WSNs are vulnerable to various types of attacks. These attacks can be broadly categorized. That lead to cryptography, a security system utilized to ensure WSNs against external attacks. It guarantees numerous security administrations, including integrity and verification by checking the information parcel source and its substance using cryptographic algorithms, which can be categorized into three classes, symmetric-key algorithms, asymmetric-key algorithms, and hash functions [8,9].

Knowledge about cryptography and its unique customization with WSNs case studies will provide the research community with the latest updates in cryptographic techniques and bring a new perspective to security, power consumption, and many other areas of high importance in WSNs [10].

It is difficult decision to decide which cryptographic techniques should be used, how often they are used, and which network performance metrics are used to evaluate the design and security analysis. The first choice may be, “when does one use symmetric cryptography, and when does one use asymmetric cryptography?”

Symmetric encryption is also called single-key cryptography. In this encryption process, the receiver and the sender have to agree upon a single secret (shared) key. Given a message (plain text) and the key, encryption produces one intelligible data, about the same length as the plain text. Decryption is the reverse of encryption and uses the same key as encryption [11]. On the other hand, asymmetric encryption is also called public-key cryptography. It uses two keys: a public key, which is known to the public, used for encryption, and a private key, which is known only to the user of that key, used for decryption. The public and private keys are related by any mathematical means. In other words, data encrypted by one public key can be encrypted only by its corresponding private key [12].

The main distinguishing feature of asymmetric encryption is that it allows the establishment of secure communication between individuals without the requirement of a previously shared a single cryptographic key. Asymmetric cryptography came up with a radical change of paradigms [13]. In [14] Alshammari and Elleithy proposed a protocol that utilizes the existing cryptographic primitives and leverages asymmetric encryption to achieve key distribution and node authentication in one step and using only one frame to avoid communication overhead.

Two popular asymmetric schemes are Rivest-Shamir-Adleman (RSA) [15] and Elliptic Curve Cryptography (ECC) [16,17]. It is widely admitted that RSA is computationally intensive and usually executes thousands or even millions of multiplication instructions to perform a single-security operation [18]. Further, a microprocessor’s public key algorithm efficiency is primarily determined by the number of clock cycles required for multiplication instruction [19]. At [20], they found that public key algorithms such as RSA usually require on the order of tens of seconds and up to minutes to perform encryption and decryption operations in resource-constrained wireless devices, which exposes a vulnerability to the attacks.

In [21], they quantified the energy cost of authentication and key exchange based on public-key cryptography, RSA, and ECC on an 8-bit microcontroller platform. A comparison has been presented on two public-key algorithms, RSA and ECC, considering mutual authentication between two parties. The result shows that even software-based public key cryptography is feasible for an 8-bit microcontroller platform. Moreover, ECC shows significantly better results than RSA in terms of reduced computation time and the amount of data that needs to be stored and transmitted. Consequently, ECC requires less energy than RSA [8,21,22]. Further, the ECC-based key exchange protocol outperforms the RSA-based key exchange protocol on the server-side, and there is almost no difference in the energy cost for these two key exchange protocols on the client-side [23]. In addition, the relative performance advantage of ECC over RSA increases as the key size increases.

Anderson et al. questioned if “you can show that asymmetric encryption is feasible in sensor networks at a certain level of cost, it becomes possible to invent new security protocols or adapt existing ones for sensor networks” [24].

For the above reasons, in this research we adopted security algorithms that are more energy-efficient and have fewer processing operations possible to maintain the sensor’s life, such as ECC as asymmetric algorithm and Message Digest 5 (MD5) as hash algorithm. In addition, we propose Energy Saving and Securing Data algorithm (ESSD) and then apply ECC, MD5, and ESSD to LEACH and TEEN routing algorithms, which are considered the most widely used in WSNs.

A quick overview of both ECC algorithm and MD5 algorithms in the following:

In WSNs, the energy consumption is one of the most critical issues. The traditional routing protocols for WSN may not be optimal in energy consumption [28]. HRPs are more energy-efficient than other protocols [29]. HRP follows the clustering mechanisms; clustering techniques can be efficient in energy and scalability [30]. By using a clustering technique, they greatly minimize the consumption of energy in collecting and disseminating (fusion and aggregation) data. HRP minimizes energy consumption by dividing nodes into different clusters. In each cluster, higher energy nodes, i.e., the Cluster Heads (CHs), can process and send the information to the Base Station (BS). In contrast, low energy nodes, i.e., the cluster members, can be used to perform the sensing in the proximity of the target and send it to its CH. This means that the creation of clusters and assigning particular tasks to CH can significantly contribute to overall system scalability, lifetime, and energy efficiency, reducing the size of the routing table by localizing the route setup within the clusters and conserving the communication bandwidth of the network [31–33].

A quick overview of both LEACH and TEEN routing algorithms in the following:

Our proposed Energy Saving and Securing Data algorithm (ESSD) is designed to generate a set of encryption key numbers. It starts with points, Ax, Bx, Cx on the ECC curve and P prime number, then takes the start points’ integer part. In order to generate the rest of the sequence using the sum of all points modulo (P) and stop the sequence at the index (3P), the last step is to remove the repetition of numbers. Finally, get the set of integers which are the encryption keys. The steps of the ESSD method are illustrated in Algorithm 1.

Developed Algorithm ESSD (Energy Saving and Securing Data) in keys generation

For Example:

Let, Ax = 1, Bx = 1, Cx = 5, P = 13,

The next point is 7; (1+1+5) mod 13 ≡ 7 mod 13

The next point is 1; (1+1+5+7) mod 13 ≡ 1 mod 13

And so on as represented in Tab. 1.

Tab. 1 shows the generated points until the stop point 3P which equal to 3 × 13 = 39 in the example. In the previous step, we allow repetition in generating the key sequence, but the result should be a unique sequence without repetition.

So, the next step is to remove the repeated values and get the final sequence, as shown in Tab. 2,

Tab. 2 shows the key sequence for a specific example. Thus, we have the key sequence with the least number of computations and take the ECC security in order.

The simple radio model which describes the energy dissipation through the electronic devices, transmitter, power amplifier and receiver is shown in Fig. 1 [37].

In this work, we use MATLAB [38,39] for modeling & simulating the ESSD method.

Consider the following:

1) The equations of transmission and receiving the energy of the basic radio model [40] have been considered. The equations are listed below:

(2)ETX=Eclec∗K+Eamp∗d∧2∗K (3)ERX=Eclec∗K

Where,

ETX = Transmission Energy (The amount of energy consumed from the node when transmitting k of bit).

ERX = Receiving Energy (The amount of energy consumed from the node when Receiving k of bit).

Eclec (Energy used to run Transmitter Circuit) = 50 nJ/bit.

Eamp (Energy Amplifier) = 100 pJ/bit/m2.

k = number of bits to transmit or receive.

d = distance between source and destination.

Efs = Transmit Amplifier types-free space loss = 10^ (-12) * 1.

Emp = Transmit Amplifier types - multi path loss = 10^ (-15) * 1.3.

2) It’s known that Eq. (4) is not defined for a distance equal to zero. That is the reason for using a close in the distance do [41], which is in the following equation:

(4)do=(freespaceloss(Efs)multipathloss(Emp))∧0.5

3) Computing the distance between nodes using the Euclidean distance.

4) The big number of counters to compute Statistics.

Fig. 2 shows the connection loop from the node until the base station and backward. The node collects data and converts it to plain text after the ESSD method converts plain text to ciphertext. The ESSD method takes the security connection configuration as the ECC method and runs from the start points and uses a small prime number for creating a key sequence, which is the advantage of the MD5 hash key, which gives the ESSD method less number of computations.

The ESSD is a light method as the MD5 and secure as the ECC method since it takes the ECC idea and initialization.

In this chapter, we viewed the process of the ESSD method and the methodology of testing the security methods (ECC and MD5) with TEEN and LEACH protocols.

A MATLAB code has been developed to compare the lifetime of the best in literature routing protocols by enhancing the security services of these protocols by using the ESSD method. The implementation counts the number of dead nodes for each round (time) and shows how the proposed ESSD method outperformed the other key security algorithms such as MD5 and ECC. The proposed method has been implemented to conduct several tests.

The implementation code has been done under the following assumptions:

In nature, all nodes are homogeneous

The parameters used in the simulation are shown in Tab. 3.

The network lifetime in TEEN and LEACH are measured before and after applying security methods.

Fig. 3 shows the behavior of the LEACH protocol with all tested security methods.

Here, we compare with regards to energy consumption and show that the best result for energy consumption is when ESSD is used with LEACH, as the sensors began to die after 496 times (rounds) which is the longest time for all cases.

Tab. 4 shows the number of dead nodes and the time of death for each security method. As it appears, the longest time when ESSD is used, it is less energy-consuming. The most energy-consuming is when using ECC because the first 10 sensors begin to die at 412 times. The least energy-consuming is when using the ESSD method because the first 10 sensor nodes are to die at 549, and hence it shows that the best position for energy consumption is when we use ESSD with the LEACH protocol.

Fig. 4 shows the behavior of TEEN protocol with all tested security methods.

Tab. 5 shows the number of dead nodes and the time of death for each security method. This table compares the numbers of sensors that die for each algorithm and shows that its best result was ESSD as, at the time, 4317 began the death of the first ten sensors. This means that we received the lowest power consumption and the confidentiality and authentication of essential security services.

The ESSD mapped the confidentiality from the MD5 method steps and mapped the authentication from the ECC method steps since the ESSD comes from the idea of generating MD5 and ECC.

Note: The word “Non” used in Tab. 5 describes that the test ends when it reaches the maximum number of rounds which is 5000 rounds.