Internet of Things (IoT) is a set of connected smart devices providing and sharing rich data in real-time without involving a human being. However, IoT is a security nightmare because like in the early computer systems, security issues are not considered in the design step. Thereby, each IoT system could be susceptible to malicious users and uses. To avoid these types of situations, many approaches and techniques are proposed by both academic and industrial researches.DNA computing is an emerging and relatively new field dealing with data encryption using a DNA computing concepts. This technique allows rapid and secure data transfer between connected objects with low power consumption. In this paper, authors propose a symmetric cryptography method based on DNA. This method consists in cutting the message to encrypt/decrypt in blocks of characters and use a symmetric key extracted from a chromosome for encryption and decryption. Implemented on the embedded platform of a Raspberry Pi, the proposed method shows good performances in terms of robustness, complexity and attack resistance.

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Recently, considerable attention has been given to data mining techniques to improve the performance of intrusion detection systems (IDS). This has led to the application of various classification and clustering techniques for the purpose of intrusion detection. Most of them assume that behaviors, both normal and intrusions, are represented implicitly by connected classes. We state that such assumption isn't evident and is a source of the low detection rate and false alarm. This paper proposes a suitable method able to reach high detection rate and overcomes the disadvantages of conventional approaches which consider that behaviors must be closed to connected representation only. The main strategy of the proposed method is to segment sufficiently each behavior representation by connected subsets called natural classes which are used, with a suitable metric, as tools to build the expected classifier. The results show that the proposed model has many qualities compared to conventional models; especially regarding those have used DARPA data set for testing the effectiveness of their methods. The proposed model provides decreased rates both for false negative rates and for false positives.

The integrity and confidentiality of transmitted data are the main requirements of any data security system. To achieve these goals, many techniques have been developed, including cryptography and steganography. Recently, DNA-based steganography has emerged as a very powerful and promising approach to ensure the safety of sensitive information transmitted over an untrusted channel. In this paper, a two-level encryption/decryption scheme combining cryptography and steganography is proposed. First, the plain-text is concealed in a cover image by scattering its letters over randomly selected pixels. Then, the modified image is encrypted by encoding its pixels in a DNA sequence using a symmetric key. Simulations have shown that the proposed scheme is more robust than any other system based on standalone techniques and requires less computing resources.

Electronic voting, often referred to as "e-voting," has gained popularity in recent years because it reduces the cost and time of counting, increases voter participation, and reduces human resources, thereby reducing fraud and increasing transparency. In this paper, an e-voting system is designed and implemented using symmetric DNA encryption. The proposed scheme consists of using DNA-XOR as secret sharing operator for multi-authority secret ballot elections which enables end-to-end vote verification. The transmitted data is divided into segments and converted into DNA sequences. The main contributions of the resulting system are our proposal for secret sharing between authorities via DNA cryptosystem which ensures that no single authority can compromise the integrity of the ballot without the approval of the other authorities and the proposal's computational and architectural scalability, which makes it simple to implement.