Cryptography based Techniques of Encryption for Security of Data in Cloud Computing Paradigm

Rajab, Adel D.; Aqeel, Sehrish; Reshan, Mana Saleh Al; Ashraf, Awais; Almakdi, Sultan; Rajab, Khairan

doi:10.14445/22315381/ijett-v69i10p201

Cited by 4 publications

(5 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…• We build a stacked SVM-based deep learning framework for an association rule method using the cryptographic blocks given. • We demonstrate that our approach can provide a better level of privacy than most recent research (12,21,22) . Furthermore, we comprehensively demonstrate the security of our approach using multiple datasets.…”

Section: Our Contributionsmentioning

confidence: 79%

“…In this encryption section, the Elgamal encryption method is used with 2160 and 1024-bits modulus form. For privacy comparison (21) and (22) papers encryption method is used. Our proposed method is having high level security when compared with double crypto encryption (21) and some other non-privacy methods (22) .…”

Section: Security Analysismentioning

confidence: 99%

“…For privacy comparison (21) and (22) papers encryption method is used. Our proposed method is having high level security when compared with double crypto encryption (21) and some other non-privacy methods (22) .…”

Section: Security Analysismentioning

confidence: 99%

See 2 more Smart Citations

Two Level Privacy Preserving Model for Association Rule Mining in Cloud Using Deep-SVM Method

Mangayarkkarasi

2024

IJST

View full text Add to dashboard Cite

Background/Objectives: It is becoming more common for data owners to outsource data mining tasks and storage to cloud service providers as a result of the rising costs of maintaining IT infrastructures for large-scale data mining. This trend, however, also raises security concerns about unauthorized breaches of data confidentiality and outcome integrity. Methods: This research considers this scenario in which cloud user can encrypt their data and store it to cloud environment. In order to perform mining operation, the user needs to outsource the task to cloud servers. Then, the cloud server performs the mining task on the encrypted data and share the encrypted association rule to the cloud user. Yet, existing single cloud server systems have privacy leakage issues since their work focuses on either database privacy or item privacy. To remedy this gap in the literature, this study maintains both database privacy and item privacy during the frequent itemset mining process. For item privacy, it first describes a universal safe multiplication protocol with a single cloud server. We build the inner product rules, comparison rules, frequent itemset protocol, and final association rule mining process that is secure against privacy leaking on top of this multiplication protocol. During this Association Rule Mining (ARM) operation, it provides two level of protection to data privacy. This model is designed with distributed Elgamal cryptosystem and sub-protocols for item and database privacy along with Deep learning-based Support Vector Machine (SVM) for secure rule generation. Findings: The proposed method is named as two-level privacy preserving method association with Deep SVM model (2-level:D-SVM), provides guaranteed solutions to the confidentiality of the outsourced cloud data and minimizes the user interaction during association rule mining task. Here, data on breast cancer and heart disease are used, and the effectiveness of the proposed model is demonstrated by comparison to existing models. According to the study, at 25000 transactions, the proposed 2-level:D-SVM model stands for 52% and 50% more efficient than Parallel Processing (PP) and Privacy-preserving Collaborative Model Learning (PCML) techniques in terms of computing cost. Additionally, the proposed model performs 34%, 22%, 6%, and 4% better in terms of execution time https://www.indjst.org/

show abstract

Section: Our Contributionsmentioning

confidence: 79%

Section: Security Analysismentioning

confidence: 99%

See 1 more Smart Citation

Two Level Privacy Preserving Model for Association Rule Mining in Cloud Using Deep-SVM Method

Mangayarkkarasi

2024

IJST

View full text Add to dashboard Cite

show abstract

“…A ciphertext attack is when an attacker obtains information about encrypted ciphertext and attempts to deduce the secret key used for encryption and decryption. Maria Imdad et al (2020) and Wei Feng et al (2018) addressed this attack using DNA security schemes, demonstrating its durability and energy-efficient storage capabilities successfully 51 .…”

Section: Dna Security and Different Kinds Of Attacksmentioning

confidence: 99%

“…In a chosen plaintext attack, the attacker can select plaintext and observe its corresponding ciphertext. 2018) addressed this attack using DNA security schemes, demonstrating its durability and energy-efficient storage capabilities successfully 51 .…”

Section: Plain Text Attack (Pta)mentioning

confidence: 99%

DNA encoding schemes herald a new age in cybersecurity for safeguarding digital assets

Aqeel,

Khan,

Khan

et al. 2024

Sci Rep

Self Cite

View full text Add to dashboard Cite

With the urge to secure and protect digital assets, there is a need to emphasize the immediacy of taking measures to ensure robust security due to the enhancement of cyber security. Different advanced methods, like encryption schemes, are vulnerable to putting constraints on attacks. To encode the digital data and utilize the unique properties of DNA, like stability and durability, synthetic DNA sequences are offered as a promising alternative by DNA encoding schemes. This study enlightens the exploration of DNA’s potential for encoding in evolving cyber security. Based on the systematic literature review, this paper provides a discussion on the challenges, pros, and directions for future work. We analyzed the current trends and new innovations in methodology, security attacks, the implementation of tools, and different metrics to measure. Various tools, such as Mathematica, MATLAB, NIST test suite, and Coludsim, were employed to evaluate the performance of the proposed method and obtain results. By identifying the strengths and limitations of proposed methods, the study highlights research challenges and offers future scope for investigation.

show abstract

Comprehensive Review and Analysis of Cryptography Techniques in Cloud Computing

Sasikumar,

Nagarajan

2024

IEEE Access

View full text Add to dashboard Cite

Cloud computing is a fast-growing industry that offers various online services, including software, computing resources, and databases. Its payment model is usage-based, whereas consistency is based on resource-sharing. Cloud storage is popular among individuals and businesses because it reduces cost, increases productivity, boosts performance, and improves security. However, cloud computing comes with security risks as data are stored with third-party providers, and Internet access limits visibility and control. Effective data security and data protection are key issues compared with traditional on-premise computing. There are several methods for ensuring data security in the cloud, of which cryptography is the most important. Cryptography offers a range of security features including authentication, confidentiality, integrity, and availability. However, a thorough examination of the different cryptography methods in a single study is lacking. This study comprehensively examined different cryptography methods, including deoxyribose nucleic acid (DNA), elliptic curve, homomorphic, hybrid, lightweight, and novel methods. The analysis addresses their methodology, algorithms, results, applications, and limitations and provides valuable suggestions for data security in the cloud. This paper proposes the use of elliptic curve cryptography (ECC) to ensure safe communication and lightweight cryptography for Internet of Things (IoT) devices with limited resources. This emphasizes the benefit of combining asymmetric security with symmetric efficiency in hybrid cryptography.

show abstract

Cryptography based Techniques of Encryption for Security of Data in Cloud Computing Paradigm

Cited by 4 publications

References 19 publications

Two Level Privacy Preserving Model for Association Rule Mining in Cloud Using Deep-SVM Method

Two Level Privacy Preserving Model for Association Rule Mining in Cloud Using Deep-SVM Method

DNA encoding schemes herald a new age in cybersecurity for safeguarding digital assets

Comprehensive Review and Analysis of Cryptography Techniques in Cloud Computing

Contact Info

Product

Resources

About