1 00:00:00,003 --> 00:00:01,001 - [Lecturer] Welcome to this lesson 2 00:00:01,001 --> 00:00:04,001 on the Cloud Data Life Cycle, Data Dispersion 3 00:00:04,001 --> 00:00:07,002 and Data Flows. 4 00:00:07,002 --> 00:00:08,004 Since we've already been over this, 5 00:00:08,004 --> 00:00:09,005 the focus of this lesson 6 00:00:09,005 --> 00:00:11,006 will be to discuss different 7 00:00:11,006 --> 00:00:13,006 security considerations and controls 8 00:00:13,006 --> 00:00:17,001 that we're going to apply in each phase. 9 00:00:17,001 --> 00:00:21,007 We'll also briefly discuss data dispersion and data flows. 10 00:00:21,007 --> 00:00:24,000 As a reminder, the cloud secure data lifecycle 11 00:00:24,000 --> 00:00:25,008 is made up of six steps. 12 00:00:25,008 --> 00:00:30,000 These steps are create, store, use, share, archive, 13 00:00:30,000 --> 00:00:31,002 and destroy, 14 00:00:31,002 --> 00:00:33,000 and I absolutely recommend memorizing 15 00:00:33,000 --> 00:00:37,001 the order of these steps before going into your CCSP exam. 16 00:00:37,001 --> 00:00:38,003 The first step is create, 17 00:00:38,003 --> 00:00:41,002 and this is where the initial generation or modification 18 00:00:41,002 --> 00:00:45,000 of digital information takes place. 19 00:00:45,000 --> 00:00:47,007 Some activities that we might take during this phase 20 00:00:47,007 --> 00:00:49,006 are going to be data classification, 21 00:00:49,006 --> 00:00:51,008 and this refers to the process 22 00:00:51,008 --> 00:00:56,003 of assigning a security label to the data. 23 00:00:56,003 --> 00:00:59,002 For example, some labels could be public, confidential, 24 00:00:59,002 --> 00:01:02,001 secret or top secret based on both the content 25 00:01:02,001 --> 00:01:04,000 and the purpose of the data. 26 00:01:04,000 --> 00:01:08,004 This is also an important step to conduct input validation 27 00:01:08,004 --> 00:01:10,003 so that as we're collecting the data, 28 00:01:10,003 --> 00:01:12,005 we're ensuring that it meets certain criteria 29 00:01:12,005 --> 00:01:14,004 to prevent malicious input. 30 00:01:14,004 --> 00:01:18,007 This is primarily going to apply to web interfaces 31 00:01:18,007 --> 00:01:20,007 where users are inputting data 32 00:01:20,007 --> 00:01:23,001 that is eventually going to make it somewhere 33 00:01:23,001 --> 00:01:25,002 into our application. 34 00:01:25,002 --> 00:01:29,005 Step two of the data lifecycle is storing data, 35 00:01:29,005 --> 00:01:32,008 and some key requirements are going to be setting up 36 00:01:32,008 --> 00:01:35,004 that initial encryption, both in transit 37 00:01:35,004 --> 00:01:38,001 and at rest for the data. 38 00:01:38,001 --> 00:01:40,005 In this phase, we also may select 39 00:01:40,005 --> 00:01:41,008 different storage solutions 40 00:01:41,008 --> 00:01:43,006 depending on the sensitivity of the data, 41 00:01:43,006 --> 00:01:45,009 which was identified during the create phase, 42 00:01:45,009 --> 00:01:48,000 and subsequently send the data 43 00:01:48,000 --> 00:01:49,005 to the appropriate storage solution 44 00:01:49,005 --> 00:01:51,002 based on that classification. 45 00:01:51,002 --> 00:01:54,000 This is also the phase where we will determine 46 00:01:54,000 --> 00:01:57,005 and potentially apply the data retention policies, 47 00:01:57,005 --> 00:01:59,001 which is determining how long 48 00:01:59,001 --> 00:02:01,009 the data should be stored based on, once again, 49 00:02:01,009 --> 00:02:05,002 the classification and the purpose of the data. 50 00:02:05,002 --> 00:02:08,005 Step three is where we use the data, 51 00:02:08,005 --> 00:02:11,007 and similarly, it's important during this step 52 00:02:11,007 --> 00:02:14,003 that we have robust encryption 53 00:02:14,003 --> 00:02:16,001 and that we're effectively identifying 54 00:02:16,001 --> 00:02:20,001 and enforcing access controls for both people 55 00:02:20,001 --> 00:02:23,002 and systems that might be accessing this data, 56 00:02:23,002 --> 00:02:25,002 and then auditing the activities 57 00:02:25,002 --> 00:02:28,006 that take place when they do access it. 58 00:02:28,006 --> 00:02:31,009 Another useful thing we can do during the use phase is, 59 00:02:31,009 --> 00:02:34,006 depending on exactly how and why we're using it, 60 00:02:34,006 --> 00:02:37,000 you can also apply data masking, 61 00:02:37,000 --> 00:02:38,007 which is a practice of displaying 62 00:02:38,007 --> 00:02:40,005 only a portion of the sensitive data 63 00:02:40,005 --> 00:02:44,009 and removing the fields which may be considered sensitive 64 00:02:44,009 --> 00:02:47,003 if they're not actively required for the task 65 00:02:47,003 --> 00:02:49,001 being accomplished. 66 00:02:49,001 --> 00:02:51,001 The next step is sharing, 67 00:02:51,001 --> 00:02:52,008 where we will be granting data access 68 00:02:52,008 --> 00:02:55,004 to other users or entities. 69 00:02:55,004 --> 00:02:57,007 The most important aspects of this phase 70 00:02:57,007 --> 00:02:59,005 are going to be making sure that we're effectively 71 00:02:59,005 --> 00:03:03,003 authenticating and authorizing users and systems 72 00:03:03,003 --> 00:03:05,005 that are sharing the data, 73 00:03:05,005 --> 00:03:07,007 as well as applying encryption in transit 74 00:03:07,007 --> 00:03:10,000 for the data moving between systems, 75 00:03:10,000 --> 00:03:12,008 using protocols like SFTP and HTTPS 76 00:03:12,008 --> 00:03:15,003 to securely share the data. 77 00:03:15,003 --> 00:03:18,000 This might also be a phase where we determine 78 00:03:18,000 --> 00:03:20,005 and apply data usage agreements, 79 00:03:20,005 --> 00:03:24,000 such as requiring third parties to agree to terms 80 00:03:24,000 --> 00:03:26,003 about how the data is going to be used. 81 00:03:26,003 --> 00:03:28,004 The next step is archiving, 82 00:03:28,004 --> 00:03:30,007 and this is where we are storing data long-term 83 00:03:30,007 --> 00:03:33,003 for compliance or historical purposes. 84 00:03:33,003 --> 00:03:35,006 Similar to that initial store phase, 85 00:03:35,006 --> 00:03:37,002 some activities that will take place here 86 00:03:37,002 --> 00:03:40,000 is going to be determining what our solution is going to be 87 00:03:40,000 --> 00:03:42,008 for this long-term storage. 88 00:03:42,008 --> 00:03:45,007 And cold storage is a common term you might hear 89 00:03:45,007 --> 00:03:47,008 for referring to data solutions 90 00:03:47,008 --> 00:03:50,007 that are expressly designed for archival data. 91 00:03:50,007 --> 00:03:52,004 Some other activities we can do here 92 00:03:52,004 --> 00:03:55,002 are going to be conducting regular data integrity checks 93 00:03:55,002 --> 00:03:59,001 to validate that nothing has changed about the data. 94 00:03:59,001 --> 00:04:00,005 And then a special point I want to make 95 00:04:00,005 --> 00:04:03,003 is that in situations where, 96 00:04:03,003 --> 00:04:04,005 we've discussed throughout the course 97 00:04:04,005 --> 00:04:06,000 how important cryptography 98 00:04:06,000 --> 00:04:09,001 and specifically key management is in the cloud 99 00:04:09,001 --> 00:04:11,002 and in general, and specifically when it comes 100 00:04:11,002 --> 00:04:14,003 to archiving data, you should always consider 101 00:04:14,003 --> 00:04:16,008 how you are going to manage the key material 102 00:04:16,008 --> 00:04:19,003 that's used to encrypt your data 103 00:04:19,003 --> 00:04:21,001 and ensuring that the lifecycle assigned 104 00:04:21,001 --> 00:04:24,004 for the key is at least as long as the lifecycle 105 00:04:24,004 --> 00:04:26,002 of the data you are archiving. 106 00:04:26,002 --> 00:04:28,008 In fact, a key aspect of key management 107 00:04:28,008 --> 00:04:31,004 is tracking the existence of that key material 108 00:04:31,004 --> 00:04:35,002 through each of these phases of the data lifecycle. 109 00:04:35,002 --> 00:04:38,002 Okay, and the last phase is going to be destroy. 110 00:04:38,002 --> 00:04:40,007 This is where we are securely erasing our data 111 00:04:40,007 --> 00:04:43,000 once it's no longer needed. 112 00:04:43,000 --> 00:04:46,000 The goals of this phase are to ensure a permanent deletion 113 00:04:46,000 --> 00:04:51,000 of the data in a way that meets security requirements, 114 00:04:51,000 --> 00:04:53,003 and once again, it's very unlikely in a cloud environment 115 00:04:53,003 --> 00:04:56,006 that you will gain physical access to destroy disks 116 00:04:56,006 --> 00:04:58,008 where your data is written. 117 00:04:58,008 --> 00:05:01,005 So, we can use mechanisms such as crypto shredding 118 00:05:01,005 --> 00:05:03,007 to ensure that our data is unreadable, 119 00:05:03,007 --> 00:05:06,006 even if it's still written to a disc. 120 00:05:06,006 --> 00:05:09,002 Next up, let's talk about data dispersion. 121 00:05:09,002 --> 00:05:12,008 This is the concept of breaking up data into smaller chunks 122 00:05:12,008 --> 00:05:15,003 for diversified storage. 123 00:05:15,003 --> 00:05:17,001 So, you can imagine if this puzzle right here 124 00:05:17,001 --> 00:05:19,005 is a coherent set of data, 125 00:05:19,005 --> 00:05:23,000 then we're breaking it up into distinct portions 126 00:05:23,000 --> 00:05:26,003 and storing it on different drives. 127 00:05:26,003 --> 00:05:27,006 And compared to on-premises, 128 00:05:27,006 --> 00:05:31,004 this is very similar to the concept of RAID striping, 129 00:05:31,004 --> 00:05:35,007 but it's tailored specifically for cloud environments. 130 00:05:35,007 --> 00:05:36,006 Along with this, 131 00:05:36,006 --> 00:05:41,000 there's also something called erasure coding, 132 00:05:41,000 --> 00:05:43,006 and this is comparable to RAID'S parody bit, 133 00:05:43,006 --> 00:05:47,003 where if there's a failure of a disc that causes us 134 00:05:47,003 --> 00:05:51,002 to lose some portion of our original data, 135 00:05:51,002 --> 00:05:54,001 that mathematical calculations can be applied 136 00:05:54,001 --> 00:05:56,008 to the segments that are retained, 137 00:05:56,008 --> 00:06:00,001 which allows us to recover the lost data. 138 00:06:00,001 --> 00:06:01,008 Of course, this is not the algorithm applied, 139 00:06:01,008 --> 00:06:05,003 but meant to represent the application 140 00:06:05,003 --> 00:06:08,004 of complex mathematical calculations. 141 00:06:08,004 --> 00:06:11,002 Some benefits of this setup are going to be enhancing 142 00:06:11,002 --> 00:06:15,006 overall data availability as well as increased security 143 00:06:15,006 --> 00:06:17,009 since no complete set of usable data 144 00:06:17,009 --> 00:06:20,004 is available on a single device. 145 00:06:20,004 --> 00:06:24,000 However, it can become a complication 146 00:06:24,000 --> 00:06:27,001 for compliance considerations, 147 00:06:27,001 --> 00:06:30,003 especially in countries that require sensitive data 148 00:06:30,003 --> 00:06:33,004 to be retained within the country. 149 00:06:33,004 --> 00:06:36,002 There's also a possibility for some potential latency 150 00:06:36,002 --> 00:06:38,005 with data dispersion. 151 00:06:38,005 --> 00:06:41,009 Okay, finally, we'll talk about data flows. 152 00:06:41,009 --> 00:06:44,004 A data flow is a mapping of data movement 153 00:06:44,004 --> 00:06:47,003 in modular application architectures. 154 00:06:47,003 --> 00:06:50,001 The cloud has allowed us to build advanced systems 155 00:06:50,001 --> 00:06:52,004 that are modular in design, 156 00:06:52,004 --> 00:06:54,005 which offer things like faster development, 157 00:06:54,005 --> 00:06:58,007 faster deployment, and independently scalable features. 158 00:06:58,007 --> 00:07:01,008 However, sometimes these new modern designs 159 00:07:01,008 --> 00:07:05,001 have led to reduced visibility. 160 00:07:05,001 --> 00:07:07,000 In some cases, organizations can struggle 161 00:07:07,000 --> 00:07:09,004 to pinpoint exact data locations, 162 00:07:09,004 --> 00:07:13,005 routes, and open ports and services of systems. 163 00:07:13,005 --> 00:07:16,005 So, one of the things that we can build to help regain 164 00:07:16,005 --> 00:07:17,009 some of that system visibility 165 00:07:17,009 --> 00:07:20,007 are going to be data flow diagrams. 166 00:07:20,007 --> 00:07:22,002 And this is a very simple example, 167 00:07:22,002 --> 00:07:27,003 but in a data flow diagram, the purpose is to focus on 168 00:07:27,003 --> 00:07:30,001 the direction and content of data that is flowing 169 00:07:30,001 --> 00:07:33,002 through our independent systems, where maybe in this case, 170 00:07:33,002 --> 00:07:37,003 a set of users is accessing a front-end web application, 171 00:07:37,003 --> 00:07:40,002 and then that web application is communicating via an API 172 00:07:40,002 --> 00:07:42,009 to a back-end database. 173 00:07:42,009 --> 00:07:46,004 In this case, a data flow diagram should focus on 174 00:07:46,004 --> 00:07:48,008 which systems are communicating with other systems 175 00:07:48,008 --> 00:07:50,001 and what the content is 176 00:07:50,001 --> 00:07:53,008 and should be of those communications. 177 00:07:53,008 --> 00:07:56,003 In summary, in this lesson we talked about the cloud data 178 00:07:56,003 --> 00:07:57,009 lifecycle and some security 179 00:07:57,009 --> 00:08:00,005 and controls that we might apply during each phase 180 00:08:00,005 --> 00:08:03,003 of the cloud data lifecycle. 181 00:08:03,003 --> 00:08:05,006 We then talked about the concept of data dispersion 182 00:08:05,006 --> 00:08:07,004 as well as data flows 183 00:08:07,004 --> 00:08:10,003 and the importance of building data flow diagrams 184 00:08:10,003 --> 00:08:12,000 alongside our architectural diagrams.