Search

Internet of Things (IoT) employs a large number of sensors and actuators to collect and act upon data for its smart functionalities. These devices are considered as a part of the Low-power and Lossy Networks due to their use of low power embedded hardware and computationally constrained nature. For synchronization and utility, these devices are often clubbed together logically to form groups. To maintain data confidentiality within a group, a shared symmetric key called the Group Key (GK) is used by all the group members. The GK must be redistributed upon joining and leaving of a group member to maintain forward and backward secrecy. However, the key management (i.e., generation and distribution) process causes overhead which consumes the scarce network resources. In this paper, we propose TARE, a novel Topology Adaptive Re-kEying (TARE) scheme for lightweight and secure group communication. TARE integrates the principles of routing tree mapped logical key tree and local derivation of the key over the an IPv6 Routing Protocol for low-power and Lossy networks in an original way. TARE takes into consideration the current routing topology and makes maximum energy reduction as the premise for its choice of key derivation and distribution methods, thus, it reduces the network energy consumption while maintaining key secrecy and data confidentiality. In particular, TARE provides the following advantages: (1) lower network overhead and bandwidth utilization in key management and re-distribution operations, (2) effective against the network mobility in scalable IoT networks, (3) secure group communications in network against attacks such as man-in-the-middle and eavesdropping, and (4) data confidentiality by ensuring backward and forward secrecy in key distribution method. We evaluate the performance of TARE and compare it with existing schemes. Our results show the effectiveness of TARE regarding energy consumption, bandwidth utilization, and the number of encrypted message transmissions during the re-keying operations. [ABSTRACT FROM AUTHOR]

The idea of Internet of Things (IoT) is that many of the live objects (e.g., appliances) in the network are accessible, sensed, and interconnected. However, energy-constrained IoT nodes limit the performance of the IoT network. Hence, preserving energy in IoT network requires utmost attention. Unequal clustering is commonly considered as one of the efficient energy saving technique. Here, the traffic load is evenly distributed among the nodes using variable size clusters across the network. However, none of the existing solutions considered (1) realistic factors like fading model, routing protocol etc., or (2) optimization of cluster radius while devising clustering structure. The contribution of this paper is two-fold. First, we analyze the maximization of network lifetime by balancing the energy consumption among Cluster Heads (CHs). We found that cluster radius of each level has significant role in maximization of network lifetime. Second, to meet the requirement of maximization of network lifetime, this paper proposes a novel Lifetime Maximizing optimal Clustering Algorithm (LiMCA) for battery-powered IoT devices. Particularly, LiMCA includes a novel stochastic deployment scheme for Member Nodes (MNs) and CHs and a training protocol to train CHs and MNs about their coarse-grain location. Extensive simulation study shows that our algorithm improves the network lifetime by more than 30%, compared to other existing approaches. [ABSTRACT FROM AUTHOR]

A distributed denial of service (DDoS) attack on any of the major components (e.g., controller, switches, and southbound channel) of software defined networking (SDN) architecture is a critical security threat. For example, the breakdown of controller could disrupt the data communication in the whole SDN network. A possible way to perform DoS is to generate a large number of new, but short length traffic flows. These flows will trigger malicious flooding requests to overload the controller and causes overflow in flow tables at SDN switches. In this paper, we propose two lightweight and practically feasible countermeasures against two different types of DDoS attacks called Route Spoofing and Resource Exhaustion in SDN networks. For Route Spoofing attack, we introduce a technique called "selective blocking", which stops an adversary node from maliciously using other users active communication routes. To countermeasure Resource Exhaustion attack, we propose a solution called "periodic monitoring", which detects adversary nodes based on the traffic analysis statistics that are gathered within a time window. We implement and perform result analysis of the attacks and their proposed countermeasures. When using our proposed countermeasures in the target SDN scenarios, the simulation results indicate an adequate reduction in bandwidth consumption and processing delay of new request, and it also depicts substantial gain in packet delivery rate. Additionally, we present the receiver operating characteristic curve, which shows the sensitivity and specificity of our countermeasures along with their detection accuracy. [ABSTRACT FROM AUTHOR]

In this paper, we propose a Multi-Constraint Quality-of-Experience (QoE) centric Routing (MCQR) technique for efficient real-time video streaming over Mobile Ad-hoc Networks (MANETs). The dynamic estimation of link quality metric during MCQR route discovery process is the key of enhancing QoE at end user. MCQR limits end-to-end delay and jitter of received data packets by selecting long lifetime routes with maximum permissible delay. This minimizes the distortion caused fluctuations in perceived video. To prove the effectiveness of MCQR for real-time video streaming, we have designed a hybrid MANET consisting of simulated nodes and physical machines. In our hybrid network, the source and destination nodes are video traffic generators and receivers running on physical devices. Emulation results are obtained using real-time video streaming over high fidelity virtual wireless network, and conforming that the MCQR protocol provides satisfactory QoE to end users as compared to existing similar techniques. The packet delivery ratio of MCQR is higher than 90 % and its mean opinion score is higher than three (i.e., satisfactory) even when mobility and shadowing effects are kept high in target network scenarios. These improvements are achieved along with still maintaining similar or better routing overhead and processing delays. [ABSTRACT FROM AUTHOR]