Biblio

Face detection is an application widely used in video surveillance systems and it is the first step for subsequent applications such as monitoring and recognition. For facial detection, there are a series of algorithms that allow the face to be extracted in a video image, among which are the Viola & Jones waterfall method and the method by geometric models using the Hausdorff distance. In this article, both algorithms are theoretically analyzed and the best one is determined by efficiency and resource optimization. Considering the most common problems in the detection of faces in a video surveillance system, such as the conditions of brightness and the angle of rotation of the face, tests have been carried out in 13 different scenarios with the best theoretically analyzed algorithm and its combination with another algorithm The images obtained, using a digital camera in the 13 scenarios, have been analyzed using Matlab code of the Viola & Jones and Viola & Jones algorithm combined with the Kanade-Lucas-Tomasi algorithm to add the feature of completing the tracking of a single object. This paper presents the detection percentages, false positives and false negatives for each image and for each simulation code, resulting in the scenarios with the most detection problems and the most accurate algorithm in face detection.

Appending digital signatures and certificates to messages guarantee data integrity and ensure non-repudiation, but do not identify greedy authenticated nodes. Trust evolves if some reputable and trusted node verifies the node, data and evaluates the trustworthiness of the node using an accurate metric. But, even if the verifying party is a trusted centralized party, there is opacity and obscurity in computed reputation rating. The trusted party maps it with the node's identity, but how is it evaluated and what inputs derive the reputation rating remains hidden, thus concealment of transparency leads to privacy. Besides, the malevolent nodes might collude together for defamatory actions against reliable nodes, and eventually bad mouth these nodes or praise malicious nodes collaboratively. Thus, we cannot always assume the fairness of the nodes as the rating they give to any node might not be a fair one. In this paper, we propose a smart contract-based approach to update and query the reputation of nodes, stored and maintained by IPFS distributed storage. The use case particularly deals with an emergency scenario, dealing against colluding attacks. Our scheme is implemented using MATLAB simulation. The results show how smart contracts are capable of accurately identifying trustworthy nodes and record the reputation of a node transparently and immutably.

As a result of increasing the interest in developing the communication systems that use public channels for transmitting information, many channel problems are raised up. Among these problems, the important one should be addressed is the information security. This paper presents a proposed communication system with high security uses two encryption levels based on chaotic systems. The first level is chaotic scrambling, while the second one is chaotic masking. This configuration increases the information security since the key space becomes too large. The MATLAB simulation results showed that the Segmental Spectral Signal to Noise Ratio (SSSNR) of the first level (chaotic scrambling) is reduced by -5.195 dB comparing to time domain scrambling. Furthermore, in the second level (chaotic masking), the SSSNR is reduced by -20.679 dB. It is also showed that when the two levels are combined, the overall reduction obtained is -21.755 dB.

The Data Encryption Standard (DES) of the multimedia cryptography possesses the weak point of key conducting that is why it reaches to the triple form of DES. However, the triple DES obtains the better characteristic to secure the protection of data to against the attacks, it still contains an extremely inappropriate performance (speed) and efficiency in doing so. This paper provides the effective performance and the results of a single and triple chaotic cryptography using chaos in digital filter, compare to DES and triple DES. This comparison has been made pair-to-pair of single structure respectively to the triple form. Finally the implementation aspects of a single chaotic cryptography using chaos in digital filter can stand efficiently as better performance speed with the small complexity algorithm, points out the resemblances to DES and triple DES with the similar security confirmation results without reaching to the triple form of the structure. Simulation has been conducted using Matlab simulation with the input of grayscale image.

Internet of things (IoT) is the smart network which connects smart objects over the Internet. The Internet is untrusted and unreliable network and thus IoT network is vulnerable to different kind of attacks. Conventional encryption and authentication techniques sometimes fail on IoT based network and intrusion may succeed to destroy the network. So, it is necessary to design intrusion detection system for such network. In our paper, we detect routing attacks such as sinkhole and selective forwarding. We have also tried to prevent our network from these attacks. We designed detection and prevention algorithm, i.e., KMA (Key Match Algorithm) and CBA (Cluster- Based Algorithm) in MatLab simulation environment. We gave two intrusion detection mechanisms and compared their results as well. True positive intrusion detection rate for our work is between 50% to 80% with KMA and 76% to 96% with CBA algorithm.