Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is openly accessible. It evaluates the performance of a complete arrangement of machine learning algorithms and network traffic features to indicate the best features for detecting the assured attack classes. Our goal is storing the address of destination IP that is utilized to detect an intruder by method of misuse detection.
This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti
... Show MoreEmotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
... Show MoreEleven new 2,6-di-tert-butyl-4-(5-aryl-1,3,4-oxadiazol-2-yl)phenols 5a–k were synthesized by reacting aryl hydrazides with 3,5-di-tert butyl 4-hydroxybenzoic acid in the presence of phosphorus oxychloride. The resulting compounds were characterized based on their IR, 1H-NMR, 13C-NMR, and HRMS data. 2,2-Diphenyl-1-picrylhydrazide (DPPH) and ferric reducing antioxidant power (FRAP) assays were used to test the antioxidant properties of the compounds. Compounds 5f and 5j exhibited significant free-radical scavenging ability in both assays.
Background: Apicoectomy and retrograde filling is indicated when conventional endodontic treatment is impossible or failed to achieve apical seal. The aim of this study was to evaluate the effect of ER: YAG laser on apical microleakage. Materials and Methods: Sixty extracted single-rooted teeth were used in this study. The roots were divided into six groups. Group 1: apicoectomy by fissure bur, and apical cavities prepared by round bur, then cavities were filled with MTA. Group 2: the roots preparations and fillings were the same as group 1, then the apical areas were treated by Er:YAG Laser. Group 3: apicoectomy by fissure bur, and apical cavities prepared by ultrasound retrotip and cavities were filled with MTA. Group 4: the roots prepara
... Show MoreThe aim of this study is to investigate the role of prodigiosin on P. aeruginosa' s biofilm genes involved in the pathogenicity and persistency of the bacteria; Materials and methods: Gram negative bacterial isolates were taken from burn and wounds specimen obtained from some of Baghdad hospitals. Forty six isolates were identified as Pseudomonas aeruginosa and four isolates as Serratia marcescens by using biochemical tests and VITEK 2 compact system. Susceptibility test was performed for all P. aeruginosa isolates, the results showed that 100% were resistant to Amikacin and 98% were sensitive to Meropenem. Resistant isolates were tested for biofilm formation; the strong and moderate isolates (17) were detected by PCR for AlgD gene
... Show More