BY Muhammad Kazim
SUPERVISOR: Dr. Awais Shibli








Introduction
Literature Survey
Problem Statement
OpenStack
Proposed Solution and Design
Major Challenges
Roadmap
References



The core of Cloud
services, Infrastructureas-a-Service (IaaS)
model provides the
capability to provision;
Processing
Storage
Networks


In
Cloud
computing,
Virtualization is the basis
of providing IaaS.
Virtualization is benefiting
companies by reducing
their operating costs and
increasing the flexibility of
their own infrastructures.



Virtual machine (VM) is a
software container that
has its own OS, virtual
CPU, RAM and behaves
like a physical machine.
Cloud usually contains a
large number of VMs.
Every 6 seconds a new VM
in Cloud is born. 
Literature Survey
Compromised Hypervisor
 Malicious OS in attackers VM can modify
source code of hypervisor.
 Hyperjacking
 VMs can be protected from compromised
hypervisor by encrypting the VMs.
Ap1
Ap2
Ap1
VM
Ap2
VM
Hypervisor
Hardware
Jakub Szefer, Ruby B. Lee, “A Case for Hardware Protection of Guest VMs from Compromised Hypervisors in Cloud
Computing”, 31st International Conference on Distributed Computing Systems Workshops, Washington, DC, USA, 2011.
Communication between Virtual Machines
 Shared clipboard transfers data between
virtual machine and host.
◦ Could be used by malicious programs in VMs to
communicate.



VM Escape attack
Covert channels
Implement proper isolation for protection
Jenni Susan Reuben, “A Survey on Virtual Machine Security”, TKK T-110.5290 Seminar on Network
Security, 2007.
VM Storage and Restore Attacks
 VM state can be stored in a disk file to be
restored later.
 Attacker can compromise the integrity of
saved VM.
 Take hash of stored VM state and encrypt VM
before saving.
Jinzhu Kong, “Protecting the confidentiality of virtual machines against untrusted host”, International Symposium
on Intelligence Information Processing and Trusted Computing, Washington, DC, USA, 2010.




Sensitive data left on broken and sold disks.
People with access to the storage hosts can
compromise integrity and data confidentiality of
stored images.
Compromising the Cloud infrastructure can result
in customers data accessible to the attackers.
Cloud administrators such as network admin,
storage admin, virtualization admin with physical
access to Cloud can access customer data.
In order to secure virtual machines from infrastructure,
hypervisor and virtualization level storage attacks, we intend to
provide security mechanism by proposing virtual machines
image encryption based on the proposed security architecture.



OpenStack is collection of open source technology
that provides massively scalable open source cloud
computing software.
Currently a large number of organizations around
87 different countries have deployed their Cloud on
OpenStack.
OpenStack technology is written in Python with
SDKs available for java and php developers by
jcloud.






Dashboard ("Horizon") provides a web front end
to the other OpenStack services.
Compute ("Nova") stores and retrieves virtual
disks ("images") and associated metadata in
Image.
Network ("Quantum") provides virtual networking
for Compute.
Block Storage ("Cinder") provides storage
volumes for Compute.
Image ("Glance") provides catalog and repository
for disk images.
All the services authenticate with Identity
("Keystone").


Images are disk images which are templates for
virtual machine file systems. The image service,
Glance, is responsible for the storage and
management of images within OpenStack.
Instances are the individual virtual machines
running on physical compute nodes. The compute
service, Nova, manages instances. Each instance is
run from a copy of the base image.


The image store fronted by the image service,
Glance, has some number of predefined
images.
To launch an instance the user selects an
image, a flavor (resources) and optionally
other attributes.





QEMU Copy-on-write
QEMU can use a base image which is readonly, and store all writes to the qcow2 image.
Its major features include
Smaller images
AES encryption
zlib based compression
Support of multiple VM snapshots.


Virtual Machine
Size
CPU Cores
Memory
Small
1
2 GB
Medium
2
3.5 GB
Large
4
7 GB
Extra Large
8
14 GB
Encryption will result in increase in image
size and performance overhead on the Cloud
system.
Key management is another major issue.
MileStones
Duration
Preliminary study and Research
Done
Implementation
1. Python Development
2 Weeks
2. OpenStack Configuration
2 Weeks
3. Image encryption
1 month
4. Loading, executing, storing
2 months
encrypted image with VM instances
5. Key Management Policy
implementation
1 month
Performance Analysis and
Evaluation
1 month
Final Documentation
1 month
[1] Shubhashis Sengupta, Vikrant Kaulgud, Vibhu Saujanya Sharma, “Cloud Computing
Security - Trends and Research Directions”, IEEE World Congress on Services,
Washington, DC, USA, 2011.
[2] Jakub Szefer, Ruby B. Lee, “A Case for Hardware Protection of Guest VMs from
Compromised Hypervisors in Cloud Computing”, 31st International Conference on
Distributed Computing Systems Workshops, Washington, DC, USA, 2011.
[3] Jinzhu Kong, “Protecting the confidentiality of virtual machines against untrusted host”,
International Symposium on Intelligence Information Processing and Trusted
Computing, Washington, DC, USA, 2010.
[4] Farzad Sabahi, “Secure Virtualization for Cloud Environment Using Hypervisor-based
Technology”, International Journal of Machine Learning and Computing vol. 2, no. 1,
February 2012, pp.39-45.
[5] Jenni Susan Reuben, “A Survey on Virtual Machine Security”, TKK T-110.5290 Seminar
on Network Security, 2007.
[6] Seongwook Jin, Jeongseob Ahn, Sanghoon Cha, and Jaehyuk Huh, “Architectural Support
for Secure Virtualization under a Vulnerable Hypervisor”, Proceedings of the 44th Annual
IEEE/ACM International Symposium on Microarchitecture, USA, 2011.
[7] Ryan Shea, Jiangchuan Liu, “Understanding the Impact of Denial of Service on Virtual
Machines”, IEEE 20th International Workshop on Quality of Service (IWQoS), Burnaby, BC,
Canada, 2012.
[8] Wu Zhou, Peng Ning, Xiaolan Zhang, “Always up-to-date: scalable offline patching of
VM images in a compute cloud”, Proceedings of the 26th Annual Computer Security
Applications Conference, New York, USA, 2010, pp. 377-386.
[9] Trent Jaegar, Reiner Sailer, Yogesh Sreenivasan, “Managing the Risk of Covert
Information Flows in Virtual Machine Systems”, Proceedings of the 12th ACM symposium
on Access control models and technologies, New York, USA, pp. 81-90, 2007.
[10] Mikhail I. Gofman, Ruiqi Luo, Ping Yang, Kartik Gopalan, “SPARC: A security and privacy
aware Virtual Machine checkpointing mechanism”, Proceedings of the 10th annual ACM
workshop on Privacy in the electronic society, New York, USA, 2011, pp. 115-124.
[11] Zhi Wang, Xuxian Jiang, “HyperSafe: A Lightweight Approach to Provide Lifetime
Hypervisor Control-Flow Integrity” IEEE Symposium on Security and Privacy, Oakland,
CA, USA, 2010, pp. 380-385.
[12] Mohamad Rezaei et al., “TCvisor: a Hypervisor Level Secure Storage”, TCvisor: a
Hypervisor Level Secure Storage”, Internet Technology and Secured Transactions
(ICITST), London, 2010, pp. 1-9.
[13] Dan Pelleg, Muli Ben-Yehuda, Rick Harper, “Vigilant—Out-of-band Detection of
Failures in Virtual Machines”, ACM SIGOPS Operating Systems Review, New York, NY,
USA, Volume 42 Issue 1, 2008, pp. 26-31.
[14] Sandra Rueda, Rogesh Sreenivasan, Trent Jaeger, “Flexible Security Configuration for
Virtual Machines”, Proceedings of the 2nd ACM workshop on Computer Security
Architectures, New York, NY, USA, 2008, pp. 35-44.
[15] Koichi Onone, Yoshihiro Oyama, Akinori Yonezawa, “Control of System Calls from
Outside of Virtual Machines”, Proceedings of the 2008 ACM symposium on Applied
Computing, New York, NY, USA, 2008, pp. 2116-2221.
THANKYOU