Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.
This paper introduces an innovative method for image encryption called "Two-Fold Cryptography," which leverages the Henon map in a dual-layer encryption framework. By applying two distinct encryption processes, this approach offers enhanced security for images. Key parameters generated by the Henon map dynamically shape both stages of encryption, creating a sophisticated and robust security system. The findings reveal that Two-Fold Cryptography provides a notable improvement in image protection, outperforming traditional single-layer encryption techniques.
The Diffie-Hellman is a key exchange protocol to provide a way to transfer shared secret keys between two parties, although those parties might never have communicated together. This paper suggested a new way to transfer keys through public or non-secure channels depending on the sent video files over the channel and then extract keys. The proposed method of key generation depends on the video file content by using the entropy value of the video frames. The proposed system solves the weaknesses in the Diffie-Hellman key exchange algorithm, which is MIMA (Man-in-the-Middle attack) and DLA( Discrete logarithm attack). When the method used high definition videos with a vast amount of data, the keys generated with a large number up to 5
... Show MoreBotnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
... Show MoreIn the current digitalized world, cloud computing becomes a feasible solution for the virtualization of cloud computing resources. Though cloud computing has many advantages to outsourcing an organization’s information, but the strong security is the main aspect of cloud computing. Identity authentication theft becomes a vital part of the protection of cloud computing data. In this process, the intruders violate the security protocols and perform attacks on the organizations or user’s data. The situation of cloud data disclosure leads to the cloud user feeling insecure while using the cloud platform. The different traditional cryptographic techniques are not able to stop such kinds of attacks. BB84 protocol is the first quantum cry
... Show MoreThe research aims at identify the role of the electronic trading system used in the Iraq stock exchange to promote trading activity for the stocks of listed companies in this market.
To prove the hypothesis of research, it was selected the main trading indicators for the market to be a main field in test the research hypothesis.it was selected as the period of time for (9)years span between the years (2005-2013) because they represent the first two articles of equal time periods represent aperiod that preceded the introduction of electronic trading system while the second represents the period of time that followed
The research found a number of conclusions but the mo
... Show MoreTax information system is one of the most important means that help the tax administration to reach the real income of the taxpayer, and the problem of research came in the General Authority for Tax ,The next question (Does the control carried out by the Central Bank on foreign remittances to reach the real income of the taxpayer). The research is gaining importance by focusing on the Central Bank's control over foreign remittances, and how to use this control to finance the tax information system. The relationship between the Central Bank's control over foreign remittances and the tax information system.The study has reached a number of recommendations, the most important of which are the following: The work of an integrated information
... Show MoreChaotic systems have been proved to be useful and effective for cryptography. Through this work, a new Feistel cipher depend upon chaos systems and Feistel network structure with dynamic secret key size according to the message size have been proposed. Compared with the classical traditional ciphers like Feistel-based structure ciphers, Data Encryption Standards (DES), is the common example of Feistel-based ciphers, the process of confusion and diffusion, will contains the dynamical permutation choice boxes, dynamical substitution choice boxes, which will be generated once and hence, considered static,
While using chaotic maps, in the suggested system, called
Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu
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