The use of signature-based broadcast authentication for code and data dissemination in wireless sensor networks (WSNs) cannot be avoided. It increases security but requires high computation. Adversaries can exploit the latter condition as an opportunity to send many false signatures. Filtering methods can overcome this vulnerability. Cipher Puzzle is a filtering method that has low storage overhead along with high security, especially against denial of service (DoS) attacks. However, its number of hash iterations cannot be bounded, which causes sender-side delay. This paper proposes a Dynamic Cipher Puzzle (DCP), which uses a threshold function to limit the number of hash iterations. Hence, time at the sender-side can be used more efficiently. Besides, its dynamic puzzle-strength increases the obscurity of the transmitted packet. Simulation and experimental results were analyzed with Arduino 2560. The theoretical results show that the quadratic function outperformed the compared methods. The scheme decreased sender-side delay by 94.6% with a guarantee of zero solution probability in 1.728 ×10−13. The experimental results show that the consumption of resources at the sensor node increases with an acceptable value. Moreover, DCP increases the complexity for the attacker to implement probability and signature-based DoS attacks.
Using a smart grid, which increases efficiency and makes it easier to monitor critical equipment in a power grid. Online real-time applications equipped with a wireless sensor network (WSN) sense and collect data in order to provide information on power generation, transmission, distribution, and customer. Applications, the administrator, and (mobile) consumers can access the WSN directly. The communications between them must be protected from adversaries to avoid false data injection, which could cause damage either to the applications, the equipment, or the sensor nodes. Another threat comes from the characteristics of the sensor nodes, which makes them vulnerable to denial of services (DoS) attacks, i.e., flooding with false messages. In this paper, a multiuser dynamic cipher puzzle (M-DCP) equipped with TinySet is proposed. This new method provides guaranteed confidentiality in the multiuser WSN authentication and lightweight DoS resistance. The M-DCP using RC5 encryption combined with the elliptic curve digital signature algorithm (ECDSA) and partial recovery can increase brute force complexity to about 1.861 × 10 137 iterations. Furthermore, the regularization of TinySet is done to simplify the administrator's task in defining the initialization parameters. The experiment showed that the regularized TinySet required less storage space with a 64-bit index than with a 32-bit index or with Counting Bloom Filter. In addition, the average query and verification time of the proposed scheme increased only by under a second or 36% compared to Counting Bloom Filter-based authentication. This is still appropriate for implementation in the WSNs.
A feature selection algorithm (FSA) is used to eliminate redundant and irrelevant features. Obviously, it can reduce dimensionality as well as the complexity of the original problem. Furthermore, the stability of FSA output becomes a major issue in real-world applications. Stability refers to the consistency of its feature preference related to the perturbation of data samples. In sensor array optimization, an FSA is used to find the best sensor combination in a sensor array. Typically, the main objectives of sensor array optimization are reducing data dimensions, electrical consumption, production cost, computational and traffic overhead, etc. Furthermore, the stable outputs of FSA in several observations are necessary to make a firm conclusion of selected sensors. The contribution of this research is to investigate the stability of FSAs in twelve homogeneous datasets in relation to the sensor array optimization problem. In this study, the stability of seventeen filter-based FSAs is compared across twelve homogeneous datasets. These datasets are generated from the electronic nose (e-nose) used to monitor twelve types of beef cuts. In this case, gas sensor array must have good generalization to differentiate all beef types. The experimental results show that a single FSA cannot guarantee stable sensors recommendation in sensor array optimization. Thus, it becomes a caution to researchers and practitioners to use a proper approach when performing sensor array optimization.
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