Mastering Data Security and DSPM Strategies for Enterprise Protection

hello everyone and thank you for tuning in today's webinar where we'll be covering how to master data security with a deep dive into data security posture management or dspm my name is Nick iSell I'm the global head of brand journalism and the head of Tech Trends and insights at HCL Tech and I'm delighted to be joined today by Amit misra Global head data security and data privacy practice cyber security hcltech and nckl gar senior director data security security.ai before we get into the questions I'd just like to set some context and remind our audience to submit questions for a Q&A at the end we will try and get through as many of the questions as possible before the end of the webinar so the proliferation of cloud data is growing at petabyte scale and with data breaches On The Rise safe regarding this data has never been more critical how can organizations address this grown concern well a new category of tools dspm might have the answer enabling organizations to place controls on data that's in the cloud or on premise systems our panelists will delve into this topic and highlight some of the challenges organizations are facing while exploring how you can apply some learnings to overcome these challenges to drive effective Enterprise data security Amit and nil will discuss the current state of data in the Enterprise why securing data is Paramount and why this is a challenge and how dspm delivers benefits and value right so on to the discussion the first question is why is managing data in the cloud challenging for companies and what are the common pain points that you're hearing from customers and could we hear from you first please hey to start with thanks Nick for having me here I'm really looking forward to this discussion uh you hear me well right absolutely sure thank you so so back to your question on uh challenges that you asked about for Claud most to the most part I think the the nature of problem seems quite similar to that what we saw in on Prem environment except that the scale is 10 times primarily because the data has just exploded and other challenge which is quite evident is cloud is evolving by the minute and it looks like that every time and every day when you look at your architecture it looks like it is aging much faster it is getting dated then if if I were to give you top three shoes are very quickly you know just off my head I can talk about that very first one is there are no surprises we are still talking about compliance has many shoes and it just that the cloud is kind of making it much more complicated than it was in the on Prem environment and mostly because your data is not being monitored or rather managed by a third party and most of the time you don't know what lies under the hood and therefore you know that that unknown kind of makes it a little bit of uh challenging for the Enterprises uh second part is mostly and I think this is the characteristic which bothers most of us is the democratization of security along with the infr end data okay that is kind of a defining feature of the cloud let me explain what I mean because I can very easily I I believe confuse people when I say that you know this is something that bothers us what I mean to say is while on the surface it looks like the responsibilities are clearly defined between who does v the service provider what the uh Enterprise and customer do but if you think about it the developers have not got the controls and they can they spin the machines by the minutes and unfortunately they are the one who Define the configuration SEC configurations for their machine and when they are doing it dynamically you know tons of machines every day right there you have a problem you're at at your hand and they most of the time they miss out on some of the other configuration and there you go all the breaches kind of you know attributed to that if you think I'm exaggerating just do a little bit of Google search and then realize that almost every cloud security incident is attributed to that uh so that is what I think on top of my head Nick that's great thank you Nick Hill do you have any kind of insights into why managing datering cloud is challenging for companies and and what are the common pain points you're hearing I think Amit some kind of all the macro challenges really well uh only thing I'll add is like add the data perspective right um so I think scalability truly has become a huge issue uh if you look at the numbers 2013 we CL uh in 2013 had close to 9 zabt of data in the world today we have around 110 zabt and that is projected to go up to 175 zabt in the next two years so we we're going to be adding almost as much data in the next two years as we did in the last 10 years so that exponential growth really explains the common problem that every single organization is facing and Technologies like cloud is really make it even more SC complicated as I was saying uh compliance being another area just just another interesting data point I was looking at um the numbers 127 different countries have different global data protection and privacy laws so imagine the complexity for a small or for a global organization as you move as you you have Global Supply chains you have business with data moving across the globe right you have to understand the nuances and interpret each law even within us even different states have those laws so that creates a lot of complexity um macro level what I would say is like all of these challenges ultimately boil down to four areas of kind of pain points for customers uh Amit alluded to security and that is going to be the topic today data privacy becomes another huge concern compliance as we discussed and governance of data right uh I think being able to as ath you mentioning like democratization of data like balancing that need in terms of how do you kind of manage all your obligations but at the same time enable your teams to use that data that is the number one question every single organization is asking as we hear like gen is kind of the board level topic every single CEO is bringing that up to enable J you need data so you want to that is the core purpose of collecting data how do you get your teams to use data in a safe manner so having playing that Balancing Act is the number one kind of Challenge on everybody's mind that's great and so with this increas in scale and complexity what are the most common issues faced by security teams when actually protecting the data Amit could you uh start us off please you mean protecting the data in the cloud right yes so yeah so I would say that uh I mean I I say it every day so therefore I I remember this answer so it's like you know I would say bringing in homogenity in the way Securities handle in a inherently heterogeneous environment okay that was a mouthful but let me elaborate a little on that as you know that most of the service point out to that fact that most of the customers use at least 50 SAS applications multiple cloud service providers and all and all of them come with their own native security controls and features so it so happens is that uh you know for the security team most of the uh developers and Cloud security rather the cloud Architects tend to use those kind of native features which does its job fine for that in ironment but issue for the security architecture and security manager is that they now lack the visibility of what kind of controls are being configured in these individual environments that in fact is a very big issue when you come to think of it okay as as a security manager now secondly once you know that how do you know that whatever is being configured is in line with your information security policy and once you know that and there will be different methods whether they are simple or complicated so cumbersome or whatever but once you know that the third and key challenge is keeping an eye on the sensitive data usage so uh like what uh I think he nikel brought out one good point that I had missed out earlier privacy along with security so we do have some kind of accountability and obligations toward the data that we are using and these different Cloud providers when they're using this data unless and until you have got a very good view on what kind of data what obligation now it's being used I believe your security architecture is not doing its job so that is kind of some of what I think and just just last point I would like to add to that is when I'm talking about you know kind of this kind of distributed kind of scenario where different SCI providers or csps are giving their own native controls uh think from their perspective from for for them the school is quite narrow from them the scope is limited to that SAS environment or that cloud environment that they are providing but from security architect's perspective that doesn't cut so what they have to do is they definitely need a mechanism which can centrally orchestrate all these controls which can provide the kind of insights that they need on their fingertips they should not be running around Pillar To Post to find out what exactly is happening so that is what I think about the challenges that they need to address thanks Amit and nickel do you have anything to add to that point yeah I certainly want to uh add to the visibility challenge Amit was alluding to and almost every single conversation we we are having with kind of data security admins is like their paino is when they log into AWS aure whichever Cloud they're using the paino is not what they see in the console not the data that they see but what what are they not seeing so that that dark data and the shadow data system like so so many organizations are in the tail and they're still migrating to the cloud and many applications haven't been modernized uh uh companies are running MySQL mongod DBS and VMS in the cloud and those systems don't show up in the console so they're ungoverned unmanaged by how do you find those and even within all the systems that you have discovered or hidden um there's sensitive data that's hidden U and like but organizations depending on the segment and vertical we talking to we see somewhere between 40 to 90% dark data it's it's a massive massive problem and all those systems contain uh kind of sensitive data elements and if your RDS system gets exposed as a result of a misconfiguration or a MySQL system that you did not know about or some Legacy data with base with logs it doesn't matter right it's it's equally uh dangerous so that that deep level of visibility and getting the context around sensitive data is very very important and again context also varies what we often uh people hear from customers is like help me make decisions right that is what context really means don't just thrw me a bunch of dashboards and give me so much data points but what do I do with that help me kind of Drive decisions and that quickly leads to kind of a controls conversations how do I operationalize technical controls Amit you were mentioning misconfigurations and um uh I was just having a conversation with one of the cus they have done a cnap implementation Cloud native application protection platform they have they found close to 21,000 misconfigurations and the team is kind of going nuts like what do we do with this it's going to take us months if not years to go fix them and kind of rally our developers to go fix those problems they need a prioritization mechanism okay where is sensitive data what are the most critical systems where I can truly assess risk based on other dimensions such as laws and penalties and other kind of obligations so that risk prioritization becomes critical same for Access Control uh we've been talking about zero trust and leas privilege for years but how do you really operationalize that it's it's an strategy architecture becomes very very challenging so uh teams are looking for okay can you give me a granular way that doesn't get into way of my developers I don't want to blindly block access to my teams from using data just because I'm implementing zero trust so how do you kind of handle that friction between teams um and issues go goes on like data in motion how do you kind of prioritize risk so it's a long list of conversation ultimately it comes down to how do you use the context around data to kind of prioritize your controls I think that is what really everybody wants to figure out thank you and so you've both mentioned a lack of visibility a lack of context Legacy data why do you feel the current state of cloud security architecture is not good enough enough for data security an amalgamation of all those issues I'm sure and more what gaps are the customers trying to fill Amit would you like to answer first sure Nick so I think one of the challenge I I think is probably because uh there is a tendency of tendency to cloudify your existing security architecture so you have lots of existing investment and suddenly you start migrating to cloud and you start you know you decided to just kind of use it and extend it to cloud and see what happens uh but it doesn't always work and I will give you I think I will extend the point that nckl was saying just a minute back and that's a fantastic example for this point we are talking about lots of dark data now when you talk about dark data in our on PR environment it has entirely different connotation it has a different kind of meaning the moment you talk about Cloud architecture it has en enely different meaning and which was not a problem when we were completely at on Prem now now connect this point with uh the earlier point of what I was talking about the Legacy security architecture so if my security architecture is still addressing to that Legacy Enterprise architecture it so happens is suddenly it finds that this is completely out of depth for this kind of issues now most of our existing Investments were to enable a w Garden so we're bound countes were defined they were M around our you know Fort Fortress and all and that is what we are trying to enable but what cloud ended up doing was it completely changed that thinking and the and the new mantra was mostly about democratization of the data which me one key key tenet of that is a Freer collaboration and usage of the data which is just what just the opposite of what we are doing in the earlier world so when that happens definitely the first point any you know it's pure purely common sensical it it is quite evident that that old architecture is not going to work here so we with with I think if I know I if I succeeded in kind of conveying that point I think what essentially I'm trying to say is the the the point that is missing here is we need to First appreciate some of the key characteristics of cloud environment and these characteristics are first of all your infrastructure your data and your complete inventory is not static anymore it is completely Dynamic the kind of machine data Everything Changes by the day so that is very first point that we need to see and second thing we need to see is the there was clear segregation in earlier world who manages infra who manages data who manages the code who manages the security that somehow is blurring out now we need to appreciate these two key points and that is something that the new security architecture needs to C to and uh yeah I mean I I guess this and along with the increased risk surface that is something that we most commonly hear from the customer which I mean I have very strong opinion about that point as well uh which I feel that you know mostly when we talk about increase race surface that that problem is uh to an extent right but not that much as most of the people like to think I mean we have a tendency to think that cloud is inherently riskier than on Prem and with that thinking it looks like your risk surface has incre increased uh which may not necessarily be true but that for another day I think these are the three points that I wanted to convey across thank you Amit and and nickel just before we move on to the solution to this data security problem uh do you want to add anything on the current gaps that customers are trying to F at the moment yeah I want to add actually a couple of examples uh to uh amit's point right like why is the kind of Legacy architecture not extending and um this is very important because uh in cyber security we always have a especially from a vendor side we have kind of a tendency to bring new solutions to small use cases but if keeping our customer lens what we forget is like okay our organizations are dealing with so many different tools cesos and many of those projects that were kind of tools that were procured two years back they're just getting implemented now now right and then you talk about these newer Technologies new categories coming and like from an practitioner standpoint it can be overwhelming okay why do I need this um but in some cases there are real gaps in some cases like you may not need something um let's say take the example of data security still many organizations are implementing DLP tools but if you think about okay what what benefit are you getting right it is certainly helping with exfiltration kind of detection on the kind of on Prem side giving you some visibility on the structure side structured data side but there's a lot of unstructured data okay how do you get coverage around that um can you scale your DLP to your Cloud environment lot of those Solutions were not written to kind of manage pedabytes of data that is another challenge organizations are facing the other piece is um the classification uh techniques itself a lot of the older DLP tools were kind of reject Bas rule Bas detection mechanisms um but data especially unstructured data to like it is very hard to differentiate whether it's you're looking at a social security number whether it's a skew number that context is not always so you you want to figure out a way that can reduce false positive just one example of how um some of the older Technologies which are good enough are not extending to the modern world um same thing applies to like you have casb and sspm solutions all of those have have a critical role but if you think about the macro lens um you still have a visibility massive visibility Gap in terms of data that sits in public clouds um another challenge that we see is okay okay you solve for the security in the public Cloud but what about can you have a consistent mechanism so you have to look at that architecture and from the lens set okay hey how can you simplify it for your team how can you make it easy to operationalize tooling because uh it's not just about getting the best tool out there in the market but also being can your team actually operationalize it I think that is very very important um so we have to keep that balance view of Technology Innovation as well as practical implementation

Channel: Securiti

Views: 68

Keywords: Data Security, DSPM, Enterprise Security, Cybersecurity, Risk Mitigation, Compliance, Webinar, zero trust, data loss prevention, insider risk

Id: e_FG5QEWnJ0

Length: 20min 5sec (1205 seconds)

Published: Mon May 13 2024