## 4 Privacy Preserving in Cloud Computing
### Access Control  
User privacy concerns are not only dependent on what matters to a user of a system but depend on whether malicious intruders can have equal access [7]. Therefore, privacy preservation through access control comes from three major aspects, namely:  
1. Information-Centric Security: Data objects should contain access-control policies. This can be implemented through outsourcing data architectures that integrate cryptographic techniques with access control [84].
2. Trusted Computing: Trusted cloud computing system that provides consistency in accordance with software or hardware specification [82].
3. Cryptographic Protocols: Cryptographic tools and techniques can be employed to achieve privacy, such as Fully Homomorphic Encryption (FHE) [85] and Attribute-Based Encryption [86].  
[PERSON] et al. [87] proposed a Risk adaptive Access Control (RADAC) for preserving the privacy of sensitive data in flexible real-time. The RAdAC approach proposed by [87] was a hybrid of Policy-Based Access Control, Attribute-Based Access Control and Machine learning. In accomplishing this, the authors proposed principles to measure risk, establish an acceptable level of risk, and lastly, make sure that all information was tailored not to exceed the accepted level of risk. Following these guidelines, RadAC provided adaptability and flexibility compared to the traditional access control. The RADAC system discovered failures when access is being requested by checking past access control decisions and then quantifying the privileged, subject and object. [PERSON] et al. [88] proposed a framework that models the way users interact to achieve goals. The proposed framework used a catalogue that guides software engineers through alternatives in achieving privacy. The author in [88] further shows ways for reasoning about the non-functional requirements for privacy by allowing only modelled relationships between users in a strategic manner. The framework's strength is its adaptive ability to achieve goals from different alternatives. Further enhancements to I* will be to study deeper the interrelationship between trust and privacy, as this can interfere when allowing existing relationships. [PERSON] et al. [89] proposed security requirements that guarantee privacy. The author also proposed ways to maintain user anonymity while preserving user privacy, implementing an architecture that provides security and privacy when using personalised cloud systems. The approach in [89] allowed users to hide their identities during data collection. [PERSON] et al. used the concept of _Pseudoanoninity_ because N entities will be unable to reveal user anonymity. To further defend anonymity, the users included one trusted entity in every \(N+1\) component that may jeopardise anonymity. [PERSON] et al. [90] proposed a solution in preserving the privacy of users through Homomorphic Encryption (HE) while detecting anomalous intrusion and detection in network traffic. The introduced HE scheme was used in encrypting the data from third-party monitoring services, which are intended to provide security. The architecture provided Adhoc Intrusion and detection for monitoring the third-party while preserving privacy. When considering attacks such as code injection techniques, the HE scheme implemented in [90] was able to monitor generated code injection attacks without accessing any unencrypted data files. The limitation is the excess overhead incurred from the HE scheme due to additional processing time for both encryption and decryption. Secondly, the HE scheme evaluation results are always ciphered and decrypted, creating a bottleneck for the IDS as it does not possess a private key.