International Journal of Mathematical Sciences and Computing @ijmsc
Статьи журнала - International Journal of Mathematical Sciences and Computing
Все статьи: 264
Cryptographic Security using Various Encryption and Decryption Method
Статья научная
Fast development in universal computing and the growth in radio/wireless and mobile strategies have led to the extended use of application space for Radio Frequency (RFID), wireless sensors, Internet of things (IoT). There are numerous applications that are safe and privacy sensitive. The increase of the new equipments has permitted intellectual methods of linking physical strategies and the computing worlds through numerous network interfaces. Consequently, it is compulsory to take note of the essential risks subsequent from these communications. In Wireless systems, RFID and sensor linkages are extremely organized in soldierly, profitable and locomotive submissions. With the extensive use of the wireless and mobile devices, safety has therefore become a major concern. As a consequence, need for extremely protected encryption and decryption primitives in such devices is very important than before.
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Cyber Bullying Detection and Classification using Multinomial Naïve Bayes and Fuzzy Logic
Статья научная
The advent of different social networking sites has enabled people to easily connect all over the world and share their interests. However, Social Networking Sites are providing opportunities for cyber bullying activities that poses significant threat to physical and mental health of the victims. Social media platforms like Facebook, Twitter, Instagram etc. are vulnerable to cyber bullying and incidents like these are very common now-a-days. A large number of victims may be saved from the impacts of cyber bullying if it can be detected and the criminals are identified. In this work, a machine learning based approach is proposed to detect cyber bullying activities from social network data. Multinomial Naïve Bayes classifier is used to classify the type of bullying. With training, the algorithm classifies cyber bullying as- Shaming, Sexual harassment and Racism. Experimental results show that the accuracy of the classifier for considered data set is 88.76%. Fuzzy rule sets are designed as well to specify the strength of different types of bullying.
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Data Privacy System Using Steganography and Cryptography
Статья научная
Data privacy is being breached occasionally whether in storage or in transmission. This is due to the spate of attack occasioned by the movement of data and information on an insecure internet. This study aimed to design a system that would be used by both sender and receiver of a secret message. The system used the combination of Steganography (MSB) and Cryptography (RSA) approaches to ensure data privacy protection. The system generates two keys: public and private keys, for the sender and receiver to encrypt and decrypt the message respectively. The steganography method used does not affect the size of cover image. The software was designed using python programming language in PyCharmIDE. The designed system enhanced the security and privacy of data. The results of this study reveal the effectiveness of combination of steganography and cryptography over the use of either cryptography or steganography and other existing systems.
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