Security of Separated Data in Cloud Systems with Competing Attack Detection and Data Theft Processes

Abstract

Empowered by virtualization technology, service requests from cloud users can be honored through creating and running virtual machines. Virtual machines established for different users may be allocated to the same physical server, making the cloud vulnerable to coresidence attacks where a malicious attacker can steal a user's data through co-residing their virtual machines on the same server. For protecting data against the theft, the data partition technique is applied to divide the user's data into multiple blocks with each being handled by a separate virtual machine. Moreover, early warning agents (EWAs) are deployed to possibly detect and prevent co-residence attacks at a nascent stage. This article models and analyzes the attack success probability (complement of data security) in cloud systems subject to competing attack detection process (by EWAs) and data theft process (by co-residence attackers). Based on the suggested probabilistic model, the optimal data partition and protection policy is determined with the objective of minimizing the user's cost subject to providing a desired level of data security. Examples are presented to illustrate effects of different model parameters (attack rate, number of cloud servers, number of data blocks, attack detection time, and data theft time distribution parameters) on the attack success probability and optimization solutions.

Digital Security Challenges Faced by Business Organizations

“…Generally, in the case of a large IP packet, it will be splitted into numerous fragments and reassembled into a complete packet to the recipient host. However, POD attack exactly exploits the reassembling packet size of 65,535 bytes greater than its maximum to maliciously manipulate overflow of memory allocated as a result of denial of service [11].…”

“…CCA could be conducted by various methods such as structured query language (SQL) injection attack, DDoS attack, malicious insider, side channel attack, man-in-themiddle (MITM) attack and abuse of cloud services. Cloud computing attack is the most economically significant threat in the world of virtualization technology, confidential data breach is one of the key diminish potential revenue loss and customer trust [11]. In fact, a massive cyber attack in Sweden in July 2017, a high confidential data stored at cloud system was breached, causing irreversible consequences that exposed national secrets, national security, international wrongdoing, and resignation of ministers.…”

Healthcare in the Balance

“…Prevention and detection methods as well as professionally trained cybersecurity specialists are needed to protect patient data, medical devices and other sensitive healthcare systems. [1,7,8,9,11,15,19,25,27,29,31,33,35,36,38,39,40,42,45].…”

Financial Risk Analysis and Early Warning Research Based on Data Mining and Statistical Analysis Technology

“…The information contained in the test sample is real-time and fair. [7][8][9][10] Second, make clear the structure of artificial neural network. In practice, the concrete model with artificial neural network as the core should be defined first.…”