<span lang="EN-US">In the recent years, an increasing demand for securing visual resource-constrained devices become a challenging problem due to the characteristics of these devices. Visual resource-constrained devices are suffered from limited storage space and lower power for computation such as wireless sensors, internet protocol (IP) camera and smart cards. Consequently, to support and preserve the video privacy in video surveillance system, lightweight security methods are required instead of the existing traditional encryption methods. In this paper, a new light weight stream cipher method is presented and investigated for video encryption based on hybrid chaotic map and ChaCha20 algorithm. Two chaotic maps are employed for keys generation process in order to achieve permutation and encryption tasks, respectively. The frames sequences are encrypted-decrypted based on symmetric scheme with assist of ChaCha20 algorithm. The proposed lightweight stream cipher method has been tested on several video samples to confirm suitability and validation in term of encryption–decryption procedures. The performance evaluation metrics include visual test, histogram analysis, information entropy, correlation analysis and differential analysis. From the experimental results, the proposed lightweight encryption method exhibited a higher security with lower computation time compared with state-of-the-art encryption methods.</span>

This paper introduces a secure communication protocol that provides secured communication pathways to manipulate drones through unsecured communication. The deployment of the proposed protocol works through providing two secured communication paths; drones to the drone’s controller path and controller to data centre path. The first secured communication path has achieved a high level of security and privacy by using a modification of SHA-1 method and an advanced encryption method. The modification of the SHA-1 is called 83SHA-1. These modifications can increase rounds in the first stage up to 83 rounds, inject each round with expansion and S-Boxes procedures that are used in DES to extend length from 160 to 240 bits then reduce it from 240 to 160 bits. After hash data from the drone then use the advanced encryption method which is called Geffe-Genetic (GG) Encryption algorithm where three types of keys will be used for deception attackers. The second accomplishment is to ensure providing secure communication between the drone’s controller and datacentre by using RNA-RADG-CBC (RRCBC) encryption algorithm where will generate an initialization vector (IV) for cipher block chaining (CBC) randomly, generate keys, and propose an encryption/decryption method. The security analysis shows a promising high security level of drones’s data.

Intrusion detection system is responsible for monitoring the systems and detect attacks, whether on (host or on a network) and identifying attacks that could come to the system and cause damage to them, that’s mean an IDS prevents unauthorized access to systems by giving an alert to the administrator before causing any serious harm. As a reasonable supplement of the firewall, intrusion detection technology can assist systems to deal with offensive, the Intrusions Detection Systems (IDSs) suffers from high false positive which leads to highly bad accuracy rate. So this work is suggested to implement (IDS) by using a Recursive Feature Elimination to select features and use Deep Neural Network (DNN) and Recurrent Neural Network (RNN) for classification, the suggested model gives good results with high accuracy rate reaching 94%, DNN was used in the binary classification to classify either attack or Normal, while RNN was used in the classifications for the five classes (Normal, Dos, Probe, R2L, U2R). The system was implemented by using (NSL-KDD) dataset, which was very efficient for offline analyses systems for IDS.

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Image encryption is one of the primary approaches which is used to keep image information secure and safe. Recently, image encryption is turning its attention to combination with the field of DNA computing. In the presented study, a novel method of image encryption is suggested and implemented based on the DNA algorithm and Chaos theory, the most important principle in image encryption is breaking the correlation amongst pixels. This algorithm performs well against chosen cipher-text attacks. Furthermore, the proposed approach was implemented and analyzed for the Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), The performance of the encryption method is analyzed using the histogram, Shannon entropy and key space.