techniques are presented in tabular format. This article contribution provides essential and potential information for the researchers to design, develop and implement efficient robust and hybrid SVD-based image watermarking systems. [ABSTRACT FROM AUTHOR]

Security is crucial in wireless sensor networks (WSNs) since a growing variety of applications require strict security. Cluster-based architecture has an enhancement in the system performance of WSNs. This article presents a trust enhancement scheme for cluster-based WSNs, where network time is divided into multiple rounds. Each round contains a setup phase and a steady-state phase. In the setup phase, clusters are formed and mutual trusted relationships between cluster nodes are established through two proposed authentication protocols called SET-μTESLA (Setup μTESLA) and SET-SCHNORR (Setup SCHNORR). SET-μTESLA uses the authenticated broadcast μTESLA scheme and reduces the iterations of hash function to improve the energy efficiency, while SET-SCHNORR applies a lightweight signature SCHNORR scheme. In the steady-state phase, collected environmental or physical data are transmitted through the proposed STEADY-μTESLA protocol (Steady-state μTESLA), which guarantees the data credibility. The analysis demonstrates that the security scheme does well in resisting such attacks as data confidentiality attacks, data integrity attacks and compromise node attacks. In addition, the results of calculations and simulations show that the proposed scheme performs better than the existing security protocols in terms of communication overhead and energy consumption. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSN) is a part of particular case of mobile wireless network, which is provided with distinctive feature. The routing protocol of traditional wireless network is difficult to directly apply to WSN. High speed of node triggers dynamic changes of the networks topology, which leads to frequent communications link failures of WSN. Link reliability issue of high dynamic network has aroused wide public concern. Therefore, route reliability aiming at expressway WSN is analyzed, the evolving graph theory is expanded, extended—evolving graph model (EEGM) is established, and EEGM is adopted to obtain dynamic information of WSN topology so as to obtain the information of reliable routing in advance. On this basis, reliable routing protocol (EGRAODV) based on evolving graph theory is proposed. The simulations reveal that routing protocol proposed has improved in packet transmission rate, end-to-end transmission delay, routing requests ratio and number of link failures aspects compared to other similar protocol. [ABSTRACT FROM AUTHOR]

By the widespread use of cloud storage service, users get a lot of conveniences such as low-price file remote storage and flexible file sharing. The research points in cloud computing include the verification of data integrity, the protection of data privacy and flexible data access. The integrity of data is ensured by a challenge-and-response protocol based on the signatures generated by group users. Many existing schemes use group signatures to make sure that the data stored in cloud is intact for the purpose of privacy and anonymity. However, group signatures do not consider user equality and the problem of frameability caused by group managers. Therefore, we propose a data sharing scheme PSFS to support user equality and traceability meanwhile based on our previous work HA-DGSP. PSFS has some secure properties such as correctness, traceability, homomorphic authentication and practical data sharing. The practical data sharing ensures that the data owner won’t loss the control of the file data during the sharing and the data owner will get effective incentive of data sharing. The effective incentive is realized by the technology of blockchain. The experimental results show that the communication overhead and computational overhead of PSFS is acceptable. [ABSTRACT FROM AUTHOR]

The advent of 'Big Data' and 'Deep Learning' offers both, a great challenge and a huge opportunity for personalised health-care. In machine learning-based biomedical data analysis, feature extraction is a key step for 'feeding' the subsequent classifiers. With increasing numbers of biomedical data, extracting features from these 'big' data is an intensive and time-consuming task. In this case study, we employ a Graphics Processing Unit (GPU) via Python to extract features from a large corpus of snore sound data. Those features can subsequently be imported into many well-known deep learning training frameworks without any format processing. The snore sound data were collected from several hospitals (20 subjects, with 770-990 MB per subject - in total 17.20 GB). Experimental results show that our GPU-based processing significantly speeds up the feature extraction phase, by up to seven times, as compared to the previous CPU system. [ABSTRACT FROM AUTHOR]

Seamless handover between the evolved universal terrestrial radio access network and other access networks is highly desirable to mobile equipments in the long term evolution (LTE) or LTE-Advanced (LTE-A) networks, but ensuring security and efficiency of this process is challenging. In this paper, we propose a novel privacy-preserving with non-frameability handover authentication protocol based on ( t, n) secret sharing to fit in with all of the mobility scenarios in the LTE/LTE-A networks, which is called Nframe. To the best of our knowledge, Nframe is the first to support protecting users' privacy with non-frameability in the handover process. Moreover, Nframe uses pairing-free identity based cryptographic method to secure handover process and to achieve high efficiency. The formal verification by the AVISPA tool shows that Nframe is secure against various malicious attacks and the simulation result indicates that it outperforms the existing schemes in terms of computation and communication cost. [ABSTRACT FROM AUTHOR]

Integrated WiMAX and WiFi networks is of great potential for the future due to the wider coverage of WiMAX and the high data transport capacity of WiFi. However, seamless and secure handover (HO) is one of the most challenging issues in the WiMAX and WiFi heterogeneous networks. In this paper, we present a fast and secure HO authentication scheme based on credential ticket for WiMAX and WiFi heterogeneous networks. In the proposed scheme, Mobile Station (MS) shows its corresponding credential ticket generated by the previously visited Base Station (BS)/Access Point (AP) to the target BS/AP whenever an HO occurs, and then the MS and target BS/AP can complete the mutual authentication and derive their shared session key without interacting with the Authentication, Authorization, and Accounting server, which significantly reduces the HO authentication delay. Moreover, our scheme fulfills the essential security requirements in HO authentication semantics and the formal verification by the AVISPA tool shows that the proposed scheme is secure against various malicious attacks. In addition, the theoretical analysis and simulation indicate that our scheme outperforms the existing HO authentication schemes in terms of communication and computation cost. [ABSTRACT FROM AUTHOR]

Snore related signals (SRS) have been demonstrated to carry important information about the obstruction site and degree in the upper airway of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) patients in recent years. To make this acoustic signal analysis method more accurate and robust, big SRS data processing is inevitable. As an emerging concept and technology, cloud computing has motivated numerous researchers and engineers to exploit applications both in academic and industry field, which could have an ability to implement a huge blue print in biomedical engineering. Considering the security and transferring requirement of biomedical data, we designed a system based on private cloud computing to process SRS. Then we set the comparable experiments of processing a 5-hour audio recording of an OSAHS patient by a personal computer, a server and a private cloud computing system to demonstrate the efficiency of the infrastructure we proposed. [ABSTRACT FROM AUTHOR]

This paper is concerned with the sampled-data state estimation problem for a class of delayed neural networks with Markovian jumping parameters. Unlike the classical state estimation problem, in our state estimation scheme, the sampled measurements are adopted to estimate the concerned neuron states. The neural network under consideration is assumed to have multiple modes that switch from one to another according to a given Markovian chain. By utilizing the input delay approach, the sampling period is converted into a time-varying yet bounded delay. Then a sufficient condition is given under which the resulting error dynamics of the neural networks is exponentially stable in the mean square. Based on that, a set of sampled-data estimators is designed in terms of the solution to a set of linear matrix inequalities (LMIs) which can be solved by using the available software. Finally, a numerical example is used to show the effectiveness of the estimation approach proposed in this paper. [ABSTRACT FROM AUTHOR]

IEEE 802.16m is now under consideration by the International Telecommunication Union (ITU) to become the International Mobile Telecommunications (IMT)-Advanced standard. However, handover authentication is a critical issue in this area. In this paper, we propose an efficient group-based handover authentication mechanism, named as GHAP, for correlated mobile stations (MSs) in IEEE 802.16m networks. In our scheme, the correlated MSs who have the similar Signal to Interference-plus-Noise Ratio and history handover information etc. are divided into the same handover group. When the first MS of the handover group members moves from the service base station (BS) to a target BS, the service BS transmits all the handover group members' security context to the target BS utilizing the security context transfer (SCT) method and then all these MSs in the same handover group can easily perform the handover authentication with the target BS. Different from the conventional SCT schemes, our scheme uses the MSs' security context as a symmetric key of Cipher-based message authentication code (CMAC) but not the key material of deriving new session key. Therefore, the proposed scheme can effectively resist the domino effect existing in the previous SCT schemes. Moreover, security analysis shows that the proposed scheme also meets the other security requirements in handover authentication semantics. Furthermore, performance analysis demonstrates that the proposed scheme is very efficient in reducing average handover latency. [ABSTRACT FROM AUTHOR]

In the age of big data, service recommendation has provided an effective manner to filter valuable information from massive data. Generally, by observing the past service invocation records (Boolean values) distributed across different cloud platforms, a recommender system can infer personalized preferences of a user and recommend him/her new services to gain more profits. However, the historical service invocation records are a kind of private information for users. Therefore, how to protect sensitive user data distributed across multiple cloud platforms is becoming a necessity for successful service recommendations. Additionally, the historical service invocation records often update with time, which call for an efficient and scalable service recommendation method. In view of these challenges, we introduce the multi-probe Simhash technique in information retrieval domain into the recommendation process and further put forward a privacy-preserving recommendation method based on historical service invocation records. At last, we design several experiments on the real-world service quality data in set WS-DREAM. Experimental results show the feasibility of the proposal in terms of producing accurate recommended results while protecting users' private information contained in historical service invocation records. [ABSTRACT FROM AUTHOR]