Data in transit validation for cloud computing using cloud-based algorithm detection of injected objects

• Main Authors: Olanrewaju, Rashidah Funke, Islam, Thouhedul, Khalifa, Othman Omran, Fajingbesi, Fawwaz Eniola
• Format: Article
• Language: English; English
• Published: Institute of Advanced Engineering and Science (IAES) 2018
• Subjects: TK Electrical engineering. Electronics Nuclear engineering; TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
• Online Access: http://irep.iium.edu.my/64152/1/64152_Data%20in%20transit%20validation%20for%20cloud%20computing_article.pdf; http://irep.iium.edu.my/64152/2/64152_Data%20in%20transit%20validation%20for%20cloud%20computing_scopus.pdf; http://irep.iium.edu.my/64152/; http://www.iaescore.com/journals/index.php/IJEECS/article/view/10891/8225

The recent paradigm shift in the IT sector leading to cloud computing however innovative had brought along numerous data security concerns. One major such security laps is that referred to as the Man in the Middle (MITM) attack where external data are injected to either hijack a data in transit or to manipulate the files and object by posing as a floating cloud base. Fresh algorithms’ for cloud data protection do exist however, they are still prone to attack especially in real-time data transmissions due to employed mechanism. Hence, a validation protocol algorithm based on hash function labelling provides a one-time security header for transferable files that protects data in transit against any unauthorized injection. The labelling header technique allows for a two-way data binding; DOM based communication between local and cloud computing that triggers automated acknowledgment immediately after file modification. A two layer encryption functions in PHP was designed for detecting injected object; bcrypt methods in Laravel and MD5 that generate 32 random keys. A sum total of 1600 different file types were used during training then evaluation of the proposed algorithm, where 87% of the injected objects were correctly detected.