S-box design based on optimize LFT parameter selection: a practical approach in recommendation system domain

Beg, Saira; Ahmad, Naveed; Anjum, Adeel; Ahmad, Mansoor; Khan, Abid; Baig, Faisal; Ahmed, Mansoor

doi:10.1007/s11042-019-08464-6

Cited by 16 publications

(19 citation statements)

References 42 publications

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“…From the remaining 60% (3/5) studies, one study proposed a HE-based scheme to secure mobile app usage data (Xu et al , 2018). The second study used s-box encryption to secure data transmission between the mobile device and the recommendation server (Beg et al , 2020). They used app usage frequency: app installs log, mobile calls, and SMS frequency, contact list and recommendation list.…”

Section: Slr Process and Resultsmentioning

confidence: 99%

“…We selected the most relevant papers including G-E-4 (Xu et al , 2018), G-SP-5 (Beg et al , 2020) and G-ACM-2 (Gao et al , 2020) in the mobile app recommendation domain. The first relevant study (Xu et al , 2018) proposed two privacy-preservation schemes for two different settings of the mobile app recommendation, i.e.…”

Section: Important Studies and Future Research Dimensionsmentioning

confidence: 99%

“…The second selected study (Beg et al , 2020) proposed the data-in-transit encryption scheme to secure the data between mobile devices and service providers during transmission. In this study, the authors argued that existing privacy and security-based mobile app recommendation studies usually assumed a secure communication channel as discussed in the above study (Xu et al , 2018) where such an assumption sometimes may not be true in different scenarios.…”

Section: Important Studies and Future Research Dimensionsmentioning

confidence: 99%

“…Yet it provides a privacy-preservation-based data collection scheme for mobile CDR and app usage data in the mobile app recommendation domain. The other repeated studies are Xu et al (2018) and Beg et al (2020) which are already discussed in Section 3. After reading the abstract of the selected papers, article Xu et al (2020) discussed DP solutions for recommendation systems but they tested their proposed method on the MovieLense dataset.…”

Section: Threats To Validity (Ttv)mentioning

confidence: 99%

See 3 more Smart Citations

Data usage-based privacy and security issues in mobile app recommendation (MAR): a systematic literature review

Beg

Khan

Anjum

2021

LHT

Self Cite

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PurposeSimilarly, Zhu et al. (2014) and Zhang et al. (2014) stated that addressing privacy concerns with the recommendation process is necessary for the healthy development of app recommendation. Recently, Xiao et al. (2020) mentioned that a lack of effective privacy policy hinders the development of personalized recommendation services. According to the reported work, privacy protection technology methods are too limited for mobile focusing on data encryption, anonymity, disturbance, elimination of redundant data to protect the recommendation process from privacy breaches. So, this situation motivated us to conduct a systematic literature review (SLR) to provide the viewpoint of privacy and security concerns as mentioned in current state-of-the-art in the mobile app recommendation domain.Design/methodology/approachIn this work, the authors have followed Kitchenham guidelines (Kitchenham and Charters, 2007) to devise the SLR process. According to the guidelines, the SLR process has three main phases: (1) define, (2) conduct the search and (3) report the results. Furthermore, the authors used systematic mapping approach as well to ensure the whole process.FindingsBased on the selected studies, the authors proposed three main thematic taxonomies, including architectural style, security and privacy strategies, and user-usage in the mobile app recommendation domain. From the studies' synthesis viewpoint, it is observed that the majority of the research efforts have focused on the movie recommendation field, while the mainly used privacy scheme is homomorphic encryption. Finally, the authors suggested a set of future research dimensions useful for the potential researchers interested to perform the research in the mobile app recommendation domain.Originality/valueThis is an SLR article, based on existing published research, where the authors identified key issues and future directions.

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Section: Slr Process and Resultsmentioning

confidence: 99%

Section: Important Studies and Future Research Dimensionsmentioning

confidence: 99%

Section: Important Studies and Future Research Dimensionsmentioning

confidence: 99%

Section: Threats To Validity (Ttv)mentioning

confidence: 99%

See 2 more Smart Citations

Data usage-based privacy and security issues in mobile app recommendation (MAR): a systematic literature review

Beg

Khan

Anjum

2021

LHT

Self Cite

View full text Add to dashboard Cite

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“…Yousaf et al [23] used the action of finite Abelian group to construct an S-box with almost optimal features. An effective approach based on optimize linear fractional transformation is presented in [24]. Jamal et al in [25] presented a novel technique based on the LFT and improved chaotic Tent-Sine system (TSS) to construct an S-box.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Generation of Strong Substitution-Boxes Based on Coset Graphs and Symmetric Groups

et al. 2020

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The success of AES encryption standard created challenges for the cryptographers to construct strong substitution-boxes using different underlying approaches. It is because they are solely responsible to decide the robustness of cryptosystem against linear and differential cryptanalyses. With an aim to fulfill the mentioned requirement of robustness, a novel group theoretic and graphical method is proposed to construct S-box with optimal features. Firstly, a strong S-box is generated with the help of orbits of coset graphs and the action of proposed powerful permutation of symmetric group S 256 . In addition, a specific group is designed the action of whose pairs of permutations has the ability to generate as many as 462422016 strong S-boxes. Few of such proposed S-boxes are reported and assessed against standard performance parameters to validate the effectiveness of proposed findings. The features of proposed S-boxes are compared with most of the recent S-boxes to validate the superior performance. Moreover, they are also applied for image encryption to demonstrate their suitability for multimedia security applications.

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Construction of a non-degeneracy 3D chaotic map and application to image encryption with keyed S-box

Wang

Liu

Zhao

2023

Multimed Tools Appl

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S-box design based on optimize LFT parameter selection: a practical approach in recommendation system domain

Cited by 16 publications

References 42 publications

Data usage-based privacy and security issues in mobile app recommendation (MAR): a systematic literature review

Data usage-based privacy and security issues in mobile app recommendation (MAR): a systematic literature review

A Novel Method for Generation of Strong Substitution-Boxes Based on Coset Graphs and Symmetric Groups

Construction of a non-degeneracy 3D chaotic map and application to image encryption with keyed S-box

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