Absolutely. And if such byte level security is inbuilt into the product, and data access is isolated, which also means hacks can be isolated too, then it becomes easier for us to sell the idea to the Hospitals CIOs and CSOs. Let’s hear what our folks here have to say about it too.
Regards//K -----Original Message----- From: Xianqing Yu [mailto:yuxian...@gmail.com] Sent: Thursday, September 13, 2012 12:04 PM To: Kingshuk Chatterjee; common-dev@hadoop.apache.org Cc: Peng Ning Subject: Re: Make Hadoop run more securely in Public Cloud environment Hi Kingshuk, Thank you for your interesting. I think you make a very nice example. If Healthcare company push their data to public cloud, the byte-level access control can minimize the data every party can get (e.g. task process). So even one task process or TaskTracker is hacked, the information loss can be minimized. Another feature is also very help to this scenario. Currently all NameNode and DataNodes are sharing the same key to generate Block Access Token. If the hacker get the key by hacking any one of HDFS machine, she or he potentially can read everything in the HDFS and impact is huge. So I re-design that to make sure that, if hacker success to attack one machine, he or she can only get what is on this machine, not others in the cluster. And also secure channel (encrypted channel) to transfer data can be another security bonus. Thanks, Xianqing -----Original Message----- From: Kingshuk Chatterjee Sent: Thursday, September 13, 2012 2:23 PM To: 'Peng Ning' Cc: yuxian...@gmail.com Subject: RE: Make Hadoop run more securely in Public Cloud environment Hi Xianqing - I am a systems architect and a consultant for Healthcare industry, and the first impression I get from your email below is that the byte level security can be a very helpful feature in securing patient's health information (PHI), and assuring the healthcare service providers to take steps to push their data to public cloud. I will be happy to contribute in anyway, let me know. Regards//K Kingshuk Chatterjee Director, Technology Consulting -------------------------------------------------------------------------------- 5155 Rosecrans Ave, Suite 250 http://www.calance.com Hawthorne, CA 90250 ' +1-(412 606 8582) -----Original Message----- From: Xianqing Yu [mailto:yuxian...@gmail.com] Sent: Thursday, September 13, 2012 11:19 AM To: common-dev@hadoop.apache.org Cc: Peng Ning Subject: Make Hadoop run more securely in Public Cloud environment Hi Hadoop community, 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? I created JIRA for the discussion. https://issues.apache.org/jira/browse/HADOOP-8803#comment-13455025 Thanks, Xianqing
