Cloud resources modelling using smart cloud management

Chyad, Haitham Salman; Mustafa, Raniah Ali; George, Dena Nadir

doi:10.11591/eei.v11i2.3286

Cited by 5 publications

(4 citation statements)

References 23 publications

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“…26, No. 3, June 2022: 1747-1757 1748 [1]- [6]. Results show that the privacy preservation scheme that has been proposed in this research manages to protect the privacy, but those algorithms involve creation of fake transaction and the algorithm also fails to maintain the privacy related to data frequency.…”

Section: Introductionmentioning

confidence: 89%

Enhancement in privacy preservation in cloud computing using apriori algorithm

Mustafa

Chyad

Mutar

2022

IJEECS

Self Cite

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Cloud <span>computing provides advantages, like flexibly of space, security, cost optimization, accessibility from any remote location. Because of this factor cloud computing is emerging as in primary data storage for individuals as well as organisations. At the same time, privacy preservation is an also a significant aspect of cloud computing. In regrades to privacy preservation, association rule mining was proposed by previous researches to protect the privacy of users. However, the algorithm involves creation of fake transaction and this algorithm also fails to maintain the privacy of data frequency. In this research an apriori algorithm is proposed to enhance the privacy of encrypted data. The proposed algorithm is integrated with elagmal cryptography and it does not require fake transactions. In this way, the proposed algorithm improves the data protection as well as query privacy and it hides data frequency. Result analysis shows that the proposed algorithm improves the privacy as compared to previously proposed association rule mining and the algorithm also shows 3% to 5% improvement in performance when compared to other existing algorithms. This performance analysis with varying number of the data and fake transactions shows that the proposed algorithm doesn’t require fake transactions, like data privacy association rule mining.</span>

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Section: Introductionmentioning

confidence: 89%

Enhancement in privacy preservation in cloud computing using apriori algorithm

Mustafa

Chyad

Mutar

2022

IJEECS

Self Cite

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“…This is accomplished by combining cybersecurity techniques with machine learning approaches. In the early discovery and diagnosis of any medical issues, this is very helpful [10,11,12,13].…”

Section: Accept/ Rejectmentioning

confidence: 99%

Subject review: Cyber security using machine learning and deep learning techniques

Raniah Ali Mustafa,

Haitham Salman Chyad

2023

Global J. Eng. Technol. Adv.

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In order to protection computers, programs, networks and data from intrusions and unauthorised access (UA), alteration, or demolition, a set of technologies and procedures is known as cybersecurity. A significant concern is the identification and prevention of a network intrusion. Methods like machine learning & deep learning identify network intrusions through estimating risk utilizing training data. Through the years, a number of machine learning & deep learning techniques have been introduced, and it has been demonstrated that these techniques are more accurate than other network intrusion detection systems. Moreover, the most crucial research on the utilize of machine learning & deep learning in cybersecurity (CS) is summarized in this research article. The results indicate which through foreseeing and comprehending the behavior and traffic of malicious software, machine learning & deep learning methods play important roles in restricting unauthorised access (UA) to computer systems and in managing system permeation. also explains how machine learning & deep learning are utilized in cyber security for both offensive and defensive purposes, as well as how cyber-attacks on models utilizing machine learning & deep learning have been targeted.

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“…Machine learning emphasizes generalization and empirical data, but deep learning uses artificial neural networks designed to mimic the cognitive procedures of individuals [9] Up until recently, the complexity of neural networks was constrained by the computing power available Businesses can better deploy their resources because it cuts down on the time spent on repetitive tasks. In summary, deep learning can improve cybersecurity by making it simpler, more preventative, less expensive, and more efficient [10]. This, however, will only be feasible if the machine learning data supports a precise representation of the environment.…”

Section: Introductionmentioning

confidence: 99%

Subject Review: Detecting Cyber Security Attacks

Salman Chyad,

Mustafa

2023

IJASRE

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Attacks against cyber security are increasing in frequency and complexity over the years. Due to the complexity and level of sophistication that are increasing, defensive strategies need to be developed further and continuously innovated. Traditional strategies to intrusion detection and deep packet inspection continue to be utilized and suggested, but they are adequate for addressing the requirements of changing security threats. As processing power increases and the cost of doing so drops, machine learning is seen as a complementary method or additional defense against malware, botnets, and other attacks. Deep learning algorithms in particular have piqued the interest of academics recently because of their unparalleled excellent performance in many areas that depend on prediction. This study paper presented promising applications of machine learning and deep learning, a branch of artificial intelligence built on many layers of artificial neural networks, in Various kinds of security-related assignments. We describe the distinguished features of sample machine learning & deep learning architectures used in cybersecurity attacks decisively previously and comparably assessing state-of-the-art solutions from the literature. We outline necessary resources, such as a general framework for detection cyber security attacks and appropriate datasets, and we highlight the newest trends in machine learning and deep learning.

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Cloud resources modelling using smart cloud management

Cited by 5 publications

References 23 publications

Enhancement in privacy preservation in cloud computing using apriori algorithm

Enhancement in privacy preservation in cloud computing using apriori algorithm

Subject review: Cyber security using machine learning and deep learning techniques

Subject Review: Detecting Cyber Security Attacks

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