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1. 1
5/02/2024 Data Security in Cloud Computing
Department of Artificial Intelligence & Machine Learning
Data Security In Cloud Computing
Presented by
Bellamkonda Manasa 3BR20AI014
A
Technical seminar
on
Dr. C N Shariff
Professor
Dept. of AIML
Under the Guidance of
Dr.Mallikarjuna A.
Asst HOD & Seminar Coordinator
Dept. of AIML
Dr. B.M Vidyavathi
Head of the Department
Dept. of AIML

2. 1. Introduction
2. Basics of Data Security
3. Data Security Issues
4. Mitigation Measures
5. Machine Learning for Data Security
6. Conclusion
7. References
5/02/2024 Data Security in Cloud Computing 2
Contents

3. Cloud computing refers to the delivery of computing services over the
internet.
Data security in cloud computing refers to the measures and practices to
protect sensitive information stored and processed in the cloud from
unauthorized access.
Therefore, it is essential to implement robust data security measures to
protect data in the cloud.
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Introduction

4. 5/02/2024 Data Security in Cloud Computing 4
Basics of Data Security
• Life Cycle of Data - Create, Store, Use, Share, Archive and Destroy
• Important properties of the data - Confidentiality, Integrity, and Availability(CIA triad)
• Authentication, authorization, and nonrepudiation are the other three important properties
associated with people who access the data.

5. 1.Data Breach Cycle
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Data Security Issues
• Reconnaissance
• Initial Access
• Privilege Escalation
• Lateral Movement
• Data Exfiltration
• Maintaining Access
• Covering Tracks

6. 5/02/2024 Data Security in Cloud Computing 6
Data Security Issues
2. Data Loss
• Accidental or intentional deletion, corruption, or destruction of data.
• GitLab, a web-based DevOps lifecycle tool (2017).
3. Insufficient Access Controls
• Access controls determine who can access what resources and under what
conditions.
• In 2017, it was discovered that a misconfigured Amazon S3 bucket belonging
to a third-party vendor exposed millions of Verizon customer records,
including names, phone numbers, and account PINs, to the public internet.

7. 4. Insecure Authentication
• Insecure authentication mechanisms in cloud computing can result in
unauthorized access.
• Weak passwords and lack of multi-factor authentication (MFA) can
compromise user credentials.
• In 2012, Dropbox suffered a security breach where hackers used stolen
passwords from other websites to access Dropbox accounts.
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Data Security Issues
5. Inadequate Encryption
• Inadequate encryption practices expose data to risks during storage,
transmission, or processing within the cloud environment.
• In 2014, celebrities’ iCloud accounts were hacked due to weak passwords
and inadequate data encryption.

8. 5/02/2024 Data Security in Cloud Computing 8
Mitigation Measures

9. 5/02/2024 Data Security in Cloud Computing 9
Mitigation Measures - Encryption
Symmetric Encryption
• Advanced Encryption Standard (AES)
• Data Encryption Standard (DES)
Asymmetric Encryption
• Uses a pair of keys - public key and private key
• Rivest-Shamir-Adleman(RSA) and Elliptic Curve
Cryptography(ECC).

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Mitigation Measures – Authentication and Identity Security
Multi-factor authentication Single sign-on

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Mitigation Measures – Managing Access Control
• Access management is vital to ensure the security of
cloud computing.
• Organizations can implement access control through a
variety of methods, including
• Role-Based Access Control (RBAC)
• Attribute-Based Access Control (ABAC)

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Mitigation Measures – Safe Deletion and Backing Up Data
Safe Deletion
• This is crucial for ensuring that data is properly removed and cannot be
recovered after it is no longer needed or is considered sensitive.
• Safe deletion techniques securely erase data from cloud storage and
preventing unauthorized access to residual data.
• Techniques – Cryptographic erasure, Data wiping
Backing Up Data
• One of the best methods to prevent data loss is to back up your data
to the cloud.
• Cloud data backups should be performed frequently and consistently.

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Mitigation Measures - Intrusion Detection Systems (IDS)
Intrusion Detection Architecture[1]
• IDS monitors network activity and prevents unauthorized access, data breaches, and other
security incidents.
• Types of IDS: Host-based Intrusion Detection and Network-based Intrusion Detection.

14. Support Vector Machine (SVM)
• SVM is a supervised learning algorithm that is effective in
classifying and detecting anomalies in data.
• It is used for intrusion detection and malware detection.
5/02/2024 Data Security in Cloud Computing 14
Machine Learning for Data Security
Random Forest
• Random Forest is an ensemble learning method that constructs a
multitude of decision trees during training and outputs the mode of
the classes as the prediction.
• It is used for classification and anomaly detection.

15. Data security in cloud computing is essential for protecting
sensitive information and meeting regulatory requirements. While
cloud solutions offer scalability and efficiency, they also introduce
risks such as data privacy concerns, and potential connectivity
issues. To address these challenges, businesses should carefully
select reputable cloud providers with strong security measures and
compliance certifications. Implementing encryption, access
controls, and regular data backups are critical to ensuring data
integrity and disaster recovery.
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Conclusion

16. [1] T. Ali, M. Al-Khalidi, and R. Al-Zaidi, "Information Security Risk Assessment Methods in Cloud Computing:
Comprehensive Review," Journal of Computer Information Systems, pp. 1-28, Mar. 29, 2024. doi:
10.1080/08874417.2024.2329985
[2] N. Akhtar, B. Kerim, Y. Perwej, A. Tiwari, and S. Praveen, "A Comprehensive Overview of Privacy and Data Security
for Cloud Storage," Int. J. Sci. Res. Sci. Eng. Technol., 2021. doi: 10.32628/IJSRSET21852
[3] I. Zulifqar, S. Anayat, and I. Kharal, "A Review of Data Security Challenges and their Solutions in Cloud Computing,"
I.J. Information Engineering and Electronic Business, vol. 3, pp. 30-38, Jun. 2021. doi: 10.5815/ijieeb.2021.03.04
[4] U. A. Butt et al., "A Review of Machine Learning Algorithms for Cloud Computing Security," IEEE Access, vol. 8, pp.
142776-142796, 2020. doi: 10.1109/ACCESS.2020.3014413
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References

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