133
limitations, not least the lack of standards-based interoperable clouds and
APIs, the possible amplification of the attack surface to multiple clouds,
and the management and measurement of multiple service level agreements across multiple clouds (Bucur et al. 2018).
There is a long history of encryption as a means of securing systems.
For example, many messaging systems use encryption to protect the content of messages through the use of shared public or private keys. These
legacy systems have a number of limitations including data control and the
management of keys (Acar et al. 2018). Homomorphic encryption
schemes overcome these limitations by allowing a cloud service provider
to perform certain computable functions on the encrypted data while preserving the features of the function and format of the encrypted data (Acar
et al. 2018). Louk and Lim (2015) proposed a homomorphic data security encryption scheme that converted data into ciphertext and manipulated the ciphertext just like the original text without compromising the
encryption. There are a variety of different homographic encryption types,
for example multiplicative, additive and fully homomorphic, all of which
have been applied to secure communication and storage in the cloud
(Tebaa and Hajji 2014). There are significant performance limitations
with fully homomorphic encryption schemes thus requiring optimisation
at the architectural, algorithmic, and hardware resource levels (Moore
et al. 2014).
The ubiquity of smartphones, and their dependence on cloud computing, present significant challenges for securing data at the edge, in the
cloud, and in between. Smartphones, and indeed other Internet of Things
end points, are typically resource constrained due to their form and bandwidth. As such, security methods need to be relatively lightweight. Wang
et al. (2014) propose a secure sharing scheme that envisages users uploading multiple data pieces to different clouds, and using a watermarking
algorithm for authentication of mobile users and cloud services. A key
feature of this solution is the both the security and the reduced load on the
network. Khan et al. (2014) propose a BSS (block-based sharing scheme)
cryptographic method that divides data logically into multiple blocks,
encrypting and decrypting the blocks, and reconstructing the data into
their original form. Secure Data Sharing in Clouds (SeDaSC) is another
approach to secure sharing comprising three entities—the user, a cryptographic server (CS) and the cloud (Ali et al. 2015). The CS is responsible
for encryption, decryption, key management, and access control. Yu et al.
(2015) proposed a public auditing protocol that ensures the integrity of
7 TRUSTWORTHY CLOUD COMPUTING
limitations, not least the lack of standards-based interoperable clouds and
APIs, the possible amplification of the attack surface to multiple clouds,
and the management and measurement of multiple service level agreements across multiple clouds (Bucur et al. 2018).
There is a long history of encryption as a means of securing systems.
For example, many messaging systems use encryption to protect the content of messages through the use of shared public or private keys. These
legacy systems have a number of limitations including data control and the
management of keys (Acar et al. 2018). Homomorphic encryption
schemes overcome these limitations by allowing a cloud service provider
to perform certain computable functions on the encrypted data while preserving the features of the function and format of the encrypted data (Acar
et al. 2018). Louk and Lim (2015) proposed a homomorphic data security encryption scheme that converted data into ciphertext and manipulated the ciphertext just like the original text without compromising the
encryption. There are a variety of different homographic encryption types,
for example multiplicative, additive and fully homomorphic, all of which
have been applied to secure communication and storage in the cloud
(Tebaa and Hajji 2014). There are significant performance limitations
with fully homomorphic encryption schemes thus requiring optimisation
at the architectural, algorithmic, and hardware resource levels (Moore
et al. 2014).
The ubiquity of smartphones, and their dependence on cloud computing, present significant challenges for securing data at the edge, in the
cloud, and in between. Smartphones, and indeed other Internet of Things
end points, are typically resource constrained due to their form and bandwidth. As such, security methods need to be relatively lightweight. Wang
et al. (2014) propose a secure sharing scheme that envisages users uploading multiple data pieces to different clouds, and using a watermarking
algorithm for authentication of mobile users and cloud services. A key
feature of this solution is the both the security and the reduced load on the
network. Khan et al. (2014) propose a BSS (block-based sharing scheme)
cryptographic method that divides data logically into multiple blocks,
encrypting and decrypting the blocks, and reconstructing the data into
their original form. Secure Data Sharing in Clouds (SeDaSC) is another
approach to secure sharing comprising three entities—the user, a cryptographic server (CS) and the cloud (Ali et al. 2015). The CS is responsible
for encryption, decryption, key management, and access control. Yu et al.
(2015) proposed a public auditing protocol that ensures the integrity of
7 TRUSTWORTHY CLOUD COMPUTING