Ransomware is a special type of malicious software that encrypts the user's assets and makes it unavailable to the users until a ransom is paid to the ransomware author. Such attacks have become one of the most widespread malware that poses serious threat to both individuals and business organizations. Against this destructive malicious program, the dynamic analysis approach is the most popular approach

Videos are expected to be a primary contributor to an anticipated massive surge in mobile network data. Caching the videos within the mobile network can significantly reduce the network load and Operational Expenditure (OPEX) for mobile network operators. Multi-access Edge Computing (MEC) can enable the video caching by providing processing and storage capabilities within the network. However, content

A Hybrid cloud is an integration of resources between private and public clouds. It enables users to horizontally scale their on-premises infrastructure up to public clouds in order to improve performance and cut up-front investment cost. This model of applications deployment is called cloud bursting that allows data-intensive applications especially distributed database systems to have the benefit

Mobile devices furnish users with various services while on the move, but also raise public concerns about trajectory privacy. Unfortunately, traditional privacy protection methods, such as anonymity and generalization, are not secure because they cannot resist attackers with background knowledge. The emergence of differential privacy provides an effective solution to this problem. Still, the existing

Mobile cloud computing helps to overcome the challenges of mobile computing by allowing mobile devices to migrate computation-intensive and data-intensive tasks to high-performance and scalable computation resources. However, emerging data-intensive applications pose challenges for mobile cloud computing platforms because of high latency, cost and data location issues. To address the challenges of

Unstructured data (mostly text data) have become a vital part in the era of big data. Hence, it has become increasingly difficult to identify the internal relations among data and describing the access control object during the design of access control (especially fine-grained access control) policies. Furthermore, in recent years, security incidents have frequently occurred due to the leakage of secrets

In many applications, multiple parties would benefit from a precise learning model trained from the aggregated dataset. However, the trivial method that all the data is aggregated into one datacenter and processed centrally is not appropriate when data privacy is a significant concern. In this paper, we propose a new framework for secure multi-party learning and construct a concrete scheme by incorporating

Human activity recognition has gained importance in recent years due to its applications in various fields such as health, security and surveillance, entertainment, and intelligent environments. A significant amount of work has been done on human activity recognition and researchers have leveraged different approaches, such as wearable, object-tagged, and device-free, to recognize human activities

It is commonsense that the data should be encrypted by searchable encryption before being outsourced to the cloud for its confidentiality and availability. Most of existing studies focus on forward privacy, we initiate the study of forward unforgeability, which defines the time periods when files can be uploaded while the forward privacy defines the time periods when files can be queried. For example

Blockchain possesses potential for enabling secure data sharing of industrial big data generated by the Industrial Internet of Things (IIoT). However, the existing data-sharing schemes based on blockchain secure only the data exchange process between the data-sharing parties; they do not consider the efficiency of data sharing at all. In this study, we propose a data-sharing scheme based on blockchain

With the rapid growth in design and fabrication outsourcing in semiconductor industry, concerns have increased about insuring the trustworthiness of underlying hardware, commonly known as hardware Trojans. This paper presents a new low-cost and high-speed design for trust methodology (DfTr) to detect hardware Trojans, especially for resource-constraint IoT devices. To relieve the stealthy nature of

Compared with outdoor localization using Global Positioning System (GPS), indoor localization is more complex and difficult due to the shadowing, fading and reflecting of radio. Thus, pioneers struggled for accurate device-free indoor localization and many creative schemes were proposed. However, these schemes still have defects and deficiencies. Mode-based schemes usually extract features of radio

Dividing a larger area into smaller subregions is a well addressed problem in Precision Agriculture (PA) where the existing application specific solutions (laboratory based) require human intervention and result in static region demarcation schemes. However, the boundary of a subregion is subject to change with various soil and environmental parameters. On the other hand, Wireless Sensor Networks (WSNs)

The low power idle mode implemented by Energy Efficient Ethernet (EEE) allows network interfaces to save up to 90% of their nominal energy consumption when idling. There is an ample body of research that recommends the use of frame coalescing algorithms—that enter the low power mode as soon as there is no more traffic waiting to be sent, and delay the exit from this mode until there is an acceptable

Over the last years, big data has emerged as a new paradigm for the processing and analysis of massive volumes of data. Big data processing has been combined with service and cloud computing, leading to a new class of services called “Big Services”. In this new model, services can be seen as an abstract layer that hides the complexity of the processed big data. To meet users' complex and heterogeneous

Organized in associations, Cloud Computing Providers became able to negotiate the acquisition of resources from other providers at more attractive prices, while allowing the marketing of their own idle resources to the other members of the respective Inter-Cloud. However, Inter-Cloud associations are characterized as resource-sharing environments, which allow for the presence of malicious providers

Identity management solutions are generally designed to facilitate the management of digital identities and operations such as authentication, and have been widely used in real-world applications. In recent years, there have been attempts to introduce blockchain-based identity management solutions, which allow the user to take over control of his/her own identity (i.e. self-sovereign identity). In

The fifth generation (5G) wireless networks are on the way to be deployed around the world. The 5G technologies target to support diverse vertical applications by connecting heterogeneous devices and machines with drastic improvements in terms of high quality of service, increased network capacity and enhanced system throughput. However, 5G systems still remain a number of security challenges that

Unmanned Aerial Vehicles (UAVs) are an emerging technology with the potential to be used in industries and various sectors of human life to provide a wide range of applications and services. During the last decade, there has been a growing focus of research in the UAV's assistance paradigm as a fundamental concept resulting in the constant improvement between different kinds of ground networks and

To protect user privacy (e.g., IP address and sensitive data in a packet), many traffic protection methods, like traffic obfuscation and encryption technologies, are introduced. However, these methods have been used by attackers to transmit malicious traffic, posing a serious threat to network security. To enhance network traffic supervision, this paper proposes a new traffic classification model based

Link prediction methods anticipate the likelihood of a future connection between two nodes in a given network. The methods are essential in social networks to infer social interactions or to suggest possible friends to the users. Rapid social network growth trigger link prediction analysis to be more challenging especially with the significant advancement in complex social network modeling. Researchers

With the proliferation of smartphones and tablets, large amounts of data are generated at the edge of the network. Edge computing becomes a promising paradigm for the processing of large amounts of data due to its characteristics of low latency, high data throughput, and low traffic pressure. However, the increasing requirements of the novel terminal applications and services on timely content delivery

Aggregating multiple small packets into a large packet provides many advantages. For example, multiple small packets can share a single copy of common Ethernet/IP/UDP headers to reduce the percentage of network bandwidth spent on transmitting headers. In the past, packet aggregation and disaggregation were done by a server CPU or a switch CPU, resulting in low throughputs. In this paper, we design

Identifying the positions of mobile devices within indoor environments allows for the development of advanced context-based applications and general environmental awareness. Classic localization methods require GPS; an expensive, high power consuming and inaccurate solution for indoor scenarios. Relative positioning instead allows nodes to recognize location in relation to neighboring nodes without

A bibliometric analysis of the Journal of Network and Computer Applications (JNCA) for the 1997–2019 period is performed. This analysis uncovers the structural and hidden implications of this journal. JNCA is one of the most prestigious journals in the computer science and engineering research community. Clarivate Analytics Web of Science is used to extract the bibliometric data on which the analysis

Fog computing has emerged as a complementary solution to address the issues faced in cloud computing. While fog computing allows us to better handle time/delay-sensitive Internet of Everything (IoE) applications (e.g. smart grids and adversarial environment), there are a number of operational challenges. For example, the resource-constrained nature of fog-nodes and heterogeneity of IoE jobs complicate

In this paper, we consider deceptive friendly jammers in a half-duplex random wireless network against a group of adaptive eavesdroppers. The destinations, eavesdroppers and friendly jammers are distributed according to homogeneous Poisson point process (HPPP). To the best of our knowledge, we are the first to study such a system model. As we may combine hostile jamming and passive eavesdropping, the

This work contributes to a real-time, edge-centric inferential modeling and analytics methodology introducing the fundamental mechanisms for (i) predictive models update and (ii) diverse models selection in distributed computing. Our objective in edge-centric analytics is the time-optimized model caching and selective forwarding at the network edge adopting optimal stopping theory, where communication

With the major advances in location acquisition techniques, deployment of GPS enabled devices and increasing number of mobile users, substantial amount of location traces are generated from different geographical regions. It provides unprecedented opportunities to analyse and derive valuable insights of urban dynamics, specifically, time-dependent mobility patterns and region-specific travel demands

The cognitive radio enabled cooperative communication is envisioned to be a vital part of the 5G-based Internet of Things (IoT). Since IoT contains billions of resource constrained devices, spectrum utilization efficiency (SUE) becomes a significant problem in order to accommodate such a large number of devices within the scarce spectrum. Therefore, in this paper, SUE of cognitive radio networks (CRNs)

Software switches are pivotal in the Software-Defined Networking (SDN) paradigm, particularly in the early phases of development, deployment and testing. Currently, the most popular one is Open vSwitch (OVS), leveraged in many production-based environments. However, due to its kernel-based nature, OVS is typically complex to modify when additional features or adaptation is required. To this regard

Massive data is transferred in the Internet of Thing (IoT) every single second. Protecting the security of these data is a crucial task. Steganography is a collection of techniques for concealing the existence of information by embedding it within irrelevant carriers, which could protect security and privacy of the data. Distinct from the cryptography, steganography put emphasis on hiding the existence

The Internet of Things (IoT) provides tremendous smart devices that are always connected to and interacting with the Internet. However, the development of IoT also promotes the threat of network attacks due to the billions of IoT devices vulnerable to hackers. Link-flooding attack (LFA) is a new type of DDoS attack used to flood the crucial network links. In IoT environment, LFA can be more easily

In public security, video super-resolution has been an important technology for assisting users in effectively locating potential safety hazards. However, the video collected from video monitoring equipment is usually polluted by motion blur and noise, which results in low video quality after reconstruction. In this paper, we propose a super-resolution reconstruction model for motion-blurred video

Routing Protocol for low power and Lossy networks (RPL) is a standardized routing protocol for low power and lossy networks (LLNs) such as the Internet of Things (IoT). RPL was designed to be a simple (but efficient) and practical networking protocol to perform routing in IoT networks that consists of resource constrained devices. These tiny intercommunicating devices are currently in use in a large

In recent years, with the increase of human activities in cyberspace, intrusion events, such as network penetration, detection and attack, tend to be frequent and hidden. The traditional intrusion detection methods which prefer rules are not enough to deal with the increasingly complex network intrusion flow. However, the generalization ability of intrusion detection system based on classical machine

Nowadays, wireless communication techniques, such as WiFi, Bluetooth low energy (BLE), etc., have been pervasive in our daily lives, and not only provide convenient data transmission services, but also enable popular indoor positioning and navigation services. The placement of wireless infrastructures like WiFi access points (APs) and BLE beacons have significant influences on the performance of localization

With the rapid development and deployment of the Network Function Virtualization (NFV) technology, the number and types of Network Services (NSs) in virtualized environments keep increasing significantly. However, due to the dynamic network and service status, manually customizing an NS in an NFV environment is a professional, time-consuming and error-prone task, and there is an urgent need to develop

Synthetic aperture radar (SAR) image target recognition has consistently been a research hotspot in the field of radar image interpretation. Compared with traditional target recognition algorithms, SAR target recognition algorithms based on deep learning offer end-to-end feature learning, which can effectively improve the target recognition rate, making them an important method for radar target recognition

The cooperative motion of autonomous vehicles (AVs), which communicate through wireless local area networks (WLANs), has been implemented using various technologies, e.g., the Internet of things (IoT). However, there are several insecure disturbances that occur during the communication of intelligent entities. These disturbances can compromise the cooperative control of AVs. In this paper, we propose

The transformation of mobile networks towards fifth generation (5G) is considered an unprecedented revolution when compared to the previous generations, mainly because of the support required for three scenarios: ultra reliable and low latency; high throughput broadband; and massive machine type communication. In this context, the evolution from RAN to C-RAN is a significant contribution to advance

Software Defined Networking (SDN) decouples the control and data planes of a network, and employs a central controller to provide effective use of network resources and ease of service provision. Virtualization in SDN empowers the virtual SDN networks to share common physical network infrastructures, and, thus, make them capable for versatile service provisioning. In such setting, SDN hypervisor supports

As the spring up of Internet of Things (IoT), IoT devices are naturally advantageous to create botnets for Distributed Denial of Service (DDoS) attacks. To mitigate the effect of IoT-powered DDoS attacks, multiple bandwidth reservation approaches have been explored. Nonetheless, spreading capability and prompt defense are not fully considered in these approaches. In this paper, we propose STBA, a spatio-temporal

Deduplication technology is used extensively in applications such as cloud computing services to optimize their storage performance (e.g., cloud service providers store only one copy of identical data). However, due to the use of encryption (to ensure the confidentiality of data stored in the cloud), it can be challenging for cloud service providers to perform deduplication (e.g., due to the use of

Cognitive radio is emerging as a technology to alleviate spectrum shortage and to improve spectrum utilization. In database-driven cognitive radio networks (CRNs), secondary users (SUs) must provide their locations to the database to enable channel allocation, which results in severe privacy violation. As SUs are usually energy-constrained or fast-moving, how to provide efficient channel allocation

Log data records system state and runtime behaviors, and is usually used to diagnose system failures and detect anomalies. However, the accuracy of log-based anomaly detection algorithms will reduce dramatically in dynamic logs since the system more complex than ever before, a phenomenon known as concept drift. In this paper, we design a confidence-guide anomaly detection model that combines multiple

Blockchain is a new approach to create a distributed network which was first introduced in 2008. By the help of this disruptive technology a peer-to-peer network can be formed where nodes have to reach a consensus and form a chain from accepted blocks, while no central party or trusted controller is required. Among all the existing uses of this technology, decentralized storage systems are one of its

In contemporary era of technologies, blockchain has acquired tremendous attention from various domains. It has wide spectrum of applications ranging from finance to social services and has greatly influenced the emerging business world. Since, blockchain technology is getting embedded in the e-commerce services, the cryptocurrencies are gaining huge prevalence. Bitcoin and ethereum are few such crypto

Ubiquitous sensing, provided via wireless sensor networks technologies, disseminates across many domains of contemporary day living. This provides the ability to sense, process, analyze and infer environmental parameters from natural resources and delicate ecologies to urban environments. The explosion in the number of devices that are connected to the internet has led to the emergence of the Internet

We consider the problem of designing a Wireless Local Area Network according to a Green paradigm (GWLAN), i.e. minimizing the power consumption of the network by powering-on just a subset of access points and associating users with the powered-on access points. To protect the system against fluctuations in the data rate transmission between users and access points, which naturally affect the problem

Recent advance in wireless communication and electronics industry has allowed the development of a wide range of biosensors to be used for Wireless Body Area Networks (WBANs) and Internet of Medical Things (IoMTs) which are emerging technologies for health monitoring. IEEE 802.15.6 is the first international WBANs’ standard, developed by the IEEE Task Group-6 to fulfill WBANs requirements for wireless

The reliability of Internet of Things (IoT) connected devices is heavily dependent on the security model employed to protect user data and prevent devices from engaging in malicious activity. Existing approaches for detecting phishing, distributed denial of service (DDoS), and Botnet attacks often focus on either the device or the back-end. In this paper, we propose a cloud-based distributed deep learning

Recently Ying and Nayak proposed a multi-server supported lightweight authentication protocol for 5G networks and confirmed the security of their protocol against all prominent attacks. Nevertheless, this paper will show certain shortcomings in their protocol, like vulnerability against identity guessing, password guessing, and user impersonation attacks. Additionally, it lacks in rendering strong

As a new video coding technology, distributed compressive video sensing (DCVS) uses compressed sensing (CS) independent encoding and joint decoding. Since DCVS breaks through the constraint of traditional video coding, it is suitable for resource-constrained wireless multimedia sensor networks (WMSNs). However, two major issues related to DCVS in WMSNs need to be solved urgently: one is to balance

Over the last decade, IoT platforms have been developed into a global giant that grabs every aspect of our daily lives by advancing human life with its unaccountable smart services. Because of easy accessibility and fast-growing demand for smart devices and network, IoT is now facing more security challenges than ever before. There are existing security measures that can be applied to protect IoT.

Radio frequency identification (RFID) technology, which obtained significant development in the past several decades, is widely applied in numerous industrial applications. One of the typical applications is to detect the missing tags, which can perform real-time detection of missing objects while each object is attached with a low-cost RFID tag in a large-scale warehouse. However, there actually may

Network Function Virtualization (NFV) provides great flexibility in solving the problem of deploying service function chains (SFCs). The existing serial SFCs organize virtual network functions (VNFs) in a predefined order and execute the VNFs one by one, which can result in high SFC delay as the lengths of the SFCs increases. In order to address this problem, in this work, the SFC parallelization is

During the past decades, due to the advances of the cloud computing technology with tens of thousands of processing machines, the intra data-center network traffic has increased tremendously. In data-center networks, the typical communication patterns of cloud computing technologies such as map-reduce require short latency of the request and response messages to achieve high service quality. Thus,

Video on Demand services generate the largest amount of traffic in networks nowadays. Previous works have proposed integrating Content Delivery Networks (CDN) and Peer-to-Peer (P2P) networks to satisfy this demand. However, their analytical methods do not consider all the factors that affect the performance of these systems. Hence, we present a novel comprehensive framework, based on a fluid model