Biblio

WSNs are extensively used in defence application for monitoring militant activities in various ways in large unknown territories. Here WSNs has to have large set of distributed systems in the form as sensors nodes. Along with security concerns, False Alarming is also a factor which may interrupt the service and downgrade the application further. Thus in our work we have made sure that when a trigger is raised to an event, images can be captured from the connected cameras so that it will be helpful for both auditing the event as well as capturing the scene which led to the triggering of the event.

In the Internet of Things (IoT), it is feasible to interconnect networks of different devices and all these different devices, such as smartphones, sensor devices, and vehicles, are controlled according to a particular user. These different devices are delivered and accept the information on the network. This thing is to motivate us to do work on IoT and the devices used are sensor nodes. The validation of data delivery completely depends on the checks of count data forwarding in each node. In this research, we propose the Link Hop Value-based Intrusion Detection System (L-IDS) against the blackhole attack in the IoT with the assist of WSN. The sensor nodes are connected to other nodes through the wireless link and exchange data routing, as well as data packets. The LHV value is identified as the attacker's presence by integrating the data delivery in each hop. The LHV is always equivalent to the Actual Value (AV). The RPL routing protocol is used IPv6 to address the concept of routing. The Routing procedure is interrupted by an attacker by creating routing loops. The performance of the proposed L-IDS is compared to the RPL routing security scheme based on existing trust. The proposed L-IDS procedure is validating the presence of the attacker at every source to destination data delivery. and also disables the presence of the attacker in the network. Network performance provides better results in the existence of a security scheme and also fully represents the inoperative presence of black hole attackers in the network. Performance metrics show better results in the presence of expected IDS and improve network reliability.

The rapid development of technology makes it possible for a physical machine to be converted into a virtual machine, which can operate multiple operating systems that are running simultaneously and connected to the internet. DoS/DDoS attacks are cyber-attacks that can threaten the telecommunications sector because these attacks cause services to be disrupted and be difficult to access. There are several software tools for monitoring abnormal activities on the network, such as IDS Snort and IDS Suricata. From previous studies, IDS Suricata is superior to IDS Snort version 2 because IDS Suricata already supports multi-threading, while IDS Snort version 2 still only supports single-threading. This paper aims to conduct tests on IDS Snort version 3.0 which already supports multi-threading and IDS Suricata. This research was carried out on a virtual machine with 1 core, 2 core, and 4 core processor settings for CPU, memory, and capture packet attacks on IDS Snort version 3.0 and IDS Suricata. The attack scenario is divided into 2 parts: DoS attack scenario using 1 physical computer, and DDoS attack scenario using 5 physical computers. Based on overall testing, the results are: In general, IDS Snort version 3.0 is better than IDS Suricata. This is based on the results when using a maximum of 4 core processor, in which IDS Snort version 3.0 CPU usage is stable at 55% - 58%, a maximum memory of 3,000 MB, can detect DoS attacks with 27,034,751 packets, and DDoS attacks with 36,919,395 packets. Meanwhile, different results were obtained by IDS Suricata, in which CPU usage is better compared to IDS Snort version 3.0 with only 10% - 40% usage, and a maximum memory of 1,800 MB. However, the capabilities of detecting DoS attacks are smaller with 3,671,305 packets, and DDoS attacks with a total of 7,619,317 packets on a TCP Flood attack test.

In this paper we consider the pollution attack in network coded systems where network nodes are computationally limited. We consider the combined use of cryptographic signature based security and information theoretic network error correction and propose a fountain-like network error correction code construction suitable for this purpose.

This paper explains a novel caching data protection scheme that uses lightweight blockchain and hashchain for information-centric wireless sensor networks. The proposed verification procedure in a Blockchain is conducted based on the proof-of-consensus validation mechanism without using exhaustive mining computations; therefore, our scheme is suitable for resource-shortage wireless and mobile devices. Hashchains are utilized for traceability and signatures that ensure a block's validity. We make a primitive evaluation of the scheme using computer simulations in familiar low-power wide-area wireless environments.

The wireless communication has become very vast, important and easy to access nowadays because of less cost associated and easily available mobile devices. It creates a potential threat for the community while accessing some secure information like banking passwords on the unsecured network. This proposed research work expose such a potential threat such as Rogue Access Point (RAP) detection using soft computing prediction tool. Fuzzy logic is used to implement the proposed model to identify the presence of RAP existence in the network.

Wireless networks are very significant in the present world owing to their widespread use and its application in domains like disaster management, smart cities, IoT etc. A wireless network is made up of a group of wireless nodes that communicate with each other without using any formal infrastructure. The topology of the wireless network is not fixed and it can vary. The huge increase in the number of wireless devices is a challenge owing to the limited availability of wireless spectrum. Opportunistic spectrum access by Cognitive radio enables the efficient usage of limited spectrum resources. The unused channels assigned to the primary users may go waste in idle time. Cognitive radio systems will sense the unused channel space and assigns it temporarily for secondary users. This paper discusses about the recent trends in the two most important aspects of Cognitive radio namely spectrum sensing and security.

This paper introduces an efficient reactive routing protocol considering the mobility and the reliability of a node in Cognitive Radio Sensor Networks (CRSNs). The proposed protocol accommodates the dynamic behavior of the spectrum availability and selects a stable transmission path from a source node to the destination. Outlined as a weighted graph problem, the proposed protocol measures the weight for an edge the measuring the mobility patterns of the nodes and channel availability. Furthermore, the mobility pattern of a node is defined in the proposed routing protocol from the viewpoint of distance, speed, direction, and node's reliability. Besides, the spectrum awareness in the proposed protocol is measured over the number of shared common channels and the channel quality. It is anticipated that the proposed protocol shows efficient routing performance by selecting stable and secured paths from source to destination. Simulation is carried out to assess the performance of the protocol where it is witnessed that the proposed routing protocol outperforms existing ones.

Wireless technology is widely used today and is growing rapidly. One of the wireless technologies is VANET where the network can communicate with vehicles (V2V) which can prevent accidents on the road. Energy is also a problem in VANET so it needs to be used efficiently. The presence of malicious nodes or nodes can eliminate and disrupt the process of data communication. The routing protocol used in this study is AODV. The purpose of this study is to analyze the comparison of blackhole attack and flooding attack against energy-efficient AODV on VANET. This research uses simulation methods and several supporting programs such as OpenStreetMap, SUMO, NS2, NAM, and AWK to test the AODV routing protocol. Quality of service (QOS) parameters used in this study are throughput, packet loss, and end to end delay. Energy parameters are also used to examine the energy efficiency used. This study uses the number of variations of nodes consisting of 20 nodes, 40 nodes, 60 nodes, and different network conditions, namely normal network conditions, network conditions with black hole attacks, and network conditions with flooding attacks. The results obtained can be concluded that the highest value of throughput when network conditions are normal, the greatest value of packet loss when there is a black hole attack, the highest end to end delay value and the largest remaining energy when there is a flooding attack.

We use potential fields tuned by genetic algorithms to dynamically reconFigure unmanned aerial vehicles networks to serve user bandwidth needs. Such flying network base stations have applications in the many domains needing quick temporary networked communications capabilities such as search and rescue in remote areas and security and defense in overwatch and scouting. Starting with an initial deployment that covers an area and discovers how users are distributed across this area of interest, tuned potential fields specify subsequent movement. A genetic algorithm tunes potential field parameters to reposition UAVs to create and maintain a mesh network that maximizes user bandwidth coverage and network lifetime. Results show that our evolutionary adaptive network deployment algorithm outperforms the current state of the art by better repositioning the unmanned aerial vehicles to provide longer coverage lifetimes while serving bandwidth requirements. The parameters found by the genetic algorithm on four training scenarios with different user distributions lead to better performance than achieved by the state of the art. Furthermore, these parameters also lead to superior performance in three never before seen scenarios indicating that our algorithm finds parameter values that generalize to new scenarios with different user distributions.

Wireless Sensor Network (WSN) is a heterogeneous type of network consisting of scattered sensor nodes and working together for data collection, processing, and transmission functions[1], [2]. Because WSN is widely used in vital matters, aspects of its security must also be considered. There are many types of attacks that might be carried out to disrupt WSN networks. The methods of attack that exist in WSN include jamming attack, tampering, Sybil attack, wormhole attack, hello flood attack, and, blackhole attack[3]. Blackhole attacks are one of the most dangerous attacks on WSN networks. Enhanced Check Agent method is designed to detect black hole attacks by sending a checking agent to record nodes that are considered black okay. The implementation will be tested right on a wireless sensor network using ZigBee technology. Network topology uses a mesh where each node can have more than one routing table[4]. The Enhanced Check Agent method can increase throughput to 100 percent.

The present work describes a remote environment monitoring system based on the paradigms of mesh networks and opportunistic networks, whereby a sensor node can explore “con-nectivity windows” to transmit information that will eventually reach another network participants. We discuss the threats to the system's security and propose security mechanisms for the system ensuring the integrity and availability of monitoring information, something identified as critical to its proper operation.

Almost all smart appliances are operated through wireless sensor networks. With the passage of time, due to various applications, the WSN becomes prone to various external attacks. Preventing such attacks, Intrusion Detection strategy (IDS) is very crucial to secure the network from the malicious attackers. The proposed IDS methodology discovers the pattern in large data corpus which works for different types of algorithms to detect four types of Denial of service (DoS) attacks, namely, Grayhole, Blackhole, Flooding, and TDMA. The state-of-the-art detection algorithms, such as KNN, Naïve Bayes, Logistic Regression, Support Vector Machine (SVM), and ANN are applied to the data corpus and analyze the performance in detecting the attacks. The analysis shows that these algorithms are applicable for the detection and prediction of unavoidable attacks and can be recommended for network experts and analysts.

Due to the harsh environment and energy limitation, maintaining efficient communication is crucial to the lifetime of Underwater Sensor Networks (UWSN). Named Data Networking (NDN), one of future network architectures, begins to be applied to UWSN. Although Underwater Named Data Networking (UNDN) performs well in data transmission, it still faces some security threats, such as the Denial-of-Service (DoS) attacks caused by Interest Flooding Attacks (IFAs). In this paper, we present a new type of DoS attacks, named as Synergetic Denial-of-Service (SDoS). Attackers synergize with each other, taking turns to reply to malicious interests as late as possible. SDoS attacks will damage the Pending Interest Table, Content Store, and Forwarding Information Base in routers with high concealment. Simulation results demonstrate that the SDoS attacks quadruple the increased network traffic compared with normal IFAs and the existing IFA detection algorithm in UNDN is completely invalid to SDoS attacks. In addition, we analyze the infection problem in UNDN and propose a defense method Trident based on carefully designed adaptive threshold, burst traffic detection, and attacker identification. Experiment results illustrate that Trident can effectively detect and resist both SDoS attacks and normal IFAs. Meanwhile, Trident can robustly undertake burst traffic and congestion.

Wireless Sensor Networks (WSNs) are applied in environmental monitoring, military surveillance, etc., whereas these applications focuses on providing security for sensed data and the nodes are available for a long time. Hence, we propose DEAVD protocol for secure data exchange with limited usage of energy. The DEAVD protocol compresses data to reduces the energy consumption and implements an energy efficient encryption and decryption technique using voronoi diagram paradigm. Thus, there is an improvement in the proposed protocol with respect to security due to the concept adapted during data encryption and aggregation.

This paper describes a realisation of a ResNet face recognition method through Zigbee-based wireless protocol. The system uses a CC2530 Zigbee-based radio frequency chip with connected VC0706 camera on it. The Arduino Nano had been used for organisation of data compression and effective division of Zigbee packets. The proposed solution also simplifies a data transmission within a strict bandwidth of Zigbee protocol and reliable packet forwarding in case of frequency distortion. The following investigation model uses Raspberry Pi 3 with connected Zigbee End Device (ZED) for successful receiving of important images and acceleration of deep learning interfaces. The model is integrated into a smart security system based on Zigbee modules, MySQL database, Android application and works in the background by using daemons procedures. To protect data, all wireless connections had been encrypted by the 128-bit Advanced Encryption Standard (AES-128) algorithm. Experimental results show a possibility to implement complex systems under restricted requirements of available transmission protocols.

Image Encryption is a technique where an algorithm along with a set of characters called key encrypts the data into cipher text. The cipher text can be converted back into plaintext by decryption. This technique is employed for the security of data such that confidentiality, integrity and authenticity of data is maintained. In today's era security of information has become a crucial task, unauthorized access and use of data has become a noticeable issue. To provide the security required, there are several algorithms to suit the purposes. While the use and transferring of images has become easy and faster due to technological advancements especially wireless sensor network, image destruction and illegitimate use has become a potential threat. Different transfer mediums and various uses of images require different and appropriately suiting encryption approaches. Hence, in this paper we discuss the types of image encryption techniques. We have also discussed several encryption algorithms, their advantages and suitability.

It is necessary to improve the safety of the underwater acoustic sensor networks (UASNs) since it is mostly used in the military industry. Specific emitter identification is the process of identifying different transmitters based on the radio frequency fingerprint extracted from the received signal. The sonar transmitter is a typical low-frequency radiation source and is an important part of the UASNs. Class D power amplifier, a typical nonlinear amplifier, is usually used in sonar transmitters. The inherent nonlinearity of power amplifiers provides fingerprint features that can be distinguished without transmitters for specific emitter recognition. First, the nonlinearity of the sonar transmitter is studied in-depth, and the nonlinearity of the power amplifier is modeled and its nonlinearity characteristics are analyzed. After obtaining the nonlinear model of an amplifier, a similar amplifier in practical application is obtained by changing its model parameters as the research object. The output signals are collected by giving the same input of different models, and, then, the output signals are extracted and classified. In this paper, the memory polynomial model is used to model the amplifier. The power spectrum features of the output signals are extracted as fingerprint features. Then, the dimensionality of the high-dimensional features is reduced. Finally, the classifier is used to recognize the amplifier. The experimental results show that the individual sonar transmitter can be well identified by using the nonlinear characteristics of the signal. By this way, this method can enhance the communication safety of the UASNs.

Voice user interfaces can offer intuitive interaction with our devices, but the usability and audio quality could be further improved if multiple devices could collaborate to provide a distributed voice user interface. To ensure that users' voices are not shared with unauthorized devices, it is however necessary to design an access management system that adapts to the users' needs. Prior work has demonstrated that a combination of audio fingerprinting and fuzzy cryptography yields a robust pairing of devices without sharing the information that they record. However, the robustness of these systems is partially based on the extensive duration of the recordings that are required to obtain the fingerprint. This paper analyzes methods for robust generation of acoustic fingerprints in short periods of time to enable the responsive pairing of devices according to changes in the acoustic scenery and can be integrated into other typical speech processing tools.

Wireless Personal Area Network is widely used in day to day life. It might be a static or dynamic environment. As the density of the nodes increases it becomes difficult to handle the situation. The need of multiple sensor node technology in a desired environment without congestion is required. The use of autonomic network provides one such solution. The autonomicity combines the local automate and address agnostic features that controls the congestion resulting in improved throughput, fault tolerance and also with unicast and multicast packets delivery. The algorithm LA based ANA in a Bluetooth based dynamic environment provide 20% increase in throughput compared with LACAS based Wireless Sensor Network. The LA based ANA leads with 10% lesser fault tolerance levels and extended unicast and multi-cast packet delivery.

Bluetooth Classic (BT) remains the de facto connectivity technology in car stereo systems, wireless headsets, laptops, and a plethora of wearables, especially for applications that require high data rates, such as audio streaming, voice calling, tethering, etc. Unlike in Bluetooth Low Energy (BLE), where address randomization is a feature available to manufactures, BT addresses are not randomized because they are largely believed to be immune to tracking attacks. We analyze the design of BT and devise a robust de-anonymization technique that hinges on the apparently benign information leaking from frame encoding, to infer a piconet's clock, hopping sequence, and ultimately the Upper Address Part (UAP) of the master device's physical address, which are never exchanged in clear. Used together with the Lower Address Part (LAP), which is present in all frames transmitted, this enables tracking of the piconet master, thereby debunking the privacy guarantees of BT. We validate this attack by developing the first Software-defined Radio (SDR) based sniffer that allows full BT spectrum analysis (79 MHz) and implements the proposed de-anonymization technique. We study the feasibility of privacy attacks with multiple testbeds, considering different numbers of devices, traffic regimes, and communication ranges. We demonstrate that it is possible to track BT devices up to 85 meters from the sniffer, and achieve more than 80% device identification accuracy within less than 1 second of sniffing and 100% detection within less than 4 seconds. Lastly, we study the identified privacy attack in the wild, capturing BT traffic at a road junction over 5 days, demonstrating that our system can re-identify hundreds of users and infer their commuting patterns.

Dynamic strain sensing is necessary for high-temperature harsh-environment applications, including powerplants, oil wells, aerospace, and metal manufacturing. Monitoring dynamic strain is important for structural health monitoring and condition-based maintenance in order to guarantee safety, increase process efficiency, and reduce operation and maintenance costs. Sensing in high-temperature (HT), harsh-environments (HE) comes with challenges including mounting and packaging, sensor stability, and data acquisition and processing. Wireless sensor operation at HT is desirable because it reduces the complexity of the sensor connection, increases reliability, and reduces costs. Surface acoustic wave resonators (SAWRs) are compact, can operate wirelessly and battery-free, and have been shown to operate above 1000°C, making them a potential option for HT HE dynamic strain sensing. This paper presents wirelessly interrogated SAWR dynamic strain sensors operating around 288.8MHz at room temperature and tested up to 400°C. The SAWRs were calibrated with a high-temperature wired commercial strain gauge. The sensors were mounted onto a tapered-type Inconel constant stress beam and the assembly was tested inside a box furnace. The SAWR sensitivity to dynamic strain excitation at 25°C, 100°C, and 400°C was .439 μV/με, 0.363μV/με, and .136 μV/με, respectively. The experimental outcomes verified that inductive coupled wirelessly interrogated SAWRs can be successfully used for dynamic strain sensing up to 400°C.

In-Band Full-Duplex (IBFD) Underwater Acoustic (UWA) communication technology plays a major role in enhancing the performance of Underwater acoustic sensor networks (UWSN). Self-Interference (SI) is one of the main inherent challenges affecting the performance of IBFD UWA communication. To reconstruct the SI signal and counteract the SI effect, this is important to estimate the short range channel through which the SI signal passes. Inaccurate estimation will result in the performance degradation of IBFD UWA communication. From the perspective of engineering implementation, we consider that the UWA communication modem shell has a significant influence on the short-range SI channel, which will limit the efficiency of self-interference cancellation in the analog domain to some degree. Therefore we utilize a simplified model to simulate the influence of the structure of the IBFD UWA communication modem on the receiving end. This paper studies the effect of acoustic-shell coupling on near-end self-interference signal of IBFD UWA communication modem. Some suggestions on the design of shell structure of IBFD UWA communication modem are given.

This paper proposes an infrared sensor human target locating system for the Internet of Things. In this design, the wireless sensor network is designed and developed to detect human targets by using 6LoWPAN protocol and pyroelectric infrared (PIR) sensors. Based on the detection data acquired by multiple sensor nodes, K-means++ clustering algorithm combined with cost function is applied to complete human target location in a 10m×10m detection area. The experimental results indicate the human locating system works well and the user can view the location information on the terminal devices.

Low-power wireless network technology is one of the main key characteristics in communication systems that are needed by the Internet of Things (IoT). Nowadays, the 6LoWPAN standard is one of the communication protocols which has been identified as an important protocol in IoT applications. Networking technology in 6LoWPAN transfer IPv6 packets efficiently in link-layer framework that is well-defined by IEEE 802.14.5 protocol. 6Lo WPAN development is still having problems such as threats and entrust crises. The most important part when developing this new technology is the challenge to secure the network. Data security is viewed as a major consideration in this network communications. Many researchers are working to secure 6LoWPAN communication by analyzing the architecture and network features. 6LoWPAN security weakness or vulnerability is exposed to various forms of network attack. In this paper, the security solutions for 6LoWPAN have been investigated. The requirements of safety in 6LoWPAN are also presented.