The emergence of mobile service composition meets the current needs for real-time eCommerce. However, the requirements for eCommerce, such as safety and timeliness, are becoming increasingly strict. Thus, the cloud-edge hybrid computing model has been introduced to accelerate information processing, especially in a mobile scenario. However, the mobile environment is characterized by limited resource

Recently, due to the increase in popularity of the Internet, the problem of digital data security over the Internet is increasing at a phenomenal rate. Watermarking is used for various notable applications to secure digital data from unauthorized individuals. To achieve this, in this article, we propose a joint encryption then-compression based watermarking technique for digital document security.

The vision for programmable matter is to create a material that can be reprogrammed to have different shapes and to change its physical properties on demand. They are autonomous systems composed of a huge number of independent connected elements called particles. The connections to one another form the overall shape of the system. These particles are capable of interacting with each other and take

Currently, the integration of the supply chain and blockchain is promising, as blockchain successfully eliminates the bullwhip effect in the supply chain. Generally, concurrent Practical Byzantine Fault Tolerance (PBFT) consensus method, named C-PBFT, is powerful to deal with the consensus inefficiencies, caused by the fast node expansion in the supply chain. However, due to the tremendous complicated

Consumer behavior plays a very important role in economics and targeted marketing. However, understanding economic consumer behavior is quite challenging, such as finding credible and reliable information on product profitability. Different from frequent pattern mining, utility-oriented mining integrates utility theory and data mining. Utility mining is a useful tool for understanding economic consumer

With the development of ICT technology, users are actively participated in content creation and sharing. Service providers have provided more diverse and extensive information services. With the recent evolution to a customized service, the demand for the use of personal information is increasing. However, it affects the efficiency and convenience of service provision, as social problems and security

In blockchain networks, reaching effective supervision while maintaining anonymity to the public has been an ongoing challenge. In existing solutions, certification authorities need to record all pairs of identities and pseudonyms, which is demanding and costly. This article proposed an account guarantee scheme to realize feasible supervision for existing anonymous blockchain networks with lower storage

Korean education-related evaluation agencies utilize a centralized system that directly manages learner data. This leaves the intellectual property of the organizations and the personal information of the students vulnerable to leakage should the central server be attacked. In this study, the researchers propose a multilateral personal portfolio authentication system that guarantees the reliability

Pervasive Social Networking (PSN) supports online and instant social activities with the support of heterogeneous networks. Since reciprocal activities among both familiar/unfamiliar strangers and acquaintances are quite common in PSN, it is essential to offer trust information to PSN users. Past work normally evaluates trust based on a centralized party, which is not feasible due to the dynamic changes

With the evolvement of the Internet of things (IoT), privacy and security have become the primary indicators for users to deploy IoT applications. In the gateway-based IoT architecture, gateways aggregate data collected by perception-layer devices and upload message packets to platforms, while platforms automatically push different categories of data to different applications. However, security in

IoT devices generate massive amounts of biomedical data with increased digitalization and development of the state-of-the-art automated clinical data collection systems. When combined with advanced machine learning algorithms, the big data could be useful to improve the health systems for decision-making, diagnosis, and treatment. Mental healthcare is also attracting attention, since most medical problems

The Internet of Things (IoT) is expected to improve the individuals’ quality of life. However, ensuring security and privacy in the IoT context is a non-trivial task due to the low capability of these connected devices. Generally, the IoT device management is based on a centralized entity that validates communication and connection rights. Therefore, this centralized entity can be considered as a single

Urban crime is an ongoing problem in metropolitan development and attracts general concern from the international community. As an effective means of defending urban safety, crime prediction plays a crucial role in patrol force allocation and public safety. However, urban crime data is a macro result of crime patterns overlapped by various irrelevant factors that cause inhomogeneous noises—local outliers

Next (or successive) point-of-interest (POI) recommendation, which aims to predict where users are likely to go next, has recently emerged as a new research focus of POI recommendation. Most of the previous studies on next POI recommendation attempted to incorporate the spatiotemporal information and sequential patterns of user check-ins into recommendation models to predict the target user's next

Blockchain is regarded as one of the most promising technologies to upgrade e-commerce. This article analyzes the challenges that current e-commerce is facing and introduces a new scenario of e-commerce enabled by blockchain. A framework is proposed for mining tasks in this scenario offloaded onto edge servers based on mobile edge computing. Then, the offloading issue is modeled as a multi-constrained

Blockchain has attracted an increasing amount of researches, and there are lots of refreshing implementations in different fields. Cryptocurrency as its representative implementation, suffers the economic loss due to phishing scams. In our work, accounts and transactions are treated as nodes and edges, thus detection of phishing accounts can be modeled as a node classification problem. Correspondingly

Blockchain technology, whose most successful application is Bitcoin, enables non-repudiation and non-tamperable online transactions without the participation of a trusted central party. As a global ledger, the blockchain achieves the consistency of replica stored on each node through a consensus mechanism. A well-designed consensus mechanism, on one hand, needs to be efficient to meet the high frequency

Modern software development is increasingly dependent on components, libraries, and frameworks coming from third-party vendors or open-source suppliers and made available through a number of platforms (or forges). This way of writing software puts an emphasis on reuse and on composition, commoditizing the services that modern applications require. On the other hand, bugs and vulnerabilities in a single

The advances of Internet technology has resulted in the rapid and pervasive development of e-commerce, which has not only changed the production and operation mode of many enterprises, but also affected the economic development mode of the whole society. This trend has incurred a strong need to store and process large amounts of sensitive data. The traditional data storage and search solutions cannot

With the increasing number of users in blockchain-based cryptocurrencies, the public has raised the demand for transaction throughput, and many protocols are designed to improve the throughput following the Nakamoto consensus. Although astonishing progress has been made in the on-chain throughput improvement, high throughput makes the blockchains suffer from the increasing blockchain size, hard forks

Feedback-based reputation systems are widely deployed in E-commerce systems. Evidence shows that earning a reputable label (for sellers of such systems) may take a substantial amount of time, and this implies a reduction of profit. We propose to enhance sellers’ reputation via price discounts. However, the challenges are as follows: (1) The demands from buyers depend on both the discount and reputation

Influence Maximization (IM) aims to maximize the number of people that become aware of a product by finding the “best” set of “seed” users to initiate the product advertisement. Unlike most prior arts on the static networks containing fixed number of users, we study the evolving IM in more realistic evolving networks with temporally growing topology. The task of evolving IM, however, is far more challenging

Recent advances in cryptographic approaches, such as Functional Encryption and Attribute-based Encryption and their variants, have shown significant promise for enabling public clouds to provide secure computation and storage services for users’ sensitive data. A crucial component of these approaches is a third-party authority (TPA) that must be trusted to set up public parameters, provide private

Mobile Edge Computing (MEC) is a promising network architecture that pushes network control and mobile computing to the network edge. Recent studies propose to deploy MEC applications in the Network Function Virtualization (NFV) environment. The mobile network service in NFV is deployed as a Service Function Chaining (SFC). In the dynamic and resource-limited mobile network, SFC placement aiming at

The advent of social networks and activity networks affords us an opportunity of utilizing explicit social information and activity information to improve the quality of recommendation in the presence of data sparsity. In this article, we present a social-influence-based collaborative filtering (SICF) framework over heterogeneous information networks with three unique features. First, we integrate

The combination of Internet of Things (IoT) and Edge Computing (EC) can assist in the delivery of novel applications that will facilitate end-users’ activities. Data collected by numerous devices present in the IoT infrastructure can be hosted into a set of EC nodes becoming the subject of processing tasks for the provision of analytics. Analytics are derived as the result of various queries defined

Trust in Secure Sockets Layer–based communications is traditionally provided by Certificate (or Certification) Authorities (CAs) in the form of signed certificates. Checking the validity of a certificate involves three steps: (i) checking its expiration date, (ii) verifying its signature, and (iii) ensuring that it is not revoked. Currently, such certificate revocation checks (i.e., step (iii) above)

Viral marketing campaigns are often negatively affected by overexposure. Overexposure occurs when users become less likely to favor a promoted product after receiving information about the product from too large a fraction of their friends. Yet, existing influence diffusion models do not take overexposure into account, effectively overestimating the number of users who favor the product and diffuse

Product reviews play an important role in guiding users’ purchase decision-making in e-commerce platforms. However, it is challenging for users to find helpful reviews that meet their preferences and experiences among an overwhelming amount of reviews. Some works have been done to recommend helpful reviews to users, either from personalized or non-personalized views. While some existing models recommend

Service migration is an often-used approach in cloud computing to minimize the access cost by moving the service close to most users. Although it is effective in a certain sense, the service migration in existing research still suffers from some deficiencies in its evolutionary abilities in scalability, sensitivity, and adaptability to effectively react to the dynamically changing environments. This

Product descriptions play an important role in the e-commerce ecosystem. Yet, on leading e-commerce websites product descriptions are often lacking or missing. In this work, we suggest to overcome these issues by generating product descriptions from user reviews. We identify the set of candidates using a supervised approach that extracts review sentences in their original form, diversifies them, and

Traditional venue and tour recommendation systems do not necessarily provide a diverse set of recommendations and leave little room for serendipity. In this article, we design MPG, a Mobile Personal Guide that recommends: (i) a set of diverse yet surprisingly interesting venues that are aligned to user preferences and (ii) a set of routes, constructed from the recommended venues. We also introduce

As online sources are becoming more prevalent in journalism and scientific literature, the ephemeral nature of the World Wide Web is becoming an increasingly serious issue for their verifiability, replicability, and reproducibility. The architecture of Webchain, a new system enabling source and reference verifiability on the Web, is combining distributed ledger technologies with secure timestamping

The increasing volume of network-connected devices comprising Internet of Things and the variety of heterogeneous network architectures across these devices pose significant challenges to effective deployment and routing. In this article, we consider the adoption of probabilistic data structures to develop a novel Bloom Filter-based dual-layer inter-domain routing scheme. Our designed scheme implements

No abstract available.

In recent years, the ubiquitous nature of Internet-of-Things (IoT) applications as well as the pervasive character of next-generation communication protocols, such as the 5G technology, have become widely evident. In this work, we identify the need for low-cost security in current and next-generation IoT networks and address this demand through the implementation, testing, and validation of an intrinsic

The improvement of coverage quality in the construction of multiple-barrier coverage is a critical problem in a wireless sensor network. In this article, we investigate the K-barrier coverage construction problem in passive bistatic radar sensor networks. In contrast to traditional bistatic radar networks, the transmitters in a passive bistatic radar network are predeployed and noncooperative. To construct

Internet of Things (IoT) has emerged as a huge paradigm shift by connecting a versatile and massive collection of smart objects to the Internet, coming to play an important role in our daily lives. Data produced by IoT devices can generate a number of computational tasks that cannot be executed locally on the IoT devices. The most common solution is offloading these tasks to external devices with higher

Introduced as an extension of the Cloud at the network edge for computing and storage purposes, the Fog is increasingly considered a key enabler for Internet-of-Things applications whose latency requirements are not compatible with a Cloud-only approach. Unlike Cloud platforms, which can elastically accommodate large numbers of requests, Fog deployments are usually dimensioned for an average traffic

The Mobile IoT domain has been significantly expanded with the proliferation of drones and unmanned robotic devices. In this new landscape, the communication between the resource-constrained device and the fixed infrastructure is similarly expanded to include new messages of varying importance, control, and monitoring. To efficiently and effectively control the exchange of such messages subject to

Industrial networks typically connect hundreds or thousands of sensors and actuators in industrial facilities, such as manufacturing plants, steel mills, and oil refineries. Although the typical industrial Internet of Things (IoT) applications operate at low data rates, they pose unique challenges because of their critical demands for reliable and real-time communication in harsh industrial environments

In recent years, a new trend of advanced applications with huge demands in terms of Quality of Service (QoS) is gaining ground. Even though Cloud computing provides mature management facilities with ubiquitous capabilities, novel requirements and workloads, foisted by new services, start to expose its weaknesses. In this context, a new Information and Communication Technologies (ICT) trend aims at

In the industrial Internet of Things domain, applications are moving from the Cloud into the Edge, closer to the devices producing and consuming data. This means that applications move from the scalable and homogeneous Cloud environment into a potentially constrained heterogeneous Edge network. Making Edge applications reliable enough to fulfill Industry 4.0 use cases remains an open research challenge

Wireless sensor-actuator network (WSAN) technology is gaining rapid adoption by industrial Internet of Things applications in recent years. A WSAN typically connects sensors, actuators, and controllers in industrial facilities, such as steel mills, oil refineries, chemical plants, and infrastructures implementing complex monitoring and control processes. IEEE 802.15.4–based WSANs operate at low power

In this work, we describe an urban Internet of Things (IoT) architecture, grounded in big data patterns and focused on the needs of cities and their key stakeholders. First, the architecture of the dedicated platform USE4IoT (Urban Service Environment for the Internet of Things), which gathers and processes urban big data and extends the Lambda architecture, is proposed. We describe how the platform

The revolutionary development of the Internet of Things has triggered a huge demand for Internet of Things devices. They are extensively applied to various fields of social activities, and concerning manufacturing, they are a key enabling concept for the Industry 4.0 ecosystem. Industrial Internet of Things (IIoT) devices share common vulnerabilities with standard IoT devices, which are increasingly

Multi-task learning has been widely applied to Alzheimer's Disease study due to its capability to simultaneously rating the disease severity (classification) and predicting corresponding clinical scores (regression). In this paper, we propose a novel technique of Adaptive Multi-task Dual-Structured Learning, named AMDSL, by mutually exploring the dual manifold structure for label and regression score

In the last decade, twin support vector machines (TWSVMs) classifiers have been achieved considerable emphasis on pattern classification tasks. However, the TWSVM formulation still suffers from the following two shortcomings: (i) TWSVM deals with the inverse matrix calculation in the Wolfe-dual problems which is intractable for large scale datasets with numerous features and samples. (ii) TWSVM minimizes

Large networks of IoT devices, each consisting of one or more sensors, are being increasingly deployed for comprehensive real-time monitoring of cyber-physical systems. Such networks form an essential component of the emerging edge computing paradigm and are expected to increase in complexity and size. The physical phenomenon sensed by different sensors (within the same or different IoT devices in

Internet-enabled devices operating in the physical world are increasingly integrated in modern distributed systems. We focus on systems where the dynamics of spatial distribution is crucial; in such cases, devices may need to carry out complex computations (e.g., analyses) to check satisfaction of spatial requirements. The requirements are partly global—as the overall system should achieve certain

Nature-inspired optimization is one of the most prevalent research domains with a confounding history that fascinates the research communities. Particle Swarm Optimization (PSO) is one of the well-known optimizer that belongs to the family of nature inspired algorithms. It often suffers from premature convergence leading to a local optimum. To address this, several methods were presented using different

As one of the essential applications of Health Information Technology (HIT), the eHealth system plays a significant role in enabling various internet medicine service scenes, most of which primarily rely on service recommendation or evaluation mechanism. To avoid privacy leakage, some privacy-preserving mechanisms must be adopted to protect raters' privacy and make evaluation trust reliable. To tackle

We propose a BBDS system model with its security requirements before we propose a concrete construction by combining $\Sigma$-protocol, Paillier and AES encryption schemes, and the ECDSA signature scheme. To demonstrate the utility of our proposed BBDS system, we present a security analysis and compare our system with other solutions. We implement the prototype in Remix to analyze the gas cost and

Automatically summarizing a group of short texts that mainly share one topic is a fundamental task in many applications, e.g., summarizing the main symptoms for a disease based on a group of medical texts that are usually short. Conventional unsupervised short text summarization techniques tend to find the most representative short text document. However they may cause privacy issues, e.g., personal

Parkinson's disease (PD) is a neurodegenerative disease that affects millions of people around the world and cannot be cured fundamentally. Automatic identification of early Parkinson's disease on feature data sets is one of the most challenging medical tasks today. Many features in these datasets are useless or suffering from problems like noise, which affect the learning process and increase the

Fake news is risky, since it has been created to manipulate readers’ opinions and beliefs. In this work, we compared the language of false news to the real one of real news from an emotional perspective, considering a set of false information types (propaganda, hoax, clickbait, and satire) from social media and online news article sources. Our experiments showed that false information has different

Sentiment analysis or opinion mining for subject information extraction from the text has become more and more dependent on natural language processing, especially for business and healthcare, since the online products and service reviews affect the consuming behaviors. Word embeddings that can map the words to low-dimensional vector representations have been widely used in natural language processing

Containers, as a lightweight application virtualization technology, have recently gained immense popularity in mainstream cluster management systems like Google Borg and Kubernetes. Prevalently adopted by these systems for task deployments of diverse workloads such as big data, web services, and IoT, they support agile application deployment, environmental consistency, OS distribution portability,

Ethereum, a blockchain, supports its own cryptocurrency named Ether and smart contracts. Although more than 8M smart contracts have been deployed on Ethereum, little is known about the characteristics of its users, smart contracts, and the relationships among them. We conduct the first systematic study on Ethereum by leveraging graph analysis to characterize three major activities on Ethereum, namely

The performance evaluation results showed that the optimal EEG electrode locations were F7, F8, FC5, and FC6, whereas the accuracy of learning and test data of user-intention recognition was found to be 94.2% and 92.3%, respectively, which suggests that the proposed system can be used to recognize user intention for specific behavior. The system proposed in the present study can allow continued rehabilitation