Secure neighbor discovery in wireless sensor networks using range-free localization techniques

Si una red inalámbrica de sensores se implementa en un entorno hostil, las limitaciones intrínsecas a los nodos conllevan muchos problemas de seguridad. En este artículo se aborda un ataque particular a los protocolos de localización y descubrimiento de vecinos, llevada a cabo por dos nodos que actúan en connivencia y establecen un "agujero de gusano" para tratar de engañar a un nodo aislado, haciéndole creer que se encuentra en la vecindad de un conjunto de nodos locales. Para contrarrestar este tipo de amenazas, se presenta un marco de actuación genéricamente denominado "detection of wormhole attacks using range-free methods" (DWARF) dentro del cual derivamos dos estrategias para de detección de agujeros de gusano: el primer enfoque (DWARFLoc) realiza conjuntamente la localización y la detección de ataques, mientras que el otro (DWARFTest) valida la posición estimada por el nodo una vez finalizado el protocolo de localización. Las simulaciones muestran que ambas estrategias son eficaces en la detección de ataques tipo "agujero de gusano", y sus prestaciones se comparan con las de un test convencional basado en la razón de verosimilitudes

A distance vector hop-based secure and robust localization algorithm for wireless sensor networks

Location information of sensor nodes in a wireless sensor network is important. The sensor nodes are usually required to ascertain their positions so that the data collected by these nodes can be labeled with this information. On the other hand, certain attacks on wireless sensor networks lead to the incorrect estimation of sensor node positions. In such situations, when the location information is not correct, the data may be labeled with wrong location information that may subvert the desired operation of the wireless sensor network. In this work, we formulate and propose a distance vector hop-based algorithm to provide secure and robust localization in the presence of malicious sensor nodes that result in incorrect position estimation and jeopardize the wireless sensor network operation. The algorithm uses cryptography to ensure secure and robust operation in the presence of adversaries in the sensor network. As a result of the countermeasures, the attacks are neutralized and the sensor nodes are able to estimate their positions as desired. Our secure localization algorithm provides a defense against various types of security attacks, such as selective forwarding, wormhole, Sybil, tampering, and traffic replay, compared with other algorithms which provide security against only one or two types. Simulation experiments are performed to evaluate the performance of the proposed method, and the results indicate that our secure localization algorithm achieves the design objectives successfully. Performance of the proposed method is also compared with the performance of basic distance vector hop algorithm and two secure algorithms based on distance vector hop localization. The results reveal that our proposed secure localization algorithm outperforms the compared algorithms in the presence of multiple attacks by malicious nodes

Localization Against Wormhole Attacks in Wireless Sensor Networks

In the last decade, wireless sensor networks deployed at an accelerated pace in military, industrial, healthcare etc. fields but that were originally developed in the late 1960s and 1970s. Navigation or localization is an intuitive important because it can help in reducing the complexity of energy efficient algorithm, target tracking, routing protocol and data collection/aggregation algorithm in wireless sensor networks (WSNs). Localization has an important role in both network application domains and services; for example geographical routing. Due to self configuring nature of WSNs, it mainly deployed in a hostile environment, and hence it can be easily threatened by internal or external attack. Therefore, localization and security are essential issues in WSNs. We know that ’Wormhole Attack’ is a severe security threat where two malicious colluding sensor nodes create a virtual tunnel to WSNs. Detection and prevention of wormhole attacks in WSNs are a considerably challenging task because of its independence of MAC protocols and immunity to cryptology techniques. Around all the existing defenses have required some additional hardware requirements on the network or strong assumptions; that’s may not have perfect applicability in real environment. Our main objectives are to find the location of wormhole attackers as well as the location of sensor nodes in a wireless network system. In our schemes, we consider the three types of nodes : locators, attackers and sensors in the network and makes a conflicting set matrix on the basis of abnormal behavior of message exchanging among neighboring locators, which helps in differentiation between valid locators and dubious locators. We evaluate location estimation results through simulations in our last section

Security and Privacy for Modern Wireless Communication Systems

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

Secure Geo-location Techniques using Trusted Hyper-visor

Για πολλούς, η γεωγραφική θέση είναι μια απλή διαδικασία όπου με τη χρήση του GPS ένα άτομο μπορεί να εντοπιστεί όπου και όποτε ζητείται. Ωστόσο, ακόμη και αν η χρήση του GPS για γεωγραφική τοποθέτηση είναι ο πιο συνηθισμένος τρόπος και ταυτόχρονα ακριβής ως σύστημα, αποτελεί μια τεράστια κατανάλωση ενέργειας για να επιτευχθεί αυτή η διαδικασία και υστερεί σε μηχανισμούς και τεχνικές ασφαλείας. Σκοπός αυτής της εργασίας είναι να παρουσιάσουμε μια άλλη όψη για το πώς μπορούμε να εντοπίσουμε μια άγνωστη θέση ενός κόμβου σε ένα σύστημα και πώς θα μπορούσε να δημιουργηθεί ένα ασφαλές περιβάλλον για αυτόν τον κόμβο. Βασική μας ιδέα ήταν η δημιουργία ενός μηχανισμού όπου θα μπορούσαμε να δημιουργήσουμε ένα τρισδιάστατο πεδίο στο οποίο θα μπορούσε να εντοπιστεί άγνωστος κόμβος και στη συνέχεια θα δημιουργηθεί ένα ασφαλές περιβάλλον για τον νέο κόμβο. Μετά από μια έρευνα σε δημοσιεύσεις σχετικά με τρισδιάστατους μηχανισμούς και τεχνικές γεω-εντοπισμού, παράλληλα με την έννοια των hypervisors για τη δημιουργία ασφαλούς περιβάλλοντος με την αξιοποίηση της κρυπτογραφίας, καταλήξαμε στο συμπέρασμα της δημιουργίας ενός πλαισίου που θα ικανοποιούσε αυτά απαιτήσεις. Δημιουργήσαμε ένα τρισδιάστατο πεδίο τεσσάρων σταθμών κόμβων, όπου χρησιμοποιήσαμε δύο αλγορίθμους εντοπισμού, χωρίς GPS, για τον εντοπισμό της θέση ενός πέμπτου άγνωστου κόμβου παράλληλα με έναν hypervisor για τη δημιουργία περιβάλλοντος εμπιστοσύνης. Χρησιμοποιήσαμε ένα TPM για τη δημιουργία κρυπτογραφικών μηχανισμών και κλειδιών ασφαλείας. Σε αυτή την εργασία δημιουργήσαμε μια προσομοίωση όπου συγκρίνουμε την απόδοση αυτών των δύο αλγορίθμων γεωγραφικής τοποθέτησης από την άποψη της ταχύτητας και της ακρίβειας του υπολογισμού, παράλληλα με την απόδοση των μηχανισμών ασφαλείας του hypervisor και την ικανότητά του για ασφάλιση ακεραιότητας δεδομένων. Εκτός από τα συστατικά του προτεινόμενου μηχανισμού, παρουσιάζουμε και άλλες πληροφορίες που βρήκαμε σε σχετικά έγγραφα, όπως μια ποικιλία από hypervisors και μια ποικιλία τεχνικών εντοπισμού, για περισσότερες πληροφορίες για μελλοντικές εργασίες παράλληλα με τα βήματα υλοποίησης και εκτέλεσης.For many, geo-location is a simple process where with the utilization of GPS a person can be located wherever and whenever is requested. However, even if the utilization of GPS for geolocation is the most common way and accurate as a system, it is a huge consumption of energy in order to achieve this process and it lucks on safety mechanisms and techniques. The purpose of this paper is to present another view of how we could locate an unknown node position in a system and how a safe environment could be created for this node. Our main idea was about the creation of a framework where we could create a three-dimensional field in which an unknown node could be located and afterwards a safe environment would be created for the new node. After a research on papers relevant with three-dimensional geo-localization mechanisms and techniques, alongside with the concept of hypervisors for the creation of safe environment with the utilization of cryptography, we came to the conclusion of the creation of a framework which would satisfy those requirements. We created a 3-Dimentional field of four base nodes stations, where we utilized two localization GPS-free algorithms for the location of a fifth unknown node alongside with a hypervisor for the trust environment creation. We utilized a TPM for the cryptography mechanisms and safety keys creation. In this paper we created a simulation where we compare the performance of those two geolocation algorithms in terms of accuracy and computation speed and accuracy, alongside with the hypervisor’s security mechanisms performance and its ability for data integrity insurance. Except our proposed framework components, we present also further information that we found in relevant papers, such as a variety of hypervisors and a variety of localization techniques, for more information for future work alongside with implementation steps and guidanc

Fast, Reliable, and Secure Drone Communication: A Comprehensive Survey

Drone security is currently a major topic of discussion among researchers and industrialists. Although there are multiple applications of drones, if the security challenges are not anticipated and required architectural changes are not made, the upcoming drone applications will not be able to serve their actual purpose. Therefore, in this paper, we present a detailed review of the security-critical drone applications, and security-related challenges in drone communication such as DoS attacks, Man-in-the-middle attacks, De-Authentication attacks, and so on. Furthermore, as part of solution architectures, the use of Blockchain, Software Defined Networks (SDN), Machine Learning, and Fog/Edge computing are discussed as these are the most emerging technologies. Drones are highly resource-constrained devices and therefore it is not possible to deploy heavy security algorithms on board. Blockchain can be used to cryptographically store all the data that is sent to/from the drones, thereby saving it from tampering and eavesdropping. Various ML algorithms can be used to detect malicious drones in the network and to detect safe routes. Additionally, the SDN technology can be used to make the drone network reliable by allowing the controller to keep a close check on data traffic, and fog computing can be used to keep the computation capabilities closer to the drones without overloading them.The work of Vinay Chamola and Fei Richard Yu was supported in part by the SICI SICRG Grant through the Project Artificial Intelligence Enabled Security Provisioning and Vehicular Vision Innovations for Autonomous Vehicles, and in part by the Government of Canada's National Crime Prevention Strategy and Natural Sciences and Engineering Research Council of Canada (NSERC) CREATE Program for Building Trust in Connected and Autonomous Vehicles (TrustCAV)