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Kobayashi, Hiroyuki.  2019.  CEPHEID: the infrastructure-less indoor localization using lighting fixtures' acoustic frequency fingerprints. IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society. 1:6842–6847.
This paper deals with a new indoor localization scheme called “CEPHEID” by using ceiling lighting fixtures. It is based on the fact that each lighting fixture has its own characteristic flickering pattern. Then, the author proposes a technique to identify individual light by using simple instruments and DNN classifier. Thanks to the less requirements for hardware, CEPHEID can be implemented by a few simple discrete electronic components and an ordinary smartphone. A prototype “CEPHEID dongle” is also introduced in this paper. Finally, the validity of the author's method is examined by indoor positioning experiments.
Gauniyal, Rishav, Jain, Sarika.  2019.  IoT Security in Wireless Devices. 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA). :98—102.
IoT is evolving as a combination of interconnected devices over a particular network. In the proposed paper, we discuss about the security of IoT system in the wireless devices. IoT security is the platform in which the connected devices over the network are safeguarded over internet of things framework. Wireless devices play an eminent role in this kind of networks since most of the time they are connected to the internet. Accompanied by major users cannot ensure their end to end security in the IoT environment. However, connecting these devices over the internet via using IoT increases the chance of being prone to the serious issues that may affect the system and its data if they are not protected efficiently. In the proposed paper, the security of IoT in wireless devices will be enhanced by using ECC. Since the issues related to security are becoming common these days, an attempt has been made in this proposed paper to enhance the security of IoT networks by using ECC for wireless devices.
Munsyi, Sudarsono, Amang, Harun Al Rasvid, M. Udin.  2018.  An Implementation of Data Exchange in Environmental Monitoring Using Authenticated Attribute-Based Encryption with Revocation. 2018 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC). :359—366.
Internet of things era grown very rapidly in Industrial Revolution 4.0, there are many researchers use the Wireless Sensor Network (WSN) technology to obtain the data for environmental monitoring. The data obtained from WSN will be sent to the Data Center, where users can view and collect all of data from the Data Center using end devices such as personal computer, laptop, and mobile phone. The Data Center would be very dangerous, because everyone can intercept, track and even modify the data. Security requirement to ensure the confidentiality all of stored data in the data center and give the authenticity in data has not changed during the collection process. Ciphertext Policy Attribute-Based Encryption (CP-ABE) can become a solution to secure the confidentiality for all of data. Only users with appropriate rule of policy can get the original data. To guarantee there is no changes during the collection process of the data then require the time stamp digital signature for securing the data integrity. To protect the confidentiality and data integrity, we propose a security mechanism using CP-ABE with user revocation and Time Stamp Digital Signature using Elliptic Curve Cryptography (ECC) 384 bits. Our system can do the revocation for the users who did the illegal access. Our system is not only securing the data but also providing the guarantee that is no changes during the collection process of the data from the Data Center.
Rudolph, Hendryk, Lan, Tian, Strehl, Konrad, He, Qinwei, Lan, Yuanliang.  2019.  Simulating the Efficiency of Thermoelectrical Generators for Sensor Nodes. 2019 4th IEEE Workshop on the Electronic Grid (eGRID). :1—6.

In order to be more environmentally friendly, a lot of parts and aspects of life become electrified to reduce the usage of fossil fuels. This can be seen in the increased number of electrical vehicles in everyday life. This of course only makes a positive impact on the environment, if the electricity is produced environmentally friendly and comes from renewable sources. But when the green electrical power is produced, it still needs to be transported to where it's needed, which is not necessarily near the production site. In China, one of the ways to do this transport is to use High Voltage Direct Current (HVDC) technology. This of course means, that the current has to be converted to DC before being transported to the end user. That implies that the converter stations are of great importance for the grid security. Therefore, a precise monitoring of the stations is necessary. Ideally, this could be accomplished with wireless sensor nodes with an autarkic energy supply. A role in this energy supply could be played by a thermoelectrical generator (TEG). But to assess the power generated in the specific environment, a simulation would be highly desirable, to evaluate the power gained from the temperature difference in the converter station. This paper proposes a method to simulate the generated power by combining a model for the generator with a Computational Fluid Dynamics (CFD) model converter.

Maria Verzegnassi, Enrico Giulio, Tountas, Konstantinos, Pados, Dimitris A., Cuomo, Francesca.  2019.  Data Conformity Evaluation: A Novel Approach for IoT Security. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT). :842—846.

We consider the problem of attack detection for IoT networks based only on passively collected network parameters. For the first time in the literature, we develop a blind attack detection method based on data conformity evaluation. Network parameters collected passively, are converted to their conformity values through iterative projections on refined L1-norm tensor subspaces. We demonstrate our algorithmic development in a case study for a simulated star topology network. Type of attack, affected devices, as well as, attack time frame can be easily identified.

Chen, Yanping, Ma, Long, Xia, Hong, Gao, Cong, Wang, Zhongmin, Yu, Zhong.  2019.  Trust-Based Distributed Kalman Filter Estimation Fusion under Malicious Cyber Attacks. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). :2255—2260.

We consider distributed Kalman filter for dynamic state estimation over wireless sensor networks. It is promising but challenging when network is under cyber attacks. Since the information exchange between nodes, the malicious attacks quickly spread across the entire network, which causing large measurement errors and even to the collapse of sensor networks. Aiming at the malicious network attack, a trust-based distributed processing frame is proposed. Which allows neighbor nodes to exchange information, and a series of trusted nodes are found using truth discovery. As a demonstration, distributed Cooperative Localization is considered, and numerical results are provided to evaluate the performance of the proposed approach by considering random, false data injection and replay attacks.

Zhang, Suman, Qin, Cai, Wang, Chaowei, Wang, Weidong, Zhang, Yinghai.  2018.  Slot Assignment Algorithm Based on Hash Function for Multi-target RFID System. 2018 IEEE/CIC International Conference on Communications in China (ICCC). :583—587.

Multi-tag identification technique has been applied widely in the RFID system to increase flexibility of the system. However, it also brings serious tags collision issues, which demands the efficient anti-collision schemes. In this paper, we propose a Multi-target tags assignment slots algorithm based on Hash function (MTSH) for efficient multi-tag identification. The proposed algorithm can estimate the number of tags and dynamically adjust the frame length. Specifically, according to the number of tags, the proposed algorithm is composed of two cases. when the number of tags is small, a hash function is constructed to map the tags into corresponding slots. When the number of tags is large, the tags are grouped and randomly mapped into slots. During the tag identification, tags will be paired with a certain matching rate and then some tags will exit to improve the efficiency of the system. The simulation results indicate that the proposed algorithm outperforms the traditional anti-collision algorithms in terms of the system throughput, stability and identification efficiency.

Tsiota, Anastasia, Xenakis, Dionysis, Passas, Nikos, Merakos, Lazaros.  2019.  Multi-Tier and Multi-Band Heterogeneous Wireless Networks with Black Hole Attacks. 2019 IEEE Global Communications Conference (GLOBECOM). :1—6.

Wireless networks are currently proliferated by multiple tiers and heterogeneous networking equipment that aims to support multifarious services ranging from distant monitoring and control of wireless sensors to immersive virtual reality services. The vast collection of heterogeneous network equipment with divergent radio capabilities (e.g. multi-GHz operation) is vulnerable to wireless network attacks, raising questions on the service availability and coverage performance of future multi-tier wireless networks. In this paper, we study the impact of black hole attacks on service coverage of multi-tier heterogeneous wireless networks and derive closed form expressions when network nodes are unable to identify and avoid black hole nodes. Assuming access to multiple bands, the derived expressions can be readily used to assess the performance gains following from the employment of different association policies and the impact of black hole attacks in multi-tier wireless networks.

Pruthi, Vardaan, Mittal, Kanika, Sharma, Nikhil, Kaushik, Ila.  2019.  Network Layers Threats its Countermeasures in WSNs. 2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS). :156—163.

WSN can be termed as a collection of dimensionally diffused nodes which are capable of surveilling and analyzing their surroundings. The sensors are delicate, transportable and small in size while being economical at the same time. However, the diffused nature of these networks also exposes them to a variety of security hazards. Hence, ensuring a reliable file exchange in these networks is not an easy job due to various security requirements that must be fulfilled. In this paper we concentrate mainly on network layer threats and their security countermeasures to overcome the scope of intruders to access the information without having any authentication on the network layer. Various network layer intrusions that are discussed here include Sinkhole Attack, Sybil Attack, Wormhole Attack, Selective Forwarding Attack, Blackhole Attack And Hello Flood Attack.

Kaushik, Ila, Sharma, Nikhil, Singh, Nanhay.  2019.  Intrusion Detection and Security System for Blackhole Attack. 2019 2nd International Conference on Signal Processing and Communication (ICSPC). :320—324.

Communication is considered as an essential part of our lives. Different medium was used for exchange of information, but due to advancement in field of technology, different network setup came into existence. One of the most suited in wireless field is Wireless Sensor Network (WSN). These networks are set up by self-organizing nodes which operate over radio environment. Since communication is done more rapidly, they are confined to many attacks which operate at different layers. In order to have efficient communication, some security measure must be introduced in the network ho have secure communication. In this paper, we describe various attacks functioning at different layers also one of the common network layer attack called Blackhole Attack with its mitigation technique using Intrusion Detection System (IDS) over network simulator ns2 has been discussed.

Dhas, Y. Justin, Jeyanthi, P..  2019.  A Review on Internet of Things Protocol and Service Oriented Middleware. 2019 International Conference on Communication and Signal Processing (ICCSP). :0104–0108.
This paper surveys a review of Internet of Things (IoT) protocols, Service oriented Middleware in IoT. The modern development of IoT, expected to create many divorce application in health care without human intervention. Various protocols are involved in the applications development. Researchers are doing research for desirable protocol with all functionalities. Middleware for an IoT provides interoperability between the devices or applications. The engineering of an IoT dependent on Service Oriented Architecture (SOA), it operates as middleware. We survey the existing SOA based IoT middleware and its functionalities.
Ansari, Abdul Malik, Hussain, Muzzammil.  2018.  Middleware Based Node Authentication Framework for IoT Networks. 2018 International Conference on Inventive Research in Computing Applications (ICIRCA). :31–35.
Security and protection are among the most squeezing worries that have developed with the Internet. As systems extended and turned out to be more open, security hones moved to guarantee insurance of the consistently developing Internet, its clients, and information. Today, the Internet of Things (IoT) is rising as another sort of system that associates everything to everybody, all over. Subsequently, the edge of resistance for security and protection moves toward becoming smaller on the grounds that a break may prompt vast scale irreversible harm. One element that eases the security concerns is validation. While diverse confirmation plans are utilized as a part of vertical system storehouses, a typical personality and validation plot is expected to address the heterogeneity in IoT and to coordinate the distinctive conventions exhibit in IoT. In this paper, a light weight secure framework is proposed. The proposed framework is analyzed for performance with security mechanism and found to be better over critical parameters.
Alshinina, Remah, Elleithy, Khaled.  2018.  A highly accurate machine learning approach for developing wireless sensor network middleware. 2018 Wireless Telecommunications Symposium (WTS). :1–7.
Despite the popularity of wireless sensor networks (WSNs) in a wide range of applications, security problems associated with them have not been completely resolved. Middleware is generally introduced as an intermediate layer between WSNs and the end user to resolve some limitations, but most of the existing middleware is unable to protect data from malicious and unknown attacks during transmission. This paper introduces an intelligent middleware based on an unsupervised learning technique called Generative Adversarial Networks (GANs) algorithm. GANs contain two networks: a generator (G) network and a detector (D) network. The G creates fake data similar to the real samples and combines it with real data from the sensors to confuse the attacker. The D contains multi-layers that have the ability to differentiate between real and fake data. The output intended for this algorithm shows an actual interpretation of the data that is securely communicated through the WSN. The framework is implemented in Python with experiments performed using Keras. Results illustrate that the suggested algorithm not only improves the accuracy of the data but also enhances its security by protecting data from adversaries. Data transmission from the WSN to the end user then becomes much more secure and accurate compared to conventional techniques.
Lebiednik, Brian, Abadal, Sergi, Kwon, Hyoukjun, Krishna, Tushar.  2018.  Architecting a Secure Wireless Network-on-Chip. 2018 Twelfth IEEE/ACM International Symposium on Networks-on-Chip (NOCS). :1—8.
With increasing integration in SoCs, the Network-on-Chip (NoC) connecting cores and accelerators is of paramount importance to provide low-latency and high-throughput communication. Due to limits to scaling of electrical wires in terms of energy and delay, especially for long multi-mm distances on-chip, alternate technologies such as Wireless Network-on-Chip (WNoC) have shown promise. WNoCs can provide low-latency one-hop broadcasts across the entire chip and can augment point-to-point multi-hop signaling over traditional wired NoCs. Thus, there has been a recent surge in research demonstrating the performance and energy benefits of WNoCs. However, little to no work has studied the additional security and fault tolerance challenges that are unique to WNoCs. In this work, we study potential threats related to denial-of-service, spoofing, and eavesdropping attacks in WNoCs, due to malicious hardware trojans or faulty wireless components. We introduce Prometheus, a dropin solution inside the network interface that provides protection from all three attacks, while adhering to the strict area, power and latency constraints of on-chip systems.
Chandre, Pankaj Ramchandra, Mahalle, Parikshit Narendra, Shinde, Gitanjali Rahul.  2018.  Machine Learning Based Novel Approach for Intrusion Detection and Prevention System: A Tool Based Verification. 2018 IEEE Global Conference on Wireless Computing and Networking (GCWCN). :135–140.
Now a day, Wireless Sensor Networks are widely used in military applications by its applications, it is extended to healthcare, industrial environments and many more. As we know that, there are some unique features of WSNs such as limited power supply, minimum bandwidth and limited energy. So, to secure traditional network, multiple techniques are available, but we can't use same techniques to secure WSNs. So to increase the overall security of WSNs, we required new ideas as well as new approaches. In general, intrusion prevention is the primary issue in WSNs and intrusion detection already reached to saturation. Thus, we need an efficient solution for proactive intrusion prevention towards WSNs. Thus, formal validation of protocols in WSN is an essential area of research. This research paper aims to formally verify as well as model some protocol used for intrusion detection using AVISPA tool and HLPSL language. In this research paper, the results of authentication and DoS attacks were detected is presented, but there is a need to prevent such type of attacks. In this research paper, a system is proposed in order to avoid intrusion using machine learning for the wireless sensor network. So, the proposed system will be used for intrusion prevention in a wireless sensor network.
Vashist, Abhishek, Keats, Andrew, Pudukotai Dinakarrao, Sai Manoj, Ganguly, Amlan.  2019.  Securing a Wireless Network-on-Chip Against Jamming Based Denial-of-Service Attacks. 2019 IEEE Computer Society Annual Symposium on VLSI (ISVLSI). :320–325.
Wireless Networks-on-Chips (NoCs) have emerged as a panacea to the non-scalable multi-hop data transmission paths in traditional wired NoC architectures. Using low-power transceivers in NoC switches, novel Wireless NoC (WiNoC) architectures have been shown to achieve higher energy efficiency with improved peak bandwidth and reduced on-chip data transfer latency. However, using wireless interconnects for data transfer within a chip makes the on-chip communications vulnerable to various security threats from either external attackers or internal hardware Trojans (HTs). In this work, we propose a mechanism to make the wireless communication in a WiNoC secure against persistent jamming based Denial-of-Service attacks from both external and internal attackers. Persistent jamming attacks on the on-chip wireless medium will cause interference in data transfer over the duration of the attack resulting in errors in contiguous bits, known as burst errors. Therefore, we use a burst error correction code to monitor the rate of burst errors received over the wireless medium and deploy a Machine Learning (ML) classifier to detect the persistent jamming attack and distinguish it from random burst errors. In the event of jamming attack, alternate routing strategies are proposed to avoid the DoS attack over the wireless medium, so that a secure data transfer can be sustained even in the presence of jamming. We evaluate the proposed technique on a secure WiNoC in the presence of DoS attacks. It has been observed that with the proposed defense mechanisms, WiNoC can outperform a wired NoC even in presence of attacks in terms of performance and security. On an average, 99.87% attack detection was achieved with the chosen ML Classifiers. A bandwidth degradation of \textbackslashtextless;3% is experienced in the event of internal attack, while the wireless interconnects are disabled in the presence of an external attacker.
Shen, Weiguo, Wang, Wei.  2018.  Node Identification in Wireless Network Based on Convolutional Neural Network. 2018 14th International Conference on Computational Intelligence and Security (CIS). :238—241.
Aiming at the problem of node identification in wireless networks, a method of node identification based on deep learning is proposed, which starts with the tiny features of nodes in radiofrequency layer. Firstly, in order to cut down the computational complexity, Principal Component Analysis is used to reduce the dimension of node sample data. Secondly, a convolution neural network containing two hidden layers is designed to extract local features of the preprocessed data. Stochastic gradient descent method is used to optimize the parameters, and the Softmax Model is used to determine the output label. Finally, the effectiveness of the method is verified by experiments on practical wireless ad-hoc network.
Zhang, Lichen.  2018.  Modeling Cloud Based Cyber Physical Systems Based on AADL. 2018 24th International Conference on Automation and Computing (ICAC). :1—6.

Cloud-based cyber-physical systems, like vehicle and intelligent transportation systems, are now attracting much more attentions. These systems usually include large-scale distributed sensor networks covering various components and producing enormous measurement data. Lots of modeling languages are put to use for describing cyber-physical systems or its aspects, bringing contribution to the development of cyber-physical systems. But most of the modeling techniques only focuse on software aspect so that they could not exactly express the whole cloud-based cyber-physical systems, which require appropriate views and tools in its design; but those tools are hard to be used under systemic or object-oriented methods. For example, the widest used modeling language, UML, could not fulfil the above design's requirements by using the foremer's standard form. This paper presents a method designing the cloud-based cyber-physical systems with AADL, by which we can analyse, model and apply those requirements on cloud platforms ensuring QoS in a relatively highly extensible way at the mean time.

Wang, Chong Xiao, Song, Yang, Tay, Wee Peng.  2018.  PRESERVING PARAMETER PRIVACY IN SENSOR NETWORKS. 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP). :1316–1320.
We consider the problem of preserving the privacy of a set of private parameters while allowing inference of a set of public parameters based on observations from sensors in a network. We assume that the public and private parameters are correlated with the sensor observations via a linear model. We define the utility loss and privacy gain functions based on the Cramér-Rao lower bounds for estimating the public and private parameters, respectively. Our goal is to minimize the utility loss while ensuring that the privacy gain is no less than a predefined privacy gain threshold, by allowing each sensor to perturb its own observation before sending it to the fusion center. We propose methods to determine the amount of noise each sensor needs to add to its observation under the cases where prior information is available or unavailable.
Wang, Chong Xiao, Song, Yang, Tay, Wee Peng.  2018.  PRESERVING PARAMETER PRIVACY IN SENSOR NETWORKS. 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP). :1316–1320.
We consider the problem of preserving the privacy of a set of private parameters while allowing inference of a set of public parameters based on observations from sensors in a network. We assume that the public and private parameters are correlated with the sensor observations via a linear model. We define the utility loss and privacy gain functions based on the Cramér-Rao lower bounds for estimating the public and private parameters, respectively. Our goal is to minimize the utility loss while ensuring that the privacy gain is no less than a predefined privacy gain threshold, by allowing each sensor to perturb its own observation before sending it to the fusion center. We propose methods to determine the amount of noise each sensor needs to add to its observation under the cases where prior information is available or unavailable.
Srinu, Sesham, Reddy, M. Kranthi Kumar, Temaneh-Nyah, Clement.  2019.  Physical layer security against cooperative anomaly attack using bivariate data in distributed CRNs. 2019 11th International Conference on Communication Systems Networks (COMSNETS). :410—413.
Wireless communication network (WCN) performance is primarily depends on physical layer security which is critical among all other layers of OSI network model. It is typically prone to anomaly/malicious user's attacks owing to openness of wireless channels. Cognitive radio networking (CRN) is a recently emerged wireless technology that is having numerous security challenges because of its unlicensed access of wireless channels. In CRNs, the security issues occur mainly during spectrum sensing and is more pronounced during distributed spectrum sensing. In recent past, various anomaly effects are modelled and developed detectors by applying advanced statistical techniques. Nevertheless, many of these detectors have been developed based on sensing data of one variable (energy measurement) and degrades their performance drastically when the data is contaminated with multiple anomaly nodes, that attack the network cooperatively. Hence, one has to develop an efficient multiple anomaly detection algorithm to eliminate all possible cooperative attacks. To achieve this, in this work, the impact of anomaly on detection probability is verified beforehand in developing an efficient algorithm using bivariate data to detect possible attacks with mahalanobis distance measure. Result discloses that detection error of cooperative attacks by anomaly has significant impact on eigenvalue-based sensing.
Demir, Mehmet özgÜn, Kurty, GÜne Karabulut, Dartmannz, Guido, Ascheidx, Gerd, Pusane, Ali Emre.  2018.  Security Analysis of Forward Error Correction Codes in Relay Aided Networks. 2018 Global Information Infrastructure and Networking Symposium (GIIS). :1–5.

Network security and data confidentiality of transmitted information are among the non-functional requirements of industrial wireless sensor networks (IWSNs) in addition to latency, reliability and energy efficiency requirements. Physical layer security techniques are promising solutions to assist cryptographic methods in the presence of an eavesdropper in IWSN setups. In this paper, we propose a physical layer security scheme, which is based on both insertion of an random error vector to forward error correction (FEC) codewords and transmission over decentralized relay nodes. Reed-Solomon and Golay codes are selected as FEC coding schemes and the security performance of the proposed model is evaluated with the aid of decoding error probability of an eavesdropper. The results show that security level is highly based on the location of the eavesdropper and secure communication can be achieved when some of channels between eavesdropper and relay nodes are significantly noisier.

Wang, Zhi-Hao, Kung, Yu-Fan, Hendrick, Cheng, Po-Jen, Wang, Chih-Min, Jong, Gwo-Jia.  2018.  Enhance Wireless Security System Using Butterfly Network Coding Algorithm. 2018 International Conference on Applied Information Technology and Innovation (ICAITI). :135–138.
The traditional security system requires a lot of manpower, and the wireless security system has been developed to reduce costs. However, for wireless systems, stability and reliability are important system indicators. In order to effectively improve these two indicators, we have imported butterfly network coding algorithm into the wireless sensing network. Because this algorithm enables each node to play multiple roles, such as routing, encoding, decoding, sending and receiving, it can also improve the throughput of network transmission, and effectively improve the stability and reliability of the wireless security system. This paper used the Wi-Fi module to implement the butterfly network coding algorithm, and is actually installed in the building. The basis for transmission and reception of all nodes in the network is received signal strength indication (RSSI). On the other hand, this is an IoT system for security monitoring.
Hirose, Shoichi, Shikata, Junji.  2019.  Provable Security of the Ma-Tsudik Forward-Secure Sequential Aggregate MAC Scheme. 2019 Seventh International Symposium on Computing and Networking Workshops (CANDARW). :327—332.
Considering application to communication among wireless sensors, Ma and Tsudik introduced the notion of forward-secure sequential aggregate (FssAgg) authentication in 2007. They also proposed an FssAgg MAC scheme composed of a MAC function and cryptographic hash functions at the same time. The security of their proposed scheme has not been analyzed yet and remains open. It is shown in this paper that a slight variant of the Ma-Tsudik FssAgg MAC scheme is secure under reasonable and standard assumptions on security of the underlying primitives. An efficient instantiation of the underlying MAC function using a cryptographic hash function is also discussed.
Nandi, Giann Spilere, Pereira, David, Vigil, Martín, Moraes, Ricardo, Morales, Analúcia Schiaffino, Araújo, Gustavo.  2019.  Security in Wireless Sensor Networks: A formal verification of protocols. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). 1:425—431.

The increase of the digitalization taking place in various industrial domains is leading developers towards the design and implementation of more and more complex networked control systems (NCS) supported by Wireless Sensor Networks (WSN). This naturally raises new challenges for the current WSN technology, namely in what concerns improved guarantees of technical aspects such as real-time communications together with safe and secure transmissions. Notably, in what concerns security aspects, several cryptographic protocols have been proposed. Since the design of these protocols is usually error-prone, security breaches can still be exposed and MALICIOUSly exploited unless they are rigorously analyzed and verified. In this paper we formally verify, using ProVerif, three cryptographic protocols used in WSN, regarding the security properties of secrecy and authenticity. The security analysis performed in this paper is more robust than the ones performed in related work. Our contributions involve analyzing protocols that were modeled considering an unbounded number of participants and actions, and also the use of a hierarchical system to classify the authenticity results. Our verification shows that the three analyzed protocols guarantee secrecy, but can only provide authenticity in specific scenarios.