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Internet of Vehicles (IoV) enabled Intelligent Transportation System (ITS) allows smart vehicles to communicate with other vehicles on road, humans (customers or pedestrians), infrastructure (parking areas, traffic lights etc), Internet, Cloud etc. The vehicles communicate with other entities over wireless open channels directly or indirectly through messages or beacons. Open channel allows various attacks, like replay, man-in-the-middle, impersonation, fabrication etc., during communication. Also, malicious vehicles can be deployed in the network to misuse or have an unauthorized access to the services. To mitigate these issues, we propose a new remote access control scheme that ensures the secure communication among the vehicles. The vehicles are dynamic in nature in an IoV paradigm, that is, they are not under fixed domains. Therefore, whenever a vehicle changes its location it has to register to the nearest trusted authority () in offline or secured channel mode. To make it applicable, we propose remote registration of the vehicles via the. Access control mechanism occurs in two phases: 1) node authentication phase, where vehicles are remotely authenticated by and 2) key agreement phase, where after successful mutual authentication they compute a session key by using cryptographic techniques and pre-loaded information. The computed secret session keys are used for ensuring secure communications in future between two vehicles in a cluster as well. Informal security analysis along with formal security verification using the broadly-used Automated Validation of Internet Security Protocols and Applications (AVISPA) show that our access control scheme is secured against various potential attacks. We also show the competency of our scheme by comparing it with other existing schemes in terms of computation and communication costs. [ABSTRACT FROM AUTHOR]

Cyber threat hunting proactively searches for cyber threats, which are undetected by the traditional defense mechanisms. It scans deep to identify malicious programs (ie, malware) that escape from detection. It is important because sophisticated cyber threats can bypass the cyber security mechanisms. The performance of the cyber threat hunting can be improved through artificial intelligence (AI), especially, explainable AI (XAI), which adds trust component to the cyber threat hunting process. Due to the inclusion of XAI, the security experts get the full explanations of the detected threats as the working of the detection model in XAI is known. Information, like, which one is a threat, how it has been detected, and why it has been detected, can be obtained very easily due to the inclusion of XAI in the cyber threat hunting. Therefore, an XAI‐envisioned mechanism for cyber threat hunting has been proposed (in short, XAISM‐CTH). The network and threat models of XAISM‐CTH are designed and discussed. The conducted security analysis proves the security of XAISM‐CTH against various potential attacks. XAISM‐CTH also performs better than the other existing schemes. At the end, a practical implementation of XAISM‐CTH has been provided to observe its impact on the performance of the system. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) is one of the fastest-growing technologies. With the deployment of massive and faster mobile networks, almost every daily-use item is connected to the Internet. IoT-enabled industrial multimedia environment is used for the collection and analysis of different types of multimedia data (i.e., images, videos, audios, etc.). This multimedia data is generated by various types of smart devices like drones, robots, smart controller, smart surveillance system which are deployed for the industrial monitoring and control. The multimedia data is generated in the enormous amount which can be considered as the big data. This data is further utilized in various types of business needs for example, chances of fire accidents in the industrial plant, overall machine health, etc., which can be predicted through the application of big data analytics. Therefore, IoT-enabled industrial multimedia environment is very helpful to the concerned authorities as they come to know the important information in advance. However, all the smart devices are connected and controlled through the Internet. It further causes severe threats to the communication happens in an IoT-enabled industrial multimedia environment. It is vulnerable to various types of attacks such as replay, man-in-the-middle, impersonation, secret information leakage, sensitive information modification, and malware injection (i.e., mirai). Therefore, it is important to prevent the communication of such an environment against the different types of possible attacks. These days, the attacks performed by botnets (i.e., malware attacks such as mirai and reaper) have drawn attention to the researchers. Under the influence of such attacks, the communication of IoT-enabled industrial multimedia environment is disrupted. Moreover, the attackers may also control the smart devices remotely and can change their functionalities. Hence, we need some robust mechanism to detect the presence of the malware attacks in such an environment. In this paper, we propose a malware detection mechanism in IoT-enabled industrial multimedia environment with the help of machine-learning approach, which is named as MADP-IIME. MADP-IIME uses four different types of machine learning methods (i.e., naive bayes, logistic regression, artificial neural networks (ANN) and random forest) to detect the presence of malware attacks successfully. Furthermore, MADP-IIME performs better than other related existing schemes and achieves 99.5 % detection and 0.5 % false positive rate. In addition, the conducted security analysis proves the resilience of the proposed MADP-IIME against different types of malware attacks. [ABSTRACT FROM AUTHOR]

Vehicle-to-grid (V2G) technology enables bidirectional energy flow between the electric vehicle and power grid thereby making the electric vehicle as a virtual power plant. This seamless exchange of energy flow is possible only when the entities involved communicate wirelessly in a secured manner. In order to ensure privacy-preserving in the V2G communication, development of a novel key establishment protocol is an active area of research. This article presents a lightweight mutual authentication and key establishment protocol for secure V2G communication among the electric vehicle user, charging station, and utility service provider. The correctness of the proposed protocol is verified using the formal method BAN logic, and many of its security threats are analyzed informally. Further, the protocol is compared for its security and efficiency with the related protocols in the literature under various aspects, and the comparison results show that our protocol outshines the others. The functional correctness of the protocol is also verified in Xilinx Zynq-7000 series FPGA board so that it can be deployed in any real-time applications. [ABSTRACT FROM AUTHOR]

Summary: Internet of things environment is adopted widely in different industries and business organizations with varying capacity. It provides a favorable environment to outsource the crowdsourced data in the cloud to minimize the cost of computation, which is called crowdsourcing. Crowdsourcing is a technique where individuals or organizations obtain goods and services. A professional or industry outsource the crowdsourced data in the cloud, where confidentiality and authenticity of data become essential. Signcryption is the cryptographic technique that serves both the authenticity and the privacy of transmitted messages. This technique ensures secure authentic data transmission and storage. Therefore, this paper proposes an identity‐based signcryption scheme. In the proposed PSSCC framework, the user does pairing free computation during signcryption, which makes efficient calculation on user‐side. Moreover, PSSCC framework is proved secure under modified bilinear Diffie‐Hellman inversion and modified bilinear strong Diffie‐Hellman problems. The performance analysis of PSSCC with related schemes indicates that the proposed system supports efficient communication along with less computation cost. [ABSTRACT FROM AUTHOR]

The continuous growth to the 6G wireless communication technology overcomes storage, stringent computation, privacy and power constraints to make an efficient and intelligent next generation transportation system to alleviate traffic jams and enhance driving experience in vehicular ad-hoc networks (VANETs). In combination with 6G technology, high availability, high reliability and occasionally high throughput are enabled in VANETs. However, the information shared in the VANET system should be secured. In this paper, an efficient batch authentication and key exchange schemes are proposed to provide a high level security by evading communication with the malicious vehicle users. In addition, an anonymous batch authentication scheme is proposed to alleviate the authentication burden on the road side units (RSUs) while performing authentication in the congested areas. Moreover, the integrity of the communicating messages is preserved in this proposed scheme to evade message modification during transmission. Even though many cryptographic schemes were proposed for batch authentication in VANETS, they suffered from lack of privacy-preservation and computational overhead. The discussion of the possible attacks section illustrates that the proposed protocol can survive against potential security attacks. In the performance analysis section, the proposed batch authentication scheme is compared with well-known existing schemes and then it is clearly revealed that the proposed scheme is computationally more efficient than the existing schemes. [ABSTRACT FROM AUTHOR]

Cloud computing is a new category of service that gives each customer access to a large-scale computing network. Since most cloud computing platforms provide services to a large number of people who aren't considered to be trustworthy, various cyber attacks may potentially target them. As a result, a cloud computing system must provide a security monitoring mechanism to protect the Virtual Machine from attacks. In this case, there is a tradeoff between the security level of the security system and its performance. If we need strong security, we'll need more laws or patterns, which means we'll need a lot more computational resources in proportion to the strength of security. As a result of the declining number of resources allocated to customers, we will add a new protection scheme in cloud environments to the VM in this report. Hence, the proposed system Proposed Elliptic curve - Diffie Hellman EC(DH)2 Algorithm is designed and deployed to improve the security in healthcare domain using hybrid computing. The most popular and recent technologies such as cloud computing and fog computing are integrated to explore data movement and stable medical data health-care information. Based on the experimental results, it is inferred that the proposed system offers high security and less operating time while handling the data making its deployment in the healthcare domain. [ABSTRACT FROM AUTHOR]

Software‐defined networking (SDN) is a programmable architecture for networking domain in which the security is provided by devising the network policies with the help of the network administrator. This is very cumbersome for the administrator to handle different attacks at various planes in SDN architecture. Blockchain can be used to prevent various attacks in SDN by providing a decentralization authentication environment. In this article, a secure Blockchain‐based privacy‐preserving protocol is proposed to thwart various security vulnerabilities in the SDN architecture. The proposed approach uses Modified‐Delegated Proof of Stake as the consensus protocol to ensure safety and reliability in the network. Besides, a security protocol is designed using cryptographic primitives and analyzed using a detailed security analysis. Initially, the consensus protocols are implemented using solidity smart contracts and deployed to the public Blockchain using Ethereum. Consequently, the proposed approach is simulated on OMNet++ using INET framework. The experimental results show that the proposed SDN‐Chain is secure, efficient, less incentive to centralize, and practically implementable in resource‐limited wireless and mobile environments. [ABSTRACT FROM AUTHOR]

In this paper, an Internet of Energy (IoE) solution for providing optimal charging and control of resources in the era of electric vehicles (EVs) with energy trading and security is considered. A blockchain based security solution is presented by considering the IoE as a distributed energy system with internet of things (IoT). However, by inheriting the security concerns of IoTs, IoE also faces the security challenges and is considered here. Hierarchical key generation is used for cryptographic keys, based on lattice constructions. Along with a consensus tailored with Practical Byzantine Fault Tolerance (PBFT), an additional smart contract is also applied for utilization of energy transfer. The presented solution provides transparency, reliability, availability and failure recovery inheriting from the blockchain aspects. To the best of our knowledge, the present study is the first attempt in this direction of IoE-EV interface solutions. The experimental results, comparative analysis and security validation affirm the superiority of the proposed solution over the existing approaches. [ABSTRACT FROM AUTHOR]

The security and privacy of healthcare enterprises (HEs) are crucial because they maintain sensitive information. Because of the unique functional requirement of omni-inclusiveness, HEs are expected to monitor patients, allowing for connectivity with vehicular ad hoc networks (VANETs). In the absence of literature on security provisioning frameworks that connect VANETs and HEs, this paper presents a smart zero-knowledge proof and statistical fingerprinting-based trusted secure communication framework for a fog computing environment. A zero-knowledge proof is used for vehicle authentication, and statistical fingerprinting is employed to secure communication between VANETs and HEs. Authenticity verification of the operations is performed at the on-board unit (OBU) fitted in the vehicle based on the service executions at the resident hardware platform. The processor clock cycles are acquired from the service executions in a complete sandboxed environment. The calculated cycles assist in developing the blueprint signature for the particular OBU of the vehicle. Hence, the fingerprint signature helps build trust and plays a key role in authenticating the vehicle’s horizontal movement to everything or to different sections of the HEs. In an environment enabled for fog computing, our novel model can provide efficient remote monitoring. [ABSTRACT FROM AUTHOR]

The outbreak of coronavirus COVID-19 not only brings great disaster to the people of the world, but also brings heavy burden to the medical and health network system. Massive network data traffic and resource optimization requests make traditional network architectures unable to calmly deal with the impact of COVID-19. Artificial intelligence (AI) can effectively raise the upper limit of the medical and health network, as evidenced by the ever-increasing restorative clinical data. In addition, the development of next-generation network (NGN) technologies based on machine learning (ML) has created unlimited possibilities for the emergence of emerging medical methods. In order to reflect the effective results of the current application of AI technologies in the fight against the COVID-19 epidemic and provide a reliable guarantee for subsequent diagnosis and treatment of COVID-19 epidemics, a series of AI technologies which can be used in the diagnosis and treatment of COVID-19 are systematically summarized and analyzed. Based on various AI technologies and methods, we try to propose an AI-based medical network architecture. The architecture uses AI technologies to quickly and effectively realize the monitoring, diagnosis and treatment of patients. Finally, we rationally analyzed the technical challenges and practical problems that may be faced in implementing the architecture. The purpose of this article is to inspire scholars and medical researchers to carry out the latest research in response to the COVID-19 epidemic and make breakthrough medical technology progress. [ABSTRACT FROM AUTHOR]

Summary: Software‐defined networking (SDN) is an agile, modern networking approach that facilitates innovations in the networking paradigm. The abstracted and centralized network operating system facilitates the network management and reduces operational expenditure (OPEX). The open nature and simplicity of the data‐forwarding plane dramatically reduces capital expenditure (CAPEX) by leveraging commodity servers and switches. SDN also lends itself very well to address major cloud computing issues and complement cloud services, especially in terms of network virtualization and networking as a service (NaaS). As a new technology, SDN does involve certain security challenges, which include distributed denial of service (DDoS) threats, build and run time injected malware, insider (tenant) attacks, and security holes resulting from controller misconfigurations. These are severe threats that can cripple an entire network. It is crucial to address the SDN vulnerabilities to ensure its successful deployment in private data center networks, on cloud platforms and beyond. Some security solutions leverage the built‐in features of SDN, such as its controller software component, while other solutions provide external SDN applications running above the controller. This study reviews the security solutions for the vulnerabilities of state‐of‐the‐art SDN controllers and the available countermeasures. Furthermore, an in‐depth analysis of the SDN features that support security is presented, and some unresolved research issues on SDN controllers are identified. [ABSTRACT FROM AUTHOR]

The present world of vehicle technology is inclined to develop Electric Vehicles (EVs) with various optimized features. These vehicles need frequent charging which takes a longer time to charge up. Therefore, scheduling of vehicles in charging stations is required. Besides, the information of the EVs and its location is also stored by the charging stations and therefore creates a concern of EV privacy. Various researches are going on to solve these problems; however, an efficient privacy-preserving solution is less practiced till date. In this paper, a framework for Electric Vehicle (EV) charging is discussed. The framework uses the concept of Matching Market to identify a charging station and uses the lattice-based cryptography for secure communications. The matching market considers multiple factors to provide the best allocation of charging station and cryptography ensures security and privacy preservation. The use of lattice-based cryptographic hash SWIFFT avoids heavy computation. This usage of matching market and lattice cryptography, more specifically signcryption for EV charging framework are the highlights of the solution and add-ons to the novel features. Overall, the presented framework is efficient in terms of computation and communication cost, satisfaction ratio, slot ratio, charging latency and load balancing index. The performance metrics are compared with recent developments in this field. [ABSTRACT FROM AUTHOR]

In the Internet of Vehicles (IoV), secure information sharing among vehicles is crucial in order to upgrade driving safety as well as to strengthen vehicular services. However, public communication among vehicles leads to various potential attacks, such as replay, man-in-the-middle, impersonation, unlinkability and traceability attacks. To address this issue, we design a new conditional privacy preserving batch verification-based authentication mechanism in the IoV environment using Elliptic Curve Cryptography $(ECC)$ technique, where a vehicle can authenticate its neighbor vehicle and also a Road-Side Unit $(RSU)$ can authenticate its nearby vehicles in a batch. The proposed scheme is shown to be highly secure against a passive/active adversary through various security analysis, such as random oracle based formal security, formal security verification via automated simulation tool, and also informal security analysis. An exhaustive comparative analysis reveals that the proposed scheme offers better security and functionality attributes, and comparable storage, communication and computation overheads when these are compared with the relevant schemes. [ABSTRACT FROM AUTHOR]

A user (external party) is interested in accessing the real-time data from some designated drones of a particular fly zone in the Internet of Drones (IoD) deployment. However, to provide this facility, the user needs to be authenticated by an accessed remote drone and vice-versa. After successful authentication both parties can establish a secret session key for the secure communication. To handle this important problem in IoD environment, we design a novel temporal credential based anonymous lightweight user authentication mechanism for IoD environment, called TCALAS. A detailed security analysis using formal security under the broadly applied real-or-random (ROR) model, formal security verification under the broadly used software verification tool, known as automated validation of internet security protocols and applications, and also informal security analysis reveal that TCALAS has the capability to resist various known attacks against passive/active adversary. In addition, a detailed comparative study has been conducted for TCALAS and other related schemes, and the study also reveals that TCALAS provides better security and functionality features, and lower costs in both computation and communication as compared to existing schemes. [ABSTRACT FROM AUTHOR]

The continuous development and usage of multi-media-based applications and services have contributed to the exponential growth of social multimedia traffic. In this context, secure transmission of data plays a critical role in realizing all of the key requirements of social multimedia networks such as reliability, scalability, quality of information, and quality of service (QoS). Thus, a trust-based paradigm for multimedia analytics is highly desired to meet the increasing user requirements and deliver more timely and actionable insights. In this regard, software-defined networks (SDNs) play a vital role; however, several factors such as as-runtime security, and energy-aware networking limit its capabilities to facilitate efficient network control and management. Thus, with the view to enhance the reliability of the SDN, a hybrid deep-learning-based anomaly detection scheme for suspicious flow detection in the context of social multimedia is proposed. It consists of the following two modules: 1) an anomaly detection module that leverages improved restricted Boltzmann machine and gradient descent-based support vector machine to detect the abnormal activities, and 2) an end-to-end data delivery module to satisfy strict QoS requirements of the SDN, that is, high bandwidth and low latency. Finally, the proposed scheme has been experimentally evaluated on both real-time and benchmark datasets to prove its effectiveness and efficiency in terms of anomaly detection and data delivery essential for social multimedia. Further, a large-scale analysis over a Carnegie Mellon University (CMU)-based insider threat dataset has been conducted to identify its performance in terms of detecting malicious events such as-Identity theft, profile cloning, confidential data collection, etc. [ABSTRACT FROM AUTHOR]

Mobile cloud computing (MCC) allows mobile users to have on-demand access to cloud services. A mobile cloud model helps in analyzing the information regarding the patients’ records and also in extracting recommendations in healthcare applications. In MCC, a fine-grained level access control of multiserver cloud data is a prerequisite for successful execution of end-users applications. In this paper, we propose a new scheme that provides a combined approach of fine-grained access control over cloud-based multiserver data along with a provably secure mobile user authentication mechanism for the Healthcare Industry 4.0. To the best of our knowledge, the proposed scheme is the first to pursue fine-grained data access control over multiple cloud servers in a MCC environment. The proposed scheme has been validated extensively in different heterogeneous environment where its performance was found good in comparison to other existing schemes. [ABSTRACT FROM AUTHOR]

Summary: In wireless sensor networks (WSNs), there are many critical applications (for example, healthcare, vehicle tracking, and battlefield), where the online streaming data generated from different sensor nodes need to be analyzed with respect to quick control decisions. However, as the data generated by these sensor nodes usually flow through open channel, so there are higher chances of various types of attacks either on the nodes or on to the data captured by these nodes. In this paper, we aim to design a new elliptic curve cryptography–based user authenticated key agreement protocol in a hierarchical WSN so that a legal user can only access the streaming data from generated from different sensor nodes. The proposed scheme is based upon 3‐factor authentication, as it applies smart card, password, and personal biometrics of a user (for ticket generation). The proposed scheme maintains low computation cost for resource‐constrained sensor nodes, as it uses efficient 1‐way cryptographic hash function and bitwise exclusive‐OR operations for secure key establishment between different sensor nodes. The security analysis using the broadly accepted Burrows‐Abadi‐Needham logic, formal security verification using the popular simulation tool (automated validation of Internet security protocols and applications), and informal security show that the proposed scheme is resilient against several well‐known attacks needed for a user authentication scheme in WSNs. The comparison of security and functionality requirements, communication and computation costs of the proposed scheme, and other related existing user authentication schemes shows the superior performance of the proposed scheme. [ABSTRACT FROM AUTHOR]

Smart grid (SG) technology has recently received significant attention due to its usage in maintaining demand response management in power transmission systems. In SG, charging of electric vehicles becomes one of the emerging applications. However, authentication between a vehicle user and a smart meter is required so that both of them can securely communicate for managing demand response during peak hours. To address the above mentioned issues, in this paper, we propose a new efficient three-factor user authentication scheme for a renewable energy-based smart grid environment (TUAS-RESG), which uses the lightweight cryptographic computations such as one-way hash functions, bitwise XOR operations, and elliptic curve cryptography. The detailed security analysis shows the robustness of TUAS-RESG against various well-known attacks. Moreover, TUAS-RESG provides superior security with additional features, such as dynamic smart meter addition, flexibility for password and biometric update, user and smart meter anonymity, and untraceability as compared to other related existing schemes. The practical demonstration of TUAS-RESG is also proved using the widely accepted NS2 simulation. [ABSTRACT FROM PUBLISHER]

Nowadays, the study of underwater WSNs (UWSNs) has become a hot topic. However, UWSNs have not been fully utilized in the complex underwater environment, since there are some difficulties in controlling mobile sensor nodes and underwater environment conditions. In addition, how to ensure the security of UWSNs and the safety of underwater mobile sensor nodes has not been solved well. In this article, we study the problem of trust establishment between nodes in UWSNs. We first give a detailed overview of existing trust management mechanisms. Since UWSNs possess specific characteristics, it is noted that those existing mechanisms are not applicable for UWSNs. We then introduce a trust cloud model that is suitable for trust management in UWSNs. [ABSTRACT FROM PUBLISHER]

Fog computing as an extension to the cloud computing infrastructure has been invaluable in enhancing the applicability of the Internet of Things (IoT) paradigm. IoT based Fog systems magnify the range and minimize the latency of IoT applications. However, as fog nodes are considered transient and they offer authenticated services, when an IoT end device loses connectivity with a fog node, it must authenticate freshly with a secondary fog node. In this work, we present a new security mechanism to leverage the initial authentication to perform fast lightweight secondary authentication to ensure smooth failover among fog nodes. The proposed scheme is secure in the presence of a current de-facto Canetti and Krawczyk (CK)-adversary. We demonstrate the security of the proposed scheme with a detailed security analysis using formal security under the broadly recognized Real-Or-Random (ROR) model, informal security analysis as well as through formal security verification using the broadly-used Automated Validation of Internet Security Protocols and Applications (AVISPA) software tool. A testbed experiment for measuring computational time for different cryptographic primitives using the Multiprecision Integer and Rational Arithmetic Cryptographic Library (MIRACL) has been done. Finally, through comparative analysis with other related schemes, we show how the presented approach is uniquely advantageous over other schemes. [ABSTRACT FROM AUTHOR]

The General Data Protection Regulation (GDPR) harmonizes personal data protection laws across the European Union, affecting all sectors including the healthcare industry. For processing operations that pose a high risk for data subjects, a Data Protection Impact Assessment (DPIA) is mandatory from May 2018. Taking into account the criticality of the process and the importance of its results, for the protection of the patients' health data, as well as the complexity involved and the lack of past experience in applying such methodologies in healthcare environments, this paper presents the main steps of a DPIA study and provides guidelines on how to carry them out effectively. To this respect, the Privacy Impact Assessment, Commission Nationale de l'Informatique et des Libertés (PIA-CNIL) methodology has been employed, which is also compliant with the privacy impact assessment tasks described in ISO/IEC 29134:2017. The work presented in this paper focuses on the first two steps of the DPIA methodology and more specifically on the identification of the Purposes of Processing and of the data categories involved in each of them, as well as on the evaluation of the organization's GDPR compliance level and of the gaps (Gap Analysis) that must be filled-in. The main contribution of this work is the identification of the main organizational and legal requirements that must be fulfilled by the health care organization. This research sets the legal grounds for data processing, according to the GDPR and is highly relevant to any processing of personal data, as it helps to structure the process, as well as be aware of data protection issues and the relevant legislation. [ABSTRACT FROM AUTHOR]

Low-Power Wide-Area Network (LPWAN) is one of the enabling technologies of the Internet of Things (IoT), and focuses on providing long distance connectivity for a vast amount of smart devices. Currently, LoRa is one of the leading LPWAN solutions available for public use. In LPWANs, especially in LoRa, security is a major concern due to the resource constraints of the devices, the sensitivity level of the transmitted data, the large amount of connected devices, among other reasons. This paper studies the key management mechanism of LoRaWAN environments. A secure architecture for key management based on smart contracts and permissioned blockchain to enhance security and availability in LoRaWAN networks is proposed. To demonstrate the feasibility of the proposed blockchain-based LoRaWAN architecture, a working prototype has been created using open-source tools and commodity hardware. Performance analysis shows that the prototype presents similar execution time and latency values, when compared to a traditional system, especially for small and medium-sized LoRaWAN networks. We also discuss why the proposed solution can be used in environments with a large number of end-devices. [ABSTRACT FROM AUTHOR]

The sinkhole attack in an edge-based Internet of Things (IoT) environment (EIoT) can devastate and ruin the whole functioning of the communication. The sinkhole attacker nodes ( S H A s) have some properties (for example, they first attract the other normal nodes for the shortest path to the destination and when normal nodes initiate the process of sending their packets through that path (i.e., via S H A ), the attacker nodes start disrupting the traffic flow of the network). In the presence of S H A s, the destination (for example, sink node i.e., gateway/base station) does not receive the required information or it may receive partial or modified information. This results in reduction of the network performance and degradation in efficiency and reliability of the communication. In the presence of such an attack, the throughput decreases, end-to-end delay increases and packet delivery ratio decreases. Moreover, it may harm other network performance parameters. Hence, it becomes extremely essential to provide an effective and competent scheme to mitigate this attack in EIoT. In this paper, an intrusion detection scheme to protect EIoT environment against sinkhole attack is proposed, which is named as SAD-EIoT. In SAD-EIoT, the resource rich edge nodes (edge servers) perform the detection of different types of sinkhole attacker nodes with the help of exchanging messages. The practical demonstration of SAD-EIoT is also provided using the well known NS2 simulator to compute the various performance parameters. Additionally, the security analysis of SAD-EIoT is conducted to prove its resiliency against various types of S H A s. SAD-EIoT achieves around 95.83 % detection rate and 1.03 % false positive rate, which are considerably better than other related existing schemes. Apart from those, SAD-EIoT is proficient with respect to computation and communication costs. Eventually, SAD-EIoT will be a suitable match for those applications which can be used in critical and sensitive operations (for example, surveillance, security and monitoring systems). [ABSTRACT FROM AUTHOR]

Summary: Internet of Things (IoT) offers various types of application services in different domains, such as "smart infrastructure, health‐care, critical infrastructure, and intelligent transportation system." The name edge computing signifies a corner or edge in a network at which traffic enters or exits from the network. In edge computing, the data analysis task happens very close to the IoT smart sensors and devices. Edge computing can also speed up the analysis process, which allows decision makers to take action within a short duration of time. However, edge‐based IoT environment has several security and privacy issues similar to those for the cloud‐based IoT environment. Various types of attacks, such as "replay, man‐in‐the middle, impersonation, password guessing, routing attack, and other denial of service attacks" may be possible in edge‐based IoT environment. The routing attacker nodes have the capability to deviate and disrupt the normal flow of traffic. These malicious nodes do not send packets (messages) to the edge node and only send packets to its neighbor collaborator attacker nodes. Therefore, in the presence of such kind of routing attack, edge node does not get the information or sometimes it gets the partial information. This further affects the overall performance of communication of edge‐based IoT environment. In the presence of such an attack, the "throughput of the network" decreases, "end‐to‐end delay" increases, "packet delivery ratio" decreases, and other parameters also get affected. Consequently, it is important to provide solution for such kind of attack. In this paper, we design an intrusion detection scheme for the detection of routing attack in edge‐based IoT environment called as RAD‐EI. We simulate RAD‐EI using the widely used "NS2 simulator" to measure different network parameters. Furthermore, we provide the security analysis of RAD‐EI to prove its resilience against routing attacks. RAD‐EI accomplishes around 95.0% "detection rate" and 1.23% "false positive rate" that are notably better than other related existing schemes. In addition, RAD‐EI is efficient in terms of computation and communication costs. As a result, RAD‐EI is a good match for some critical and sensitive applications, such as smart security and surveillance system. [ABSTRACT FROM AUTHOR]

The articles in this special section present the most recent advances in amateur drone surveillance network architecture and technologies. The advancement in communication, networking and sensing technologies has attracted researchers, hobbyists, and investors to deploy mini-drones, a.k.a. unmanned air vehicles (UAVs). Drones have boundless viable applications due to their small size and ability to fly without an on-board pilot such as in agriculture, surveillance, and numerous public services. The use of drones for achieving high speed wireless communication is one of the most significant applications for next-generation communication systems (5G). However, their deployment poses several public safety threats to national institutions such as atomic plants, historic places, and the homes of public officials because of their ability to carry explosives and other destructive chemicals. To cope with these security threats, the deployment of surveillance drones is required to monitor amateur drones. The main motivation of deploying surveillance drones is to keep an eye on amateur drones, which can cause serious disasters if no precautionary measures are taken on time. The increasing use of surveillance drones presents challenges such as robust detection, tracking, intruder localization, and jamming. The accuracy of detection is a basic requirement of the system. In general, accurate detection is time-consuming. In fact, a precise moving object detection method makes tracking more reliable and faster, and supports correct classification, which is quite important for surveillance drones to be successful. [ABSTRACT FROM PUBLISHER]

The advent of online social networks (OSN) has transformed a common passive reader into a content contributor. It has allowed users to share information and exchange opinions, and also express themselves in online virtual communities to interact with other users of similar interests. However, OSN have turned the social sphere of users into the commercial sphere. This should create a privacy and security issue for OSN users. OSN service providers collect the private and sensitive data of their customers that can be misused by data collectors, third parties, or by unauthorized users. In this paper, common security and privacy issues are explained along with recommendations to OSN users to protect themselves from these issues whenever they use social media. [ABSTRACT FROM AUTHOR]