Biblio

With the development of wireless sensor networks (WSNs), WSNs have been widely used in various fields such as animal habitat detection, military surveillance, etc. This paper focuses on protecting the source location privacy (SLP) in WSNs. Existing algorithms perform poorly in non-uniform networks which are common in reality. In order to address the performance degradation problem of existing algorithms in non-uniform networks, this paper proposes a robust fixed path-based random routing scheme (RFRR), which guarantees the path diversity with certainty in non-uniform networks. In RFRR, the data packets are sent by selecting a routing path that is highly differentiated from each other, which effectively protects SLP and resists the backtracking attack. The experimental results show that RFRR increases the difficulty of the backtracking attack while safekeeping the balance between security and energy consumption.

It is important to ensure source location privacy (SLP) protection in safety-critical monitoring applications. Also, to achieve effective long-term monitoring, it is essential to design SLP protocols with high energy efficiency and energy balancing. Therefore, this study proposes a new phantom with angle (PwA) protocol. The PwA protocol employs dynamic routing paths which are designed to achieve SLP protection with energy efficiency and energy balancing. Analysis results reveal that the PwA protocol exhibits superior performance features to outperform existing protocols by achieving high levels of SLP protection for time petime periods. The results confirm that the PwA protocol is practical in long-term monitoring systems.riods. The results confirm that the PwA protocol is practical in long-term monitoring systems.

In a beyond-5G (B5G) scenario, we consider a virtual private mobile network (VPMN), i.e., a set of user equipments (UEs) directly communicating in a device-to-device (D2D) fashion, and connected to the cellular network by multiple gateways. The purpose of the VPMN is to hide the position of the VPMN UEs to the mobile network operator (MNO). We investigate the design and performance of packet routing inside the VPMN. First, we note that the routing that maximizes the rate between the VPMN and the cellular network leads to an unbalanced use of the gateways by each UE. In turn, this reveals information on the location of the VPMN UEs. Therefore, we derive a routing algorithm that maximizes the VPMN rate, while imposing for each UE the same data rate at each gateway, thus hiding the location of the UE. We compare the performance of the resulting solution, assessing the location privacy achieved by the VPMN, and considering both the case of single hop and multihop in the transmissions from the UEs to the gateways.

Wireless Sensor Networks (WSNs) and their implementations have been the subject of numerous studies over the last two decades. WSN gathers, processes, and distributes wireless data to the database storage center. This study aims to explain the four main components of sensor nodes and the mechanism of WSN's. WSNs have 5 available types that will be discussed and explained in this paper. In addition to that, shortest path routing will be thoroughly analyzed. In “The Protocol”. Reconfigurable logic applications have grown in number and complexity. Shortest path routing is a method of finding paths through a network with the least distance or other cost metric. The efficiency of the shortest path protocol mechanism and the reliability of encryption are both present which adds security and accuracy of location privacy and message delivery. There are different forms of key management, such as symmetric and asymmetric encryption, each with its own set of processing techniques. The use of encryption technique to secure sensor nodes is addressed, as well as how we overcame the problem with the aid of advanced techniques. Our major findings are that adding more security doesn't cost much and by cost we mean energy consumption, throughput and latency.

In recent years, with the rise of the Internet of things industry, a variety of user location-based applications came into being. While users enjoy these convenient services, their location information privacy is also facing a great threat. Therefore, the research on location privacy protection in the Internet of things has become a hot spot for scholars. Privacy protection microdata publishing is a hot spot in data privacy protection research. Data interference is an effective solution for privacy protection microdata publishing. Aiming at privacy protection clustering problem, a privacy protection data interference method is proposed. In this paper, the location privacy protection algorithm is studied, with the purpose of providing location services and protecting the data interference of users' location privacy. In this paper, the source location privacy protection protocol (PR \_ CECRP) algorithm with controllable energy consumption is proposed to control the energy consumption of phantom routing strategy. In the routing process from the source node to the phantom node, the source data packet forwarding mechanism based on sector area division is adopted, so that the random routing path is generated and the routing energy consumption and transmission delay are effectively controlled.

With the popularization of mobile communication and sensing equipment, as well as the rapid development of location-aware technology and wireless communication technology, LBSs(Location-based services) bring convenience to people’s lives and enable people to arrange activities more efficiently and reasonably. It can provide more flexible LBS proximity detection query, which has attracted widespread attention in recent years. However, the development of proximity detection query still faces many severe challenges including query information privacy. For example, when users want to ensure their location privacy and data security, they can get more secure location-based services. In this article, we propose an efficient and privacy-protecting proximity detection framework based on location services: PD(Proximity Detection). Through PD, users can query the range of arbitrary polygons and obtain accurate LBS results. Specifically, based on homomorphic encryption technology, an efficient PRQ(polygon range query) algorithm is constructed. With the help of PRQ, PD, you can obtain accurate polygon range query results through the encryption request and the services provided by the LAS(LBS Agent Server) and the CS(Cloud Server). In addition, the query privacy of the queryer and the information of the data provider are protected. The correctness proof and performance analysis show that the scheme is safe and feasible. Therefore, our scheme is suitable for many practical applications.

Wireless sensor networks (WSNs) have gained increasing popularity in ubiquitous support of sensing system services. Often, WSNs are energy-constrained and they are deployed in harsh and unattended environments. Consequently, WSNs are vulnerable to energy and environmental factors. To ensure secure and reliable operations in safety-critical monitoring WSNs, it is important to guarantee energy-efficient communications, location privacy protection, and reliability. Fake packet-based source location privacy (SLP) protocols are known to be energy-inefficient. Therefore, in this study, we investigate the impact of energy-inefficient communications on the privacy performance of the fake packet-based SLP protocols. Experiment results show that the protocols achieve short-term and less reliable SLP protection.

The problem of maintaining the privacy of sensitive healthcare data is crucial yet the significance of research efforts achieved still need robust development in privacy protection techniques for Wireless Multimedia Sensor Networks (WMSNs). This paper aims to investigate different privacy-preserving methods for WMSNs that can be applied in healthcare, to guarantee a privacy-aware transmission of multimedia data between sensors and base stations. The combination of ant colony optimization-based routing and hierarchical structure of the network have been proposed in the AntSensNet WMSN-based routing protocol to offer QoS and power efficient multipath multimedia packet scheduling. In this paper, the AntSensNet routing protocol was extended by utilizing privacy-preserving mechanisms thus achieving anonymity / pseudonymity, unlinkability, and location privacy. The vulnerability of standard AntSensNet routing protocol to privacy threats have raised the need for the following privacy attacks’ countermeasures: (i) injection of fake traffic, which achieved anonymity, privacy of source and base locations, as well as unlinkability; (ii) encrypting and correlating the size of scalar and multimedia data which is transmitted through a WMSN, along with encrypting and correlating the size of ants, to achieve unlinkability and location privacy; (iii) pseudonyms to achieve unlinkability. The impact of these countermeasures is assessed using quantitative performance analysis conducted through simulation to gauge the overhead of the added privacy countermeasures. It can be concluded that the introduced modifications did enhance the privacy but with a penalty of increased delay and multimedia jitter. The health condition of a patient determines the vitals to be monitored which affects the volumes and sources of fake traffic. Consequently, desired privacy level will dictate incurred overhead due to multimedia transmissions and privacy measures.

Nowadays, biometric is a most technique to authenticate /identify human been, because its resistance against theft, loss or forgetfulness. However, biometric is subject to different transmission attacks. Today, the protection of the sensitive biometric information is a big challenge, especially in current wireless networks such as internet of things where the transmitted data is easy to sniffer. For that, this paper proposes an Eigens-Fingerprint-based biometric cryptosystem, where the biometric feature vectors are extracted by the Principal Component Analysis technique with an appropriate quantification. The key-binding principle incorporated with bit-wise and byte-wise correcting code is used for encrypting data and sharing key. Several recognition rates and computation time are used to evaluate the proposed system. The findings show that the proposed cryptosystem achieves a high security without decreasing the accuracy.

The convergence of Internet of Things (IoT) and cloud computing is due to the practical necessity for providing broader services to extensive user in distinct environments. However, cloud computing has numerous constraints for applications that require high-mobility and high latency, notably in adversarial situations (e.g. battlefields). These limitations can be elevated to some extent, in a fog computing model because it covers the gap between remote data-center and edge device. Since, the fog nodes are usually installed in remote areas, therefore, they impose the design of fool proof safety solution for a fog-based setting. Thus, to ensure the security and privacy of fog-based environment, numerous schemes have been developed by researchers. In the recent past, Jia et al. (Wireless Networks, DOI: 10.1007/s11276-018-1759-3) designed a fog-based three-party scheme for healthcare system using bilinear. They claim that their scheme can withstand common security attacks. However, in this work we investigated their scheme and show that their scheme has different susceptibilities such as revealing of secret parameters, and fog node impersonation attack. Moreover, it lacks the anonymity of user anonymity and has inefficient login phase. Consequently, we have suggestion with some necessary guidelines for attack resilience that are unheeded by Jia et al.

One of the most essential ways of communication is the wireless network. As a result, ensuring the security of information transmitted across wireless networks is a critical concern. For wireless networks, classical cryptography provides conditional security with several loopholes, but quantum cryptography claims to be unconditionally safe. People began to consider beyond classical cryptosystems for protecting future electronic communication when quantum computers became functional. With all of these flaws in classical cryptosystems in mind, people began to consider beyond it for protecting future electronic communication. Quantum cryptography addresses practically all flaws in traditional cryptography.

Physical layer security has a paramount importance in tactical wireless networks. Traditional approaches may not fulfill all requirements, demanding additional sophisticated techniques. Thus, Combined Interference and Communications (CIC) emerges as a strategy against message interception in Cognitive Radio Military Networks (CRMN). Since CIC adopts an interference approach under specific CRMN requirements and characteristics, it saves great energy and reduces the receiver detection factor when compared to previous proposals in the literature. However, previous CIC analyses were conducted under vaguely realistic channel models. Thus, the focus of this paper is two-fold. Firstly, we identify more realistic channel models to achieve tactical network scenario channel parameters. Additionally, we use such parameters to evaluate CIC suitability to increase CRMN physical layer security. Numerical experiments and emulations illustrate potential impairments on previous work due to the adoption of unrealistic channel models, concluding that CIC technique remains as an upper limit to increase physical layer security in CRMN.

Software-Defined Networking (SDN) has found applications in different domains, including wired- and wireless networks. The SDN controller has a global view of the network topology, which is vulnerable to topology poisoning attacks, e.g., link fabrication and host-location hijacking. The adversaries can leverage these attacks to monitor the flows or drop them. However, current defence systems such as TopoGuard and TopoGuard+ can detect such attacks. In this paper, we introduce the Link Latency Attack (LLA) that can successfully bypass the systems' defence mechanisms above. In LLA, the adversary can add a fake link into the network and corrupt the controller's view from the network topology. This can be accomplished by compromising the end hosts without the need to attack the SDN-enabled switches. We develop a Machine Learning-based Link Guard (MLLG) system to provide the required defence for LLA. We test the performance of our system using an emulated network on Mininet, and the obtained results show an accuracy of 98.22% in detecting the attack. Interestingly, MLLG improves 16% the accuracy of TopoGuard+.

Research has been conducted on wireless network single link failures. However, cascaded link failures due to fraudulent attacks have not received enough attention, whereas this requires solutions. This research developed an enhanced genetic algorithm (EGA) focused on capacity efficiency and fast restoration to rapidly resolve link-link failures. On complex nodes network, this fault-tolerant model was tested for such failures. Optimal alternative routes and the bandwidth required for quick rerouting of video traffic were generated by the proposed model. Increasing cascaded link failures increases bandwidth usage and causes transmission delay, which slows down video traffic routing. The proposed model outperformed popular Dijkstra models, in terms of time complexity. The survived solution paths demonstrate that the proposed model works well in maintaining connectivity despite cascaded link failures and would therefore be extremely useful in pandemic periods on emergency matters. The proposed technology is feasible for current business applications that require high-speed broadband networks.

This paper for the first time investigate the security and reliability performance of ultra-reliable low-latency communication (URLLC) systems in the presence of randomly distributed eavesdroppers, where the impact of short blocklength codes and imperfect channel estimation are jointly considered. Based on the finite-blocklength information theory, we first derive a closed-form approximation of transmission error probability to describe the degree of reliability loss. Then, we also derive an asymptotic expression of intercept probability to characterize the security performance, where the impact of secrecy protected zone is also considered. Simulation and numerical results validate the accuracy of theoretical approximations, and illustrate the tradeoff between security and reliability. That is, the intercept probability of URLLC systems can be suppressed by loosening the reliability requirement, and vice versa. More importantly, the theoretical analysis and methodologies presented in this paper can offer some insights and design guidelines for supporting secure URLLC applications in the future 6G wireless networks.

Wireless communications networks are an integral part of intelligent systems that enhance the automation of various activities and operations embarked by humans. For example, the development of intelligent devices imbued with sensors leverages emerging technologies such as machine learning (ML) and artificial intelligence (AI), which have proven to enhance military operations through communication, control, intelligence gathering, and situational awareness. However, growing concerns in cybersecurity imply that attackers are always seeking to take advantage of the widened attack surface to launch adversarial attacks which compromise the activities of legitimate users. To address this challenge, we leverage on deep learning (DL) and the principle of cyber-deception to propose a method for defending wireless networks from the activities of jammers. Specifically, we use DL to regulate the power allocated to users and the channel they use to communicate, thereby luring jammers into attacking designated channels that are considered to guarantee maximum damage when attacked. Furthermore, by directing its energy towards the attack on a specific channel, other channels are freed up for actual transmission, ensuring secure communication. Through simulations and experiments carried out, we conclude that this approach enhances security in wireless communication systems.

The Internet of Battlefield Things is a relatively new cyberphysical system and even though it shares a lot of concepts from the Internet of Things and wireless ad hoc networking in general, a lot of research is required to address its scale and peculiarities. In this article we examine a fundamental problem pertaining to the routing/dissemination of information, namely the construction of a backbone. We model an IoBT ad hoc network as a multilayer network and employ the concept of domination for multilayer networks which is a complete departure from the volume of earlier works, in order to select sets of nodes that will support the routing of information. Even though there is huge literature on similar topics during the past many years, the problem in military (IoBT) networks is quite different since these wireless networks are multilayer networks and treating them as a single (flat) network or treating each layer in isolation and calculating dominating set produces submoptimal or bad solutions; thus all the past literature which deals with single layer (flat) networks is in principle inappropriate. We design a new, distributed algorithm for calculating connected dominating sets which produces dominating sets of small cardinality. We evaluate the proposed algorithm on synthetic topologies, and compare it against the only two existing competitors. The proposed algorithm establishes itself as the clear winner in all experiments.

The industry of telecommunications is being transformed towards 5G technology, because it has to deal with the emerging and existing use cases. Because, 5G wireless networks need rather large data rates and much higher coverage of the dense base station deployment with the bigger capacity, much better Quality of Service - QoS, and the need very low latency [1–3]. The provision of the needed services which are envisioned by 5G technologies need the new service models of deployment, networking architectures, processing technologies and storage to be defined. These technologies will cause the new problems for the cybersecurity of 5G systems and the security of their functionality. The developers and researchers working in this field make their best to secure 5G systems. The researchers showed that 5G systems have the security challenges. The researchers found the vulnerabilities in 5G systems which allow attackers to integrate malicious code into the system and make the different types of the illegitimate actions. MNmap, Battery drain attacks and MiTM can be successfully implemented on 5G. The paper makes the analysis of the existing cyber security problems in 5G technology. Based on the analysis, we suggest the novel Intrusion Detection System - IDS by means of the machine-learning algorithms. In the related papers the scientists offer to use NSL-KDD in order to train IDS. In our paper we offer to train IDS using the big datasets of DOS/DDOS attacks, besides of training using NSL-KDD. The research also offers the methodology of integration of the offered intrusion detection systems into an standard architecture of 5G. The paper also offers the pseudo code of the designed system.

With the gradually popular high-speed wireless networks and 5G environments, the quality and reliability of network services will be suited for mobile vehicles. In addition to communicating information between vehicles, they can also communicate information with surrounding roadside equipment, pedestrians or traffic signs, and thus improve the road safety of passers-by.Recently, various countries have continuously invested in research on autonomous driving and unmanned vehicles. The open communication environment of the Internet of Vehicles in 5G will expose all personal information in the field of wireless networks. This research is based on the consideration of information security and personal data protection. We will focus on how to protect the real-time transmission of information between mobile vehicles to prevent from imbedding or altering important transmission information by unauthorized vehicles, drivers or passers-by participating in communications. Moreover, this research proposes a multi-level security key management agreement based on a dynamic M-tree structure for Internet of Vehicles to achieve flexible and scalable key management on large-scale Internet of Vehicles.

With the rapid development of the wireless network and smart mobile equipment, many lawbreakers employ mobile devices to destroy and steal important information and property from other persons. In order to fighting the criminal act efficiently, the public security organ need to collect the evidences from the crime tools and submit to the court. In the meantime, with development of internal storage technology, the law enforcement officials collect lots of information from the smart mobile equipment, for the sake of handling the huge amounts of data, we propose a framework that combine distributed clustering methods to analyze data sets, this model will split massive data into smaller pieces and use clustering method to analyze each smaller one on disparate machines to solve the problem of large amount of data, thus forensics investigation work will be more effectively.

The ongoing expansion of underwater Internet of Things techniques promote diverse categories of maritime intelligent systems, e.g., Underwater Acoustic Sensor Networks (UASNs), Underwater Wireless Networks (UWNs), especially multiple Autonomous Underwater Vehicle (AUV) based UWNs have produced many civil and military applications. To enhance the network management and scalability, in this paper, the technique of Software-Defined Networking (SDN) technique is introduced, leading to the paradigm of Software-Defined multi-AUV-based UWNs (SD-UWNs). With SD-UWNs, the network architecture is divided into three functional layers: data layer, control layer, and application layer, and the network administration is re-defined by a framework of software-defined beacon. To manage the network, a control model based on artificial potential field and network topology theory is constructed. On account of the efficient data sharing ability of SD-UWNs, a proactive alarming-enabled path planning scheme is proposed, wherein all potential categories of obstacle avoidance scenes are taken into account. Evaluation results indicate that the proposed SD-UWN is more efficient in scheduling the cooperative network function than the traditional approaches and can secure exact path planning.

Radio is the most important part of any wireless network. Radio Access Network (RAN) has been virtualized and disaggregated into different functions whose location is best defined by the requirements and economics of the use case. This Virtualized RAN (vRAN) architecture separates network functions from the underlying hardware and so 5G can leverage virtualization of the RAN to implement these functions. The easy expandability and manageability of the vRAN support the expansion of the network capacity and deployment of new features and algorithms for streamlining resource usage. In this paper, we try to address the problem of scheduling 5G vRAN with mid-haul network capacity constraints as a combinatorial optimization problem. We transformed it to a Quadratic Unconstrained Binary Optimization (QUBO) problem by using a newly proposed quantum-based algorithm and compared our implementation with existing classical algorithms. This work has demonstrated the advantage of quantum computers in solving a particular optimization problem in the Telecommunication domain and paves the way for solving critical real-world problems using quantum computers faster and better.

Radio-frequency (RF) sensing is a key technology for designing intelligent and secure wireless networks with high spectral efficiency and environment-aware adaptation capabilities. However, existing sensing techniques can extract only limited information from RF signals or assume that the RF signals are generated by certain known protocols. As a result, their applications are limited if proprietary protocols or encryption methods are adopted, or in environments subject to errors such as unintended interference. To address this challenge, we study protocol-agnostic cross-layer sensing to extract high-layer protocol information from raw RF samples without any a priori knowledge of the protocols. First, we present a framework for protocol-agnostic sensing for over-the-air (OTA) RF signals, by taking packet boundary recognition (PBR) as an example. The framework consists of three major components: OTA Signal Generator, Agnostic RF Sink, and Ground Truth Generator. Then, we develop a software-defined testbed using USRP SDRs, with eleven benchmark statistical algorithms implemented in the Agnostic RF Sink, including Kullback-Leibler divergence and cross-power spectral density, among others. Finally, we test the effectiveness of these statistical algorithms in PBR on OTA RF samples, considering a wide variety of transmission parameters, including modulation type, transmission distance, and packet length. It is found that none of these benchmark statistical algorithms can achieve consistently high PBR rate, and new algorithms are required particularly in next-generation low-latency wireless systems.

A door enables you to enter a room without breaking through a wall. Also, a door enables you for privacy, environmental or security reasons. The problem statement which is the biometric system sometimes is sensitive and will not be able to sense the biological pattern of the employer’s fingerprint due to sweat and other factors. Next, people tend to misplace their key or RFID card. Apart from that, people tend to forget their pin number for a door lock. The objective of this paper is to present a secret knock intensity for door lock security system using Arduino and mobile. This project works by using a knock intensity and send the information to mobile application via wireless network to unlock or lock the door.

Underwater wireless sensor network(UWSN) is an emerging technology for exploring and research inside the ocean. Since it is somehow similar to the normal wireless network, which uses radio signals for communication purposes, while UWSN uses acoustic for communication between nodes inside the ocean and sink nodes. Due to unattended areas and the vulnerability of acoustic medium, UWNS are more prone to various malicious attacks like Sybil attack, Black-hole attack, Wormhole attack, etc. This paper analyzes blackhole attacks in UWSN and proposes an algorithm to mitigate blackhole attacks by forming clusters of nodes and selecting coordinator nodes from each cluster to identify the presence of blackholes in its cluster. We used public-key cryptography and the challenge-response method to authenticate and verify nodes.