Biblio

The Internet is evolving everywhere and expanding its entity globally. The IoT(Internet of things) is a new and interesting concept introduced in this world of internet. Generally it is interconnected computing device which can be embedded in our daily routine objects through which we can send and receive data. It is beyond connecting computers and laptops only although it can connect billion of devices. It can be described as reliable method of communication that also make use of other technologies like wireless sensor, QR code etc. IoT (Internet of Things) is making everything smart with use of technology like smart homes, smart cities, smart watches. In this chapter, we will study the security algorithms in IoT (Internet of Things) which can be achieved with encryption process. In the world of IoT, data is more vulnerable to threats. So as to protect data integrity, data confidentiality, we have Light weight Encryption Algorithms like symmetric key cryptography and public key cryptography for secure IoT (Internet of Things) named as Secure IoT. Because it is not convenient to use full encryption algorithms that require large memory size, large program code and larger execution time. Light weight algorithms meet all resource constraints of small memory size, less execution time and efficiency. The algorithms can be measured in terms of key size, no of blocks and algorithm structure, chip size and energy consumption. Light Weight Techniques provides security to smart object networks and also provides efficiency. In Symmetric Key Cryptography, two parties can have identical keys but has some practical difficulty. Public Key Cryptography uses both private and public key which are related to each other. Public key is known to everyone while private key is kept secret. Public Key cryptography method is based on mathematical problems. So, to implement this method, one should have a great expertise.

Despite the high directivity of THz beams, THz wireless links may still suffer compromising emissions when propagate through atmospheric turbulence and suffers scattering. In this work, we investigate the eavesdropping risks of a line-of-sight (LOS) THz link `in atmospheric turbulence with an eavesdropper located close to but outside of the beam path. A theoretical model considering the turbulence induced losses, gaseous absorption and beam divergence is conducted. Theoretical estimations agree well with our measured data. The secrecy capacity and outage probability dependent on the carrier frequency, turbulence strength, eavesdropper’s position and receiver sensitivity are analyzed.

The increased demand of multimedia leads to shortage of network bandwidth and memory capacity. As a result, image compression is more significant for decreasing data redundancy, saving storage space and bandwidth. Along with the compression the next major challenge in this field is to safeguard the compressed data further from the spy which are commonly known as hackers. It is evident that the major increments in the fields like communication, wireless sensor network, data science, cloud computing and machine learning not only eases the operations of the related field but also increases the challenges as well. This paper proposes a worthy composition for image compression encryption based on unsupervised learning i.e. k-means clustering for compression with logistic chaotic map for encryption. The main advantage of the above combination is to address the problem of data storage and the security of the visual data as well. The algorithm reduces the size of the input image and also gives the larger key space for encryption. The validity of the algorithm is testified with the PSNR, MSE, SSIM and Correlation coefficient.

Recent technological advances in developing intelligent telecommunication networks, ultra-compact bendable wireless transceiver chips, adaptive wearable sensors and actuators, and secure computing infrastructures along with the progress made in psychology and neuroscience for understanding neu-rocognitive and computational principles of human behavior combined have paved the way for a new field of research: Tactile Internet with Human-in-the-Loop (TaHiL). This emerging field of transdisciplinary research aims to promote next generation digitalized human-machine interactions in perceived real time. To achieve this goal, mechanisms and principles of human goal-directed multisensory perception and action need to be integrated into technological designs for breakthrough innovations in mobile telecommunication, electronics and materials engineering, as well as computing. This overview highlights key challenges and the frontiers of research in the new field of TaHiL. Revolutionizing the current Internet as a digital infrastructure for sharing visual and auditory information globally, the TaHiL research will enable humans to share tactile and haptic information and thus veridically immerse themselves into virtual, remote, or inaccessible real environments to exchange skills and expertise with other humans or machines for applications in medicine, industry, and the Internet of Skills.

In recent years, with the rapid update of wireless communication technologies such as 5G and the Internet of Things, as well as the explosive growth of wireless intelligent devices, people's demand for radio spectrum resources is increasing, which leads spectrum scarcity is becoming more serious. To address the scarcity of spectrum, the Internet of Things based on cognitive radio (CR-IoT) has become an effective technique to enable IoT devices to reuse the spectrum that has been fully utilized. The frequency band information is transmitted through wireless communication in the CR-IoT network, so the node is easily to be eavesdropped or tampered with by attackers in the process of transmitting data, which leads to information leakage and wrong perception results. To deal with the security problem of channel data transmission, this paper proposes a chaotic compressed spectrum sensing algorithm. In this algorithm, the chaotic parameter package is utilized to generate the measurement matrix, which makes good use of the sensitivity of the initial value of chaotic system to improve the transmission security. And the introduction of the semi-tensor theory significantly reduces the dimension of the matrix that the secondary user needs to store. In addition, the semi-tensor compressed sensing is used in the fusion center for parallel reconstruction process, which effectively reduces the sensing time delay. The simulation results show that the chaotic compressed spectrum sensing algorithm can achieve faster, high-quality, and low-energy channel energy transmission.

IoT applications are changing our daily lives. These innovative applications are supported by new communication technologies and protocols. Particularly, the information-centric network (ICN) paradigm is well suited for many IoT application scenarios that involve large-scale wireless sensor networks (WSNs). Even though the ICN approach can significantly reduce the network traffic by optimizing the process of information recovery from network nodes, it is also possible to apply data aggregation strategies. This paper proposes an unsupervised machine learning-based data aggregation strategy for multi-hop information-centric WSNs. The results show that the proposed algorithm can significantly reduce the ICN data traffic while having reduced information degradation.

Congestion control is one of the essential keys to enhance network efficiency so that the network can perform well even in the case of packet drop. This problem is even more challenging in Information-Centric Networking (ICN), a typical Future Internet design, which employs the packet flooding policy for forwarding the information. To diminish the high traffic load due to the huge number of packets in the era of the Internet of Things (IoT), this paper proposes an effective caching and forwarding algorithm to diminish the congestion rate of the IoT wireless sensor in ICN. The proposed network system utilizes accumulative popularity-based delay transmission time for forwarding strategy and includes the consecutive chunks-based segment caching scheme. The evaluation results using ndnSIM, a widely-used ns-3 based ICN simulator, demonstrated that the proposed system can achieve less interest packet drop rate, more cache hit rate, and higher network throughput, compared to the relevant ICN-based benchmarks. These results prove that the proposed ICN design can achieve higher network efficiency with a lower congestion rate than that of the other related ICN systems using IoT sensors.

Wireless Sensor Network consists of hundreds to thousands of tiny sensor nodes deployed in the large field of the target phenomenon. Sensor nodes have advantages for its size, multifunctional, and inexpensive features; unfortunately, the resources are limited in terms of memory, computational, and in energy, especially. Network transmission between nodes and base station (BS) needs to be carefully designed to prolong the network life cycle. As the data transmission is energy consuming compared to data processing, designing sensor nodes into hierarchical network architecture is preferable because it can limit the network transmission. LEACH is one of the hierarchical network protocols known for simple and energy saving protocols. There are lots of modification made since LEACH was introduced for more energy efficient purposed. In this paper, hybridization of LEACH-C and LEACH-R and the modification have been presented for a more energy saving LEACH called LEACH-CR. Experimental result was compared with previous LEACH variant and showed to has advantages over the existing LEACH protocols in terms of energy consumption, dead/alive nodes, and the packet sent to Base Station. The result reflects that the consideration made for residual energy to select the cluster head and proximity transmission lead to a better energy consumption in the network.

The recent events regarding worldwide human health sped up research efforts and resulted in the tremendous development of new technologies and applications. The last decade proved that new technologies find a proper place in worldwide human health and wellbeing, therefore the security of data during wireless transmission in medical facilities and for medical devices has become a research area of considerable importance. To provide enhanced security using conventional visible light wireless communication, we propose in this paper a novel communication protocol based on asymmetric encryption with a private key. We base the wireless communication protocol described in this work on a data encryption method using block chipers, and we propose it for medical facilities and devices with visible light transmission technology embedded. The asymmetric encryption with a private key algorithm, as part of a transmission protocol, aim to assure the security of sensitive medical data during wireless communication.

Intelligent reflecting surfaces (IRS) can improve the physical layer security (PLS) by providing a controllable wireless environment. In this paper, we propose a novel PLS technique with the help of IRS implemented by an intelligent mirror array for the visible light communication (VLC) system. First, for the IRS aided VLC system containing an access point (AP), a legitimate user and an eavesdropper, the IRS channel gain and a lower bound of the achievable secrecy rate are derived. Further, to enhance the IRS channel gain of the legitimate user while restricting the IRS channel gain of the eavesdropper, we formulate an achievable secrecy rate maximization problem for the proposed IRS-aided PLS technique to find the optimal orientations of mirrors. Since the sensitivity of mirrors’ orientations on the IRS channel gain makes the optimization problem hard to solve, we transform the original problem into a reflected spot position optimization problem and solve it by a particle swarm optimization (PSO) algorithm. Our simulation results show that secrecy performance can be significantly improved by adding an IRS in a VLC system.

Edge computing supports the deployment of ubiquitous, smart services by providing computing and storage closer to terminal devices. However, ensuring the full security and privacy of computations performed at the edge is challenging due to resource limitation. This paper responds to this challenge and proposes an adaptive approach to defense randomization among the edge data centers via a stochastic game, whose solution corresponds to the optimal security deployment at the network's edge. Moreover, security risk is evaluated subjectively based on Prospect Theory to reflect realistic scenarios where the attacker and the edge system do not similarly perceive the status of the infrastructure. The results show that a non-deterministic defense policy yields better security compared to a static defense strategy.

Underwater acoustic sensor networks (UASNs) have been receiving more and more attention due to their wide applications and the marine data collection is one of the important applications of UASNs. However, the openness and unreliability of underwater acoustic communication links and the easy capture of underwater wireless devices make UASNs vulnerable to various attacks. On the other hand, due to the limited resources of underwater acoustic network nodes, the high bit error rates, large and variable propagation delays, and low bandwidth of acoustic channels, many mature security mechanisms in terrestrial wireless sensor networks cannot be applied in the underwater environment [1]. In this paper, a secure communication protocol for marine data collection was proposed to ensure the confidentiality and data integrity of communication between under sensor nodes and the sink node in UASNs.

In recent years, the underwater sensor network has emerged as a promising solution for a wide range of marine applications. The underwater wireless sensors are usually designed to operate in open water, where eavesdropping can be a serious issue. Existing work either utilizes cryptography that is computationally intensive or requires expensive hardware. In this paper, we present a coordinated multi-point transmission based protocol to improve network security. The proposed protocol dynamically pairs sensors for coordinated communications to undermine the eavesdroppers’ capability. Our preliminary results indicate that the underwater sensor network security can be enhanced using the proposed method, especially in applications where cryptography or special hardware are not suitable.

Underwater wireless optical communications are studied through single photon detection, photon states modulation and quantum key encryption. These studies will promote the development of optical communication applications in underwater vehicles and underwater sensor networks.

To improve communication underwater, the underwater sensor networks (UWSN) provide gains for many different underwater applications, like Underwater Data-centers, Aquatic Monitoring, Tsunami Monitoring Systems, Aquatic Monitoring, Underwater Oil Field Discovery, Submarine Target Localization, Surveilling Water Territory of the Country via UWSN, Submarine Target Localization and many more. underwater applications are dependent on secure data communication in an underwater environment, so Data transmission in Underwater Sensor Network is a need of the future. Underwater data transmission itself is a big challenge due to various limitations of underwater communication mediums like lower bandwidth, multipath effect, path loss, propagation delay, noise, Doppler spread, and so on. These challenges make the underwater networks one of the most vulnerable networks for many different security attacks like sinkhole, spoofing, wormhole, misdirection, etc. It causes packets unable to be delivered to the destination, and even worse forward them to malicious nodes. A compromised node, which may be a router, intercepts packets going through it, and selectively drops them or can perform some malicious activity. This paper presents a solution to Mitigate unsecured data forwarding related attacks of an underwater sensor network, our solution uses a pre-shared key to secure communication and hashing algorithm to maintain the integrity of stored locations at head node and demonstration of attack and its mitigation done on Unetstack software.

Wireless embedded devices are key elements of Internet-of-Things (IoT) and industrial IoT (IIoT) applications. The complexity of these devices as well as the number of connected devices to networks increase steadily. The high intricacy of the overall system makes it error-prone and vulnerable to attacks and leads to the need to test individual parts or even the whole system. Therefore, this paper presents the concept of a flexible and distributed testbed to evaluate correct behavior in various operation or attack scenarios. It is based on the Robot Operating System (ROS) as communication framework to ensure modularity and expandability. The testbed integrates RF-jamming and measurement devices to evaluate remote attack scenarios and interference issues. An energy harvesting emulation cell is used to evaluate different real-world energy harvesting scenarios. A climatic test chamber allows to investigate the influence of temperature and humidity conditions on the system-under-test. As a testbed application scenario, the automated evaluation of an energy harvesting wireless sensor network designed to instrument automotive engine test benches is presented.

With the rapid development of Internet of Things technology and sensor networks, large amount of data is facing security challenges in the transmission process. In the process of data transmission, the standardization and authentication of data sources are very important. A digital signature scheme based on bilinear pairing problem is designed. In this scheme, by signing the authorization mechanism, the management node can control the signature process and distribute data. The use of private key segmentation mechanism can reduce the performance requirements of sensor nodes. The reasonable combination of timestamp mechanism can ensure the time limit of signature and be verified after the data is sent. It is hoped that the implementation of this scheme can improve the security of data transmission on the Internet of things environment.

Cyber Physical Systems (CPS) are characterized by their ability to integrate the physical and information or cyber worlds. Their deployment in critical infrastructure have demonstrated a potential to transform the world. However, harnessing this potential is limited by their critical nature and the far reaching effects of cyber attacks on human, infrastructure and the environment. An attraction for cyber concerns in CPS rises from the process of sending information from sensors to actuators over the wireless communication medium, thereby widening the attack surface. Traditionally, CPS security has been investigated from the perspective of preventing intruders from gaining access to the system using cryptography and other access control techniques. Most research work have therefore focused on the detection of attacks in CPS. However, in a world of increasing adversaries, it is becoming more difficult to totally prevent CPS from adversarial attacks, hence the need to focus on making CPS resilient. Resilient CPS are designed to withstand disruptions and remain functional despite the operation of adversaries. One of the dominant methodologies explored for building resilient CPS is dependent on machine learning (ML) algorithms. However, rising from recent research in adversarial ML, we posit that ML algorithms for securing CPS must themselves be resilient. This article is therefore aimed at comprehensively surveying the interactions between resilient CPS using ML and resilient ML when applied in CPS. The paper concludes with a number of research trends and promising future research directions. Furthermore, with this article, readers can have a thorough understanding of recent advances on ML-based security and securing ML for CPS and countermeasures, as well as research trends in this active research area.

Nodes in wireless Internet of Things (IoT) sensor networks are heterogeneous in nature. This heterogeneity can come from energy and security resources available at the node level. Besides, these resources are usually limited. Efficient cluster head (CH) selection in rounds is the key to preserving energy resources of sensor nodes. However, energy and security resources are contradictory to one another. Therefore, it is challenging to ensure CH selection with appropriate security resources without decreasing energy efficiency. Coverage and energy optimization subject to a required security level can form a solution to the aforementioned trade-off. This paper proposes a security level aware CH selection algorithm in wireless sensor networks for IoT. The proposed method considers energy and security level updates for nodes and coverage provided by associated CHs. The proposed method performs CH selection in rounds and in a centralized parallel processing way, making it applicable to the IoT scenario. The proposed algorithm is compared to existing traditional and emerging CH selection algorithms that apply security mechanisms in terms of energy and security efficiencies.

A sensor network is wireless with tiny nodes and widely used in various applications. To track the event and collect the data from a remote area or a hostile area sensor network is used. A WSN collects wirelessly connected tiny sensors with minimal resources like the battery, computation power, and memory. When a sensor collects data, it must be transferred to the control center through the gateway (Sink), and it must be transferred safely. For secure transfer of data in the network, the routing protocol must be safe and can use the cryptography method for authentication and confidentiality. An essential issue in WSN structure is the key management. WSN relies on the strength of the communicating devices, battery power, and sensor nodes to communicate in the wireless environment over a limited region. Due to energy and memory limitations, the construction of a fully functional network needs to be well arranged. Several techniques are available in the current literature for such key management techniques. Among the distribution of key over the network, sharing private and public keys is the most important. Network security is not an easy problem because of its limited resources, and these networks are deployed in unattended areas where they work without any human intervention. These networks are used to monitor buildings and airports, so security is always a major issue for these networks. In this paper, we proposed a dynamic key management scheme for the clustered sensor network that also supports the addition of a new node in the network later. Keys are dynamically generated and securely distributed to communication parties with the help of a cluster head. We verify the immunity of the scheme against various attacks like replay attack and node captured attacker. A simulation study was also done on energy consumption for key setup and refreshed the keys. Security analysis of scheme shows batter resiliency against node capture attack.

The last couple of years have seen IoT-enabled sensors continuing to experience massive growth. Sensors have enhanced the possibility of large-scale IoT deployments in grid systems, vehicles, homes, and so forth. A network that incorporates different embedded systems has the underlying capability of transmitting information and receiving instructions through distributed sensor networks. Sensors are especially essential in gathering different pieces of information that relate to different IoT devices. However, security has become a critical concern for sensor networks that are enabled by the IoT. This is partly because of their design limitations like limited memory, weak processing capability, weak processing ability, and exposure to entities that are malicious. Even more, some ad hoc wireless sensor networks that are enabled by IoT are to some extent also prone to frequent changes in topology. This dynamic aspect tends to aggravate the security issues that are associated with sensors, thus enhancing the need to find a lasting solution. This paper sheds light on the IoT security requirements with special attention to issues related to sensors.

Physical security is essential to safeguarding critical areas. Here, we focus on the physical security problem in three-dimensional (3D) stealthy lattice wireless sensor networks using a 3D sensor belt around a critical space. Specifically, we propose a theoretical framework to investigate the 3D k-barrier coverage problem, where any path crossing this belt intersects with the sensing range of at least k sensors. Precisely, we study this problem from a tiling viewpoint, where the sensing ranges of the sensors are touching (or kissing) each other. We analyze various 3D deterministic sensor deployment methods yielding simple cubic, body centered cubic, face centered cubic, and hexagonal close-packed lattice wireless sensor networks. First, using the concept of the unit cell covered volume ratio, we prove that none of these 3D lattices guarantee k-barrier coverage. Second, to remedy this problem, we consider the great rhombicuboctahedron (GR), a polyhedral space-filler. We introduce the concept of intruder's abstract paths along a 3D k-barrier covered belt, and compute their number. Also, we propose a polynomial representation for all abstract paths. In addition, we compute the number of sensors deployed over a 3D k-barrier covered belt using GR. Third, we corroborate our analysis with numerical and simulation results.

Wireless Sensor Networks (WSN) are gaining popularity as being the backbone of Cyber physical systems, IOT and various data acquisition from sensors deployed in remote, inaccessible terrains have remote deployment. However due to remote deployment, WSN is an adhoc network of large number of sensors either heli-dropped in inaccessible terrain like volcanoes, Forests, border areas are highly energy deficient and available in large numbers. This makes it the right soup to become vulnerable to various kinds of Security attacks. The lack of energy and resources makes it deprived of developing a robust security code for mitigation of various kinds of attacks. Many attempts have been made to suggest a robust security Protocol. But these consume so much energy, bandwidth, processing power, memory and other resources that the sole purpose of data gathering from inaccessible terrain from energy deprived sensors gets defeated. This paper makes an attempt to study the types of attacks on different layers of WSN and the examine the recent trends in development of various security protocols to mitigate the attacks. Further, we have proposed a simple, lightweight but powerful security protocol known as Simple Sensor Security Protocol (SSSP), which captures the uniqueness of WSN and its isolation from internet to develop an energy efficient security solution.

With the continuous improvement of China's scientific and technological level, computer network has become an indispensable part of people's daily life. It can not only effectively improve the efficiency of production and life, and shorten the distance between people, but also further promote the speed of China's social and economic development, which has a positive impact on the realization of China's modernization. Under the new information security demand environment at present, we should pay attention to the related information security work and formulate effective security measures and strategies. In order to effectively prevent these information security problems, people should actively adopt firewall technology, encryption technology, network access control technology and network virus prevention technology for effective protection. This paper analyzes the security problems in the application of wireless sensor networks and explores the mechanism of defending information security, hoping to strengthen the security and stability of wireless sensor networks through effective measures, so that people can better enjoy the convenience brought by the network age.

With the maturity of Internet of things technology, massive data transmission has become the focus of research. In order to solve the problem of low speed of traditional hybrid data fast distribution algorithm for wireless sensor networks, a hybrid data fast distribution algorithm for wireless sensor networks based on visual Internet of things is designed. The logic structure of mixed data input gate in wireless sensor network is designed through the visual Internet of things. The objective function of fast distribution of mixed data in wireless sensor network is proposed. The number of copies of data to be distributed is dynamically calculated and the message deletion strategy is determined. Then the distribution parameters are calibrated, and the fitness ranking is performed according to the distribution quantity to complete the algorithm design. The experimental results show that the distribution rate of the designed algorithm is significantly higher than that of the control group, which can solve the problem of low speed of traditional data fast distribution algorithm.