With the emergence of new and exciting wireless technologies and capabilities, Unmanned Aerial Vehicles (uavs) and the services they allow, stand to be a major influencer in our daily lives. Unfortunately, they are also prone to a plethora of security issues. Existing studies propose both prevention and identification schemes for various routing attacks. They do not, however, preclude future malicious attempts. Hence, in this work we identify the specific uav that is compromising the network, with the specific purpose of flushing it out. The proposed solution combines secret sharing and cheating identification schemes with multi-path routing protocols, to deterministically pinpoint the compromised node that is cheating the uav flock. It assures a quiet identification of the adversary creating new opportunities for its attack, even when facing a sophisticated adversary that selectively modifies data messages or re-routes them in within the network. We took special care to allow for applicability in existing networks by adhering to two basic principles: only using pre-existing standard routing protocols and not relying on a centralized or trusted third party node such as a base station. All information must be gleaned by each node using only primitives which already exist in the underlying communication protocols. We provide a rigorous mathematical proof of the cost bounds, and run simulations to prove feasibility. Moreover, the simulations show a 100% detection rate and message delivery rate. The communication overhead varies, on average, between 0.4∙106-0.8∙106 bytes, depending on various parameters such as the network size and the reception rate of network nodes. The time required varies between 0.2-0.4 seconds, depending mainly on the network size.

The proliferation of the Internet of Things (IoT) has reshaped the way we interact with technology, propelling the Routing Protocol for Low-Power and Lossy Networks (RPL) into a critical role as a communication framework. Amid this transformative landscape, security vulnerabilities within RPL-based IoT networks emerge as a substantial concern. This survey delves into these vulnerabilities, offering insights into their intricacies, potential consequences, and robust mitigation strategies. Commencing with a foundational understanding of IoT networks and their real-world applications, the survey sets the stage for comprehending the significance of Routing Protocol for Low-Power and Lossy Networks (RPL). It unravels the unique characteristics of RPL networks, their Destination-Oriented Directed Acyclic Graph (DODAG) topologies, and their pivotal role in enabling seamless device communication. The survey then delves into the heart of RPL security vulnerabilities. It navigates through diverse attack vectors, such as rank attacks and version number attacks. Each vulnerability is scrutinized, unraveling its technical mechanisms and implications for network stability. Transitioning from vulnerabilities to resilience, the survey offers a panoramic view of mitigation strategies. It dissects the nuances of intrusion detection systems (IDS), exploring trust models, location-based approaches, and hybrid systems. Signature-based, anomaly-based, and specification-based detection mechanisms are evaluated for their potential to mitigate threats within RPL networks. As standards shape the IoT landscape, the survey underscores the pivotal role of RPL within this framework. It emphasizes the necessity of secure standards in mitigating vulnerabilities across interconnected IoT devices.

Cyber-threat protection is one of the most challenging research branches of Internet-of-Things ( i o t ). With the exponential increase of tiny connected devices, the battle between friend and foe intensifies. Unfortunately, i o t devices offer very limited security features, laying themselves wide open to new attacks, inhibiting the expected global adoption of i o t technologies. Moreover, existing prevention and mitigation techniques and intrusion detection systems handle attack anomalies rather than the attack itself while using a significant amount of the network resources. rpl , the de-facto routing protocol for i o t , proposes minimal security features that cannot handle internal attacks. Hence, in this paper, we propose sprinkler , which identifies the specific thing that is under attack by an adversarial Man-in-The-Middle. sprinkler uses the multi-instance feature of rpl to identify the adversary. The proposed solution adheres to two basic principles: it only uses pre-existing standard routing protocols and does not rely on a centralized or trusted third-party node such as a certificate authority. All information must be gleaned by each node using only primitives that already exist in the underlying communication protocol, which excludes any training dataset. Simulations show that sprinkler adds minimal maintenance and energy expenditure while pinpointing deterministically the attacker in the network. In particular, sprinkler has a message delivery rate and detection rate of 100%.

Vanets, iot, and many other acronyms represent exciting new technologies that build upon pervasive computation and communications to achieve their goal. As an underlying communication model, the (mobile) ad hoc network (manet) paradigm is used, which implements a peer-to-peer communication model rather than the more traditional infrastructure model. Of course, privacy, confidentiality, integrity, and security related issues are of utter importance in such contexts as well. In this paper, we wish to present a key exchange technique, which builds upon the inherent characteristic of manets: their fluctuating topology. By splitting key exchange information into multiple parts and spraying them over space or time, the ever-changing topology of the network almost completely removes an active attacker’s success ratio. Algorithms are then simulated, and the results presented and discussed. We further point to future directions and uses for this research.

Attackers are usually interested in the important assets of the attack's target. In networks, bottleneck nodes - those that sit on many potential routes between sender and receiver - are the highest value asset that can be compromised. The dynamic nature of mobile ad-hoc networks (MANETs) causes ubiquitous routing algorithms to be even more susceptible to this class of attacks. Besides actually finding such bottleneck locations, an attacker can subvert the routing to create a virtual bottleneck. In this paper we propose a method of detecting bottleneck nodes in MANETs based on the prevalent OLSR protocol without imposing additional network traffic. Once such a bottleneck has been discovered, we propose mitigation methods.