Genetic diversity analysis of mangaba (Hancornia speciosa Gomes), an exotic braxilian tropical species.

Twenty genotypes from natural population of mangaba located in Itaporanga D’Ajuda (Sergipe state - Brazil) were subjected to analysis using RAPD markers. Polymorphism, genetic diversity and structure parameters were determined to characterize the differences between plants. 60 DNA fragments were generated by 10 primers, 85% of which were polymorphic. Results show a quantitative genetic diversity value of 0.35 and a Shannon index of 0.46 in the population. The similarity among the specimens according to Jaccard’s coefficient ranged from 0.36 to 0.87. Using cluster analysis it was possible to indentify five groups. Three individuals also stand out since they presented significant divergence from the groups. The PCoA formed four groups, with three of the groups isolated from the others. This investigation showed that genetic diversity was relatively large among these individuals. In addition, the results demonstrated that RAPD markers are a useful tool for evaluating the genetic diversity and relationships among mangaba

Evaluation of the quality of an image encrytion scheme

Encryption systems have been developed for image viewing applications using the Hill Cipher algorithm. This study aims to evaluate the image encryption quality of the Hill Cipher algorithm. Several traditional metrics are used to evaluate the quality of the encryption scheme. Three of such metrics have been selected for this study. These include, the Colour Histogram, the Maximum Deviation (comparing the original image) and the Entropy Analysis of the encrypted image. Encryption quality results from all three schemes using a variety of images show that a plain Hill Cipher approach gives a good result for all kinds of images but is more suited for colour dense images

Statistical analysis of the key scheduling of the new lightweight block cipher

This research paper is aimed at studying the generation of round keys (GRK) of the lightweight block cipher (LBC), which provides an optimal balance between security, performance, and minimal costs in internet of things (IoT). For comparative analysis, the GRK of the well-known PRESENT algorithm was studied. A number of studies have been carried out to assess the cryptographic strength of encryption algorithms, however, less attention has been paid to the assessment of the reliability of GRK algorithms, which can lead to a possible weakening of a cryptosystem. A trusted GRK should issue random and independent round keys regardless of the secret key. The experiments were carried out with secret keys of low and high density, as well as random numbers. The obtained results show that the GRK of the LBC algorithm generates random round keys that successfully pass tests of the National Institute of Standards and Technology (NIST) for randomness

COMPARATIVE STUDY OF CHAOTIC SYSTEM FOR ENCRYPTION

Chaotic systems leverage their inherent complexity and unpredictability to generate cryptographic keys, enhancing the security of encryption algorithms. This paper presents a comparative study of 13 chaotic keymaps. Several evaluation metrics, including keyspace size, dimensions, entropy, statistical properties, sensitivity to initial conditions, security level, practical implementation, and adaptability to cloud computing, are utilized to compare the keymaps. Keymaps such as Logistic, Lorenz, and Henon demonstrate robustness and high-security levels, offering large key space sizes and resistance to attacks. Their efficient implementation in a cloud computing environment further validates their suitability for real-world encryption scenarios. The context of the study focuses on the role of the key in encryption and provides a brief specification of each map to assess the effectiveness, security, and suitability of the popular chaotic keymaps for encryption applications. The study also discusses the security assessment of resistance to the popular cryptographic attacks: brute force, known plaintext, chosen plaintext, and side channel. The findings of this comparison reveal the Lorenz Map is the best for the cloud environment based on a specific scenario

CMI Computing: A Cloud, MANET, and Internet of Things Integration for Future Internet

The wireless communication is making it easier for smart devices to communicate with one another in terms of the network of the Internet of Things. Smart devices are automatically linked and built up a network on their own. But there are more obstacles to safe access within the network itself. Mobile devices such as smart home automation access point, smart washing machines, mobile boards, temperature sensors, color-changing smart lighting, smartphones, wearable devices, and smart appliances, etc. are widespread in our daily lives and is becoming valuable tools with wireless communication abilities that are using specific wireless standards that are commonly used with IEEE 802.11 access points. On the realism of the Internet, security has been perceived as a prominent inhibitor of embracing the cloud paradigm. It is resource storage and management that may lay in any since the cloud environment is a distributed architecture, which place of the world, many concerns have been raised over its vulnerabilities, security threats and challenges. The involvement of various parties has widened these concerns based on each party's perspective and objective. The Cloud point of view we mainly discuss the causes of obstacles and challenges related to security, reliability, privacy, and service availability. The wireless communication Security has been raised as one of the most critical issues of cloud computing where resolving such an issue would result in constant growth in the cloud’s use and popularity. Our purpose of this study is to create a framework of mobile ad hoc network mobility model using cloud computing for providing secure communication among smart devices network for the internet of things in 5G heterogeneous networks. Our main contribution links a new methodology for providing secure communication on the internet of smart devices in 5G. Our methodology uses the correct and efficient simulation of the desired study and can be implemented in a framework of the Internet of Things in 5G

Secure cluster-based routing using multi objective-trust centric artificial algae algorithm for wireless sensor network

Nowadays, wireless sensor network (WSN) is developed as a key technology to observe and track applications over a wide range. However, energy consumption and security are considered as important issues in the WSN. In this paper, the multi objective-trust centric artificial algae algorithm (M-TCAAA) is proposed to accomplish a secure broadcasting over the WSN. The proposed M-TCAAA is used to choose the secure cluster head (SCH) as well as routing path, based on the distinct fitness measures such as trust, communication cost, residual energy, and node degree. Hence, the M-TCAAA is used to ensure a secure data transmission while decreasing the energy consumed by the nodes. The performance of the M-TCAAA is analyzed by means of energy consumption, packet delivery ratio (PDR), throughput, end to end delay (EED), normalized routing load (NRL), and network lifetime. The existing researches namely energy aware trust and opportunity-based routing with mobile nodes (ETOR-MN), grey wolf updated whale optimization (GUWO), secure cluster-based routing protocol (SCBRP), secure routing protocol based on multi-objective ant-colony-optimization (SRPMA) and multi objective trust aware hybrid optimization (MOTAHO) are considered for evaluating the M-TCAAA. The PDR of the M-TCAAA for 100 nodes is 99.87%, which is larger than the ETOR-MN, GUWO, SRPMA and MOTAHO

SoK: Security Evaluation of SBox-Based Block Ciphers

Cryptanalysis of block ciphers is an active and important research area with an extensive volume of literature. For this work, we focus on SBox-based ciphers, as they are widely used and cover a large class of block ciphers. While there have been prior works that have consolidated attacks on block ciphers, they usually focus on describing and listing the attacks. Moreover, the methods for evaluating a cipher\u27s security are often ad hoc, differing from cipher to cipher, as attacks and evaluation techniques are developed along the way. As such, we aim to organise the attack literature, as well as the work on security evaluation. In this work, we present a systematization of cryptanalysis of SBox-based block ciphers focusing on three main areas: (1) Evaluation of block ciphers against standard cryptanalytic attacks; (2) Organisation and relationships between various attacks; (3) Comparison of the evaluation and attacks on existing ciphers

Quantitative image analysis of peripheral nerves in whiplash injury patients

The research in this thesis has examined the use of texture and shape analysis to characterise Magnetic Resonance (MR) images of peripheral nerves in order to provide a potential quantitative tool for better diagnosis and treatments. Texture and shape can be considered as inherent properties of all surfaces and have the potential to provide sensitive information which cannot be quantitatively perceived by human vision. Texture analysis has been successfully used in image classification of aerial and satellite imagery and the diagnosis and prognosis of several types of cancer. However, to date, it has never been used in investigating peripheral nerve damage. In this thesis, we study the application of texture and shape analysis to the peripheral nerves in the upper extremities of patients suffering from Whiplash Associated Disorders (WAD). Specifically, quantitative texture analysis was performed on MR images of the carpal tunnel which contains the median nerve. The median nerve was studied to identify differences in textural patterns. Texture methods such as: first order features; co-occurrence matrices; run-length matrices and autocorrelation function were applied and their performance was assessed. Texture analysis was also performed to investigate nerve damage in the MR images of the brachial plexus, both in controls and patients. Further, spatial domain shape metrics were used to quantify and study the morphological differences of the median nerve in controls and patients. This highlighted that some significant differences exist between groups and thus could potentially be reliably used in combination with clinical scale metrics to identify possible nerve damage. As MR images contain noise, locating the median nerve accurately to perform image analysis is very important. Therefore, we further investigated the application of an enhanced correlation filtering method that could be trained on images of the median nerve and then applied to detect the median nerve in test images. The Optimal Trade-off Maximum Average Correlation Height (OT-MACH) filter includes the expected distortions in the target in the construction of the filter reference function. The OT-MACH filter was tuned in a bandpass to maximize the correlation peak and thereby successfully locate the position of the median nerve in the carpal tunnel. This study has successfully demonstrated that texture and shape analysis can be used to investigate possible peripheral nerve damage. Further research is required using larger datasets to establish a quantitative image analysis tool to support clinical decision making and thereby improve patient care and treatment outcome