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https://issues.apache.org/jira/browse/HADOOP-8803?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xianqing Yu updated HADOOP-8803:
--------------------------------
Description:
I am a Ph.D student in North Carolina State University. I am modifying the
Hadoop's code (which including most parts of Hadoop, e.g. JobTracker,
TaskTracker, NameNode, DataNode) to achieve better security.
My major goal is that make Hadoop running more secure in the Cloud environment,
especially for public Cloud environment. In order to achieve that, I redesign
the currently security mechanism and achieve following proprieties:
1. Bring byte-level access control to Hadoop HDFS. Based on 0.20.204, HDFS
access control is based on user or block granularity, e.g. HDFS Delegation
Token only check if the file can be accessed by certain user or not, Block
Token only proof which block or blocks can be accessed. I make Hadoop can do
byte-granularity access control, each access party, user or task process can
only access the bytes she or he least needed.
2. I assume that in the public Cloud environment, only Namenode, secondary
Namenode, JobTracker can be trusted. A large number of Datanode and TaskTracker
may be compromised due to some of them may be running under less secure
environment. So I re-design the secure mechanism to make the damage the hacker
can do to be minimized.
a. Re-design the Block Access Token to solve wildly shared-key problem of HDFS.
In original Block Access Token design, all HDFS (Namenode and Datanode) share
one master key to generate Block Access Token, if one DataNode is compromised
by hacker, the hacker can get the key and generate any Block Access Token he
or she want.
b. Re-design the HDFS Delegation Token to do fine-grain access control for
TaskTracker and Map-Reduce Task process on HDFS.
In the Hadoop 0.20.204, all TaskTrackers can use their kerberos credentials to
access any files for MapReduce on HDFS. So they have the same privilege as
JobTracker to do read or write tokens, copy job file, etc.. However, if one of
them is compromised, every critical thing in MapReduce directory (job file,
Delegation Token) is exposed to attacker. I solve the problem by making
JobTracker to decide which TaskTracker can access which file in MapReduce
Directory on HDFS.
For Task process, once it get HDFS Delegation Token, it can access everything
belong to this job or user on HDFS. By my design, it can only access the bytes
it needed from HDFS.
There are some other improvement in the security, such as TaskTracker can not
know some information like blockID from the Block Token (because it is
encrypted by my way), and HDFS can set up secure channel to send data as a
option.
By those features, Hadoop can run much securely under uncertain environment
such as Public Cloud. I already start to test my prototype. I want to know that
whether community is interesting about my work? Is that a value work to
contribute to production Hadoop?
was:
I have two major goals in the project.
One is bring fine-grain access control to Hadoop. Based on 0.20.204, Hadoop
access control is based on user or block granularity, e.g. HDFS Delegation
Token only check if the file can be accessed by certain user or not, Block
Token only proof which block or blocks can be accessed. I would like to make
Hadoop can do byte-granularity access control, each access party, user or
task process can only access the bytes she or he least needed.
Second one is that make Hadoop work more secure in Cloud environment,
especially in public Cloud environment. So the communication between
hadoop's node should be protected. And if some nodes of hadoop is
compromised, the damage should be minimized (e.g. known wildly shared-key
problem of Block Access Token problem).
> Make Hadoop running more secure public cloud envrionment
> --------------------------------------------------------
>
> Key: HADOOP-8803
> URL: https://issues.apache.org/jira/browse/HADOOP-8803
> Project: Hadoop Common
> Issue Type: New Feature
> Components: fs, ipc, security
> Affects Versions: 0.20.204.0
> Reporter: Xianqing Yu
> Labels: hadoop
> Original Estimate: 2m
> Remaining Estimate: 2m
>
> I am a Ph.D student in North Carolina State University. I am modifying the
> Hadoop's code (which including most parts of Hadoop, e.g. JobTracker,
> TaskTracker, NameNode, DataNode) to achieve better security.
>
> My major goal is that make Hadoop running more secure in the Cloud
> environment, especially for public Cloud environment. In order to achieve
> that, I redesign the currently security mechanism and achieve following
> proprieties:
> 1. Bring byte-level access control to Hadoop HDFS. Based on 0.20.204, HDFS
> access control is based on user or block granularity, e.g. HDFS Delegation
> Token only check if the file can be accessed by certain user or not, Block
> Token only proof which block or blocks can be accessed. I make Hadoop can do
> byte-granularity access control, each access party, user or task process can
> only access the bytes she or he least needed.
> 2. I assume that in the public Cloud environment, only Namenode, secondary
> Namenode, JobTracker can be trusted. A large number of Datanode and
> TaskTracker may be compromised due to some of them may be running under less
> secure environment. So I re-design the secure mechanism to make the damage
> the hacker can do to be minimized.
>
> a. Re-design the Block Access Token to solve wildly shared-key problem of
> HDFS. In original Block Access Token design, all HDFS (Namenode and Datanode)
> share one master key to generate Block Access Token, if one DataNode is
> compromised by hacker, the hacker can get the key and generate any Block
> Access Token he or she want.
>
> b. Re-design the HDFS Delegation Token to do fine-grain access control for
> TaskTracker and Map-Reduce Task process on HDFS.
>
> In the Hadoop 0.20.204, all TaskTrackers can use their kerberos credentials
> to access any files for MapReduce on HDFS. So they have the same privilege as
> JobTracker to do read or write tokens, copy job file, etc.. However, if one
> of them is compromised, every critical thing in MapReduce directory (job
> file, Delegation Token) is exposed to attacker. I solve the problem by making
> JobTracker to decide which TaskTracker can access which file in MapReduce
> Directory on HDFS.
>
> For Task process, once it get HDFS Delegation Token, it can access everything
> belong to this job or user on HDFS. By my design, it can only access the
> bytes it needed from HDFS.
>
> There are some other improvement in the security, such as TaskTracker can not
> know some information like blockID from the Block Token (because it is
> encrypted by my way), and HDFS can set up secure channel to send data as a
> option.
>
> By those features, Hadoop can run much securely under uncertain environment
> such as Public Cloud. I already start to test my prototype. I want to know
> that whether community is interesting about my work? Is that a value work to
> contribute to production Hadoop?
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