Prevention of hidden information security attacks by neutralizing Stego-Malware. (July 2022) - Monika, A.; Eswari, R.
Highlights: Cloud computing [1] is a relatively new computer paradigm that has emerged out of possible intersection involving various genres like parallel computing, utility computing, grid computing, and other computer technologies. Cloud computingdelivers many applications like virtualization, high reliability, data storage, and high expansibility. Also, it provides on-demand and convenient network access to several inter-connected configurable computing resources (e.g., storage applications, networks, servers, and services) that may be promptly reinforced with little effort from administrators or service providers. Abstract: Cybercriminals consistently seek effective vectors to launch attacks on on-demand platforms like Cloud, thereby accurately delivering malware to the target platforms. To bypass defence mechanisms, the attackers obfuscate malware in multiple ways. Information-concealing techniques are used by hackers to bypass the existing defence mechanisms, thereby causing service disruption, loss of control, data loss, or modification of sensitive data in the cloud. This paper proposes a Stegware Neutralization model that aims to build a ubiquitous mechanism to readily counter hidden information attacks, irrespective of the obfuscation techniques used. The proposed system functions in three main phases: Steganalysis phase, Location finder and Neutralization phase. In the Steganalysis phase, the presence of obfuscated items hidden inside the digital medium is identified, while the location finder spots the exact location of the hidden payloads. In the Neutralization phase, location of the hidden item is neutralized by using nonlinear transfer function. The effectiveness of the proposed system is tested by analysing different image files obtained from the benchmarked database sources while checking for obfuscated malicious codes. A subset of the latest malware codes is collected from business Application Programming Interfaces (API) like VirusTotal. The experimental results show that the proposed system obtains higher accuracy rate in detecting malware i.e., ranging from 90% to 96% at different embedding rates (10% to 50%) as compared to the existing systems. Moreover, the proposed system firmly neutralizes the detected hidden malware. In fact, 97% of stegoimages are neutralized on an average by the proposed system. Also, the image files retain their original quality even after undergoing neutralization, showing hardly any perceptible change, almost missing the naked eye. Graphical abstract: Image, graphical abstract Prevention of hidden information security attacks by neutralizing Stego-Malwares: