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Wireless Sensor Networks constitute an important part of the Internet of Things, and in a similar way to other wireless technologies, seek competitiveness concerning savings in energy consumption and information availability. These devices (sensors) are typically battery operated and distributed throughout a scenario of particular interest. However, they are prone to interference attacks which we know as jamming. The detection of anomalous behavior in the network is a subject of study where the routing protocol and the nodes increase power consumption, which is detrimental to the network’s performance. In this work, a simple jamming detection algorithm is proposed based on an exhaustive study of performance metrics related to the routing protocol and a significant impact on node energy. With this approach, the proposed algorithm detects areas of affected nodes with minimal energy expenditure. Detection is evaluated for four known cluster-based protocols: PEGASIS, TEEN, LEACH, and HPAR. The experiments analyze the protocols’ performance through the metrics chosen for a jamming detection algorithm. Finally, we conducted real experimentation with the best performing wireless protocols currently used, such as Zigbee and LoRa.

The servitization of network resources leads to new challenges for optical networks. For instance, to provide on-demand lightpaths as a service while keeping the probability of packet loss (PPL) low, issues such as lightpath setting up, resource reservation and load balancing must be addressed. We present a self-adaptive framework to process lightpath requests on packet switching optical networks that considers and handles the aforementioned issues. The framework is composed of a dimensioning phase that adds up new resources to an initial topology and a learning phase based on reinforcement learning that provides self-adaptation to tolerate traffic changes. The framework is tested on three realistic mesh topologies achieving a PPL between $$1 \times 10^{-1}$$ and $$1 \times 10^{-6}$$ for different traffic loads. Compared to fixed multi-path routing strategies, our framework reduces PPL between $$19\%$$ and up to $$80\%$$ . Furthermore, no packet loss can also be achieved for traffic loads equal to or lower than 0.4.

In this work, we compare a recently proposed routing protocol, the multi-parent hierarchical (MPH) protocol, with two well-known protocols, the ad hoc on-demand distance vector (AODV) and dynamic source routing (DSR). For this purpose, we have developed a simulator, which faithfully reifies the workings of a given protocol, considering a fixed, reconfigurable ad hoc network given by the number and location of participants, and general network conditions. We consider a scenario that can be found in a large number of wireless sensor network applications, a single sink node that collects all of the information generated by the sensors. The metrics used to compare the protocols were the number of packet retransmissions, carrier sense multiple access (CSMA) inner loop retries, the number of nodes answering the queries from the coordinator (sink) node and the energy consumption. We tested the network under ordinary (without attacks) conditions (and combinations thereof) and when it is subject to different types of jamming attacks (in particular, random and reactive jamming attacks), considering several positions for the jammer. Our results report that MPH has a greater ability to tolerate such attacks than DSR and AODV, since it minimizes and encapsulates the network segment under attack. The self-configuring capabilities of MPH derived from a combination of a proactive routes update, on a periodic-time basis, and a reactive behavior provide higher resilience while offering a better performance (overhead and energy consumption) than AODV and DSR, as shown in our simulation results.

In this work, we present the design of a mitigation scheme for jamming attacks integrated to the routing protocols MPH, AODV, and DSR. The resulting protocols are named MPH-M (Multi-Parent Hierarchical - Modified), AODV-M (Ad hoc On Demand Distance Vector - Modified), and DSR-M (Dynamic Source Routing - Modified). For the mitigation algorithm, if the detection algorithm running locally in each node produces a positive result then the node is isolated; second, the routing protocol adapts their paths avoiding the isolated nodes. We evaluated how jamming attacks affect different metrics for all these modified protocols. The metrics we employ to detect jamming attack are number of packet retransmissions, number of CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) retries while waiting for an idle channel and the energy wasted by the node. The metrics to evaluate the performance of the modified routing protocols are the throughput and resilience of the system and the energy used by the nodes. We evaluated all the modified protocols when the attacker position was set near, middle and far of the collector node. The results of our evaluation show that performance for MPH-M is much better than AODV-M and DSR-M. For example, the node energy for MPH-M is 138.13% better than AODV-M and 126.07% better than DSR-M. Moreover, we also find that MPH-M benefits much more of the mitigation scheme than AODV-M and DSR-M. For example, the node energy consumption is 34.61% lower for MPH-M and only 3.92% and 3.42% for AODV-M and DSR-M, respectively. On throughput, the MPH protocol presents a packet reception efficiency at the collector node of 16.4% on to AODV and DSR when there is no mitigation mechanism. Moreover, MPH-M has an efficiency greater than 7.7% with respect to AODV-M and DSR-M when there is a mitigation scheme. In addition, we have that with the mitigation mechanism AODV-M and DSR-M do not present noticeable modification. However, MPH-M improves its efficiency by 8.4%. We also measure the resilience of these algorithms from the average packet re-transmissions perspective, and we find that MPH-M has around a 15% lower change rate than AODV-M and DSR-M. The MPH-M recovery time is 5 s faster than AODV-M and 2 s faster than DSR-M.

Wireless Sensor Networks deliver valuable information for long periods, then it is desirable to have optimum performance, reduced delays, low overhead, and reliable delivery of information. In this work, proposed metrics that influence energy consumption are used for a performance comparison among our proposed routing protocol, called Multi-Parent Hierarchical (MPH), the well-known protocols for sensor networks, Ad hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR), and Zigbee Tree Routing (ZTR), all of them working with the IEEE 802.15.4 MAC layer. Results show how some communication metrics affect performance, throughput, reliability and energy consumption. It can be concluded that MPH is an efficient protocol since it reaches the best performance against the other three protocols under evaluation, such as 19.3% reduction of packet retransmissions, 26.9% decrease of overhead, and 41.2% improvement on the capacity of the protocol for recovering the topology from failures with respect to AODV protocol. We implemented and tested MPH in a real network of 99 nodes during ten days and analyzed parameters as number of hops, connectivity and delay, in order to validate our Sensors 2014, 14 22812 simulator and obtain reliable results. Moreover, an energy model of CC2530 chip is proposed and used for simulations of the four aforementioned protocols, showing that MPH has 15.9% reduction of energy consumption with respect to AODV, 13.7% versus DSR, and 5% against ZTR.

In this work, two new self-tuning collaborative-based mechanisms for jamming detection are proposed. These techniques are named (i) Connected Mechanism and (ii) Extended Mechanism. The first one detects jamming by comparing the performance parameters with respect to directly connected neighbors by interchanging packets with performance metric information, whereas the latter, jamming detection relays comparing defined zones of nodes related with a collector node, and using information of this collector detects a possible affected zone. The effectiveness of these techniques were tested in simulated environment of a quadrangular grid of 7 &times, 7, each node delivering 10 packets/sec, and defining as collector node, the one in the lower left corner of the grid. The jammer node is sending packets under reactive jamming. The mechanism was implemented and tested in AODV (Ad hoc On Demand Distance Vector), DSR (Dynamic Source Routing), and MPH (Multi-Parent Hierarchical), named AODV-M, DSR-M and MPH-M, respectively. Results reveal that the proposed techniques increase the accurate of the detected zone, reducing the detection of the affected zone up to 15% for AODV-M and DSR-M and up to 4% using the MPH-M protocol.

Substitution Box (S-box) is usually the most complex module in some block ciphers. Some prominent ciphers such as AES and Camellia use S-boxes, which are affine equivalents of a multiplicative inverse in small finite fields. This manuscript describes mathematical representations of the Camellia S-box by using composite fields such as polynomial, normal or mixed. An optimized hardware implementation typically aims to reduce the number of gates to be used. Our theoretical design with composite normal bases allows saving gates in the critical path by using 19 XOR gates, 4 AND gates and 2 NOT gates. With composite mixed bases, the critical path has 2 XOR gates more than the representation with composite normal bases. Redundancies found in the affine transformation matrix that form the composite fields were eliminated. For mixed bases, new Algebraic Normal Form identities were obtained to compute the inner composite multiplicative inverse, reducing the critical path of the complete implementation of the Camellia S-box. These constructions were translated into transistor-gate architectures for hardware representations by using Electric VLSI [29] under MOSIS C5 process [17], [18], thus obtaining the corresponding schematic models.

This research shows the improvement obtained by including the principal component analysis as part of the feature production in the generation of a speech key. The main architecture includes an automatic segmentation of speech and a classifier. The first one, by using a forced alignment configuration, computes a set of primary features, obtains a phonetic acoustic model, and finds the beginnings and ends of the phones in each utterance. The primary features are then transformed according to both the phone model parameters and the phones segments per utterance. Before feeding these processed features to the classifier, the principal component analysis algorithm is applied to the data and a new set of secondary features is built. Then a support vector machine classifier generates an hyperplane that is capable to produce a phone key. Finally, by performing a phone spotting technique, the key is hardened. In this research the results for 10, 20 and 30 users are given using the YOHO database. 90% accuracy.

In this research we present a new scheme for the generation of a biometric key based on Automatic Speech Technology and Support Vector Machines. Keys are produced by making a distinction among the voice attributes of the users employing hyperplanes. It is described how the key is conformed and the reliability of the method. We depict an experimental evaluation for different values of the parameters. Among the different kernels for the Support Vector Machine, the RBF obtained the best results.