With threats on the rise and breaches getting more sophisticated, organizations need to re-evaluate their security strategy. Security starts with identity and access management since people are your most vulnerable resource. Protecting their identity is a pre-requisite to safeguarding your data.
Identity analytics incorporates machine learning to take identity protection to the next level. It spots any anomalous activity in your network by forming a baseline for normal behavior and detecting any deviation. Identity analytics helps to reveal hidden vulnerabilities like insider threats and compromised accounts in your network. Privilege abuse is one instance of insider threats that could be easily detected by monitoring administrative user actions and noting deviation in volume or timing of activities.
This way, stepping up your security game with identity analytics will keep your organization secure from identity thefts and data breaches.
Regular security information and event management (SIEM) tools are great for compliance and auditing, but the threat detection capabilities are, for the most part, rule based.
However, sophisticated attacks can be detected easily using user behavior analytics techniques. With machine learning-enabled intelligent analysis on collected logs, you can separate the abnormal activities from usual behavior to highlight threats. This way, suspicious events can be easily detected and investigated.
With an identity-analytics-powered SIEM solution, the logs collected can be used to intelligently filter out real-time threats. SIEM tools can help generate instant alerts based on the findings from these analytics.
In conclusion, while SIEM tools definitely keep your network secure, identity analytics turns it up a notch to ensure you stay ahead of advanced attacks.
Identity analytics incorporates machine learning in log analysis to derive meaningful insights from events occurring in the network. The logs collected on a daily basis help form a baseline for each user or entity. Now that the system understands the "normal" behavior for a particular user or entity, any deviation in the volume, time, or nature of activities are singled out.
Machine learning algorithms compare the regular behavior to these deviations for instant threat detection. This way, the baseline for each user or entity is different, unlike regular auditing methods that establish a common baseline for everyone and everything in the network.
For example, Bob's regular logon time may be at 4 AM, although that isn't during business hours. If he logs on at say, 2 PM, which is irregular as it pertains to him, it will be flagged as unusual behavior.
This way, suspicious activities are spotted and singled out of enormous chunks of logs without any human intervention. This analysis can be presented to the administrator for further investigation to rule out potential breaches.
The term identity governance and administration (IGA) gained prominence in 2013 once Gartner merged its earlier two Magic Quadrant (MQ) categories to form an MQ for IGA. IGA is a combination of two frameworks: identity governance and identity administration. Identity governance is a set of policies that define activities such as logging, reporting, segregating duties, and managing roles. Identity administration deals with activities such as the administration of accounts and passwords, managing entitlements, and access provisioning.
By combining these domains, an IGA system allows companies to stay compliant with regulations like the GDPR and HIPAA, automate the workflow of managing access requests, and monitor at all times if the right set of users have the right amount of permissions.
Although many parallels can be drawn between identity and access management (IAM) and identity and access governance (IGA), they are quite different in the areas they cover. IAM focuses on managing passwords and leveraging automated workflows to create and disable user accounts, assign permissions, deal with access permissions, and more. IGA, on the other hand, is a broader framework inside which IAM resides.
IGA encompasses everything that IAM covers, plus additional capabilities such as auditing and generating reports to meet compliance requirements, monitoring privileged actions in your organization, and certifying access permissions to make sure that the just-in-time and just-enough access principles are upheld. In short, IGA adds an additional layer of intelligent governance on top of IAM.
In a well-managed IGA program, access decisions are based on identity, which is the foundation for security. The first step in establishing a successful IGA program is to identify all user identities and determine what information they can access.
With user identities as the foundation for your IGA strategy, building access policies based on user accounts becomes easier and can be easily changed based on the organizational unit (OU) and group memberships of the users, ensuring just-in-time and just enough access to required resources.
Any change in an account access policy begins right from the password policies and password privileges that the user has, including the ability to reset or change their password remotely via VPN, utilize two-factor authentication for privileged accounts, and leverage single sign-on to enterprise applications protected by multi-factor authentication. If user identities do not form the foundation of your IGA strategy, it becomes difficult to set and modify access policies for your organization.
The digital identity of a user determines their access to an organization's network and data. With the advent of hybrid, mobile and BYOD - identities have become the new perimeter protecting your network. Organizations should focus on strongly safeguarding their identities. This can be achieved through a strong identity security strategy employing an efficient and granular identity and access management (IAM) solution, which can help organizations control how users access data and applications.
As any admin will tell you, a compromised user identity can be devastating — especially when you consider the modern user identity that is spread across a huge variety of resources.
Remember, even if you have implemented network and perimeter security solutions, without a security-centric IAM you may as well be leaving the key to your IT environment in the door for attackers to take advantage of.
No. Additional layers of authentication and biometrics have improved the authentication process, and although technology around passwords has come a long way, at the core, authentication through passwords largely remains unchanged. Here are two reasons why biometrics can't completely replace passwords.
a) Passwords are either completely right or completely wrong “Passwords” and “Passw0rds” may seem similar, but to an authentication system, these passwords are vastly different. Authentication through a password succeeds only if the end user has the password exactly right. There is virtually no margin for error, and no system will mistake one password for another.
However, the same cannot be said for biometric authentication systems. A biometric password only has to be good enough for authentication to succeed. Biometric systems often have to accept a margin of error; if they did not, even legitimate users at times would have trouble accessing the network. Unless biometrics become 100% fool proof, passwords are here to stay.
b) Passwords are anonymous The good thing about passwords is they don’t contain rarely contain any personal information that could be used to identify an individual. In case of a breach, it’s unlikely that an attacker will be able to trace your password back to you. You can simply change the password and be done with it. The same cannot be said with biometrics. Once your biometric information is breached, that’s it—there’s no changing your fingerprints, face, or eyes.
Data Access Governance (DAG) is a practice that deals with unstructured data. Unstructured data is any file that is created by users such as spreadsheets, documents, and presentations. In recent times, employees share critical information as unstructured data simply because it is easier to share information this way. However, apart from the clear security risk associated with this practice, it also leads to compliance issues.
DAG aims to tackle these problems. Using strong DAG practices, organizations can ensure that:
Modern businesses run on data, so it's necessary to manage its access and visibility. The following are the best practices for data access governance.
A Data Access Governance system can complement an organization's identity and access management system. IAM deals with managing user identities and their access rights to applications and sensitive information based on the roles and responsibilities assigned to the user identity.
What gets left out here is the management of access rights to unstructured data. As sensitive information stored in unstructured data keeps increasing, it becomes more important to include unstructured data in this equation as well.
This is where DAG comes into play. DAG systems first identify all the unstructured data in an organization. Then, using the same basis as IAM, i.e. user identities, these systems can decide which users can access certain files.
So, in combination, IAM takes care of ensuring that the right type of roles, responsibilities, and privileges are assigned to a user identity, while DAG takes care of ensuring that these user identities are given permission to see, access, or modify only the unstructured files necessary based on their privileges.
Hybrid infrastructures offer businesses the flexibility to continue operating their on-premises applications while embracing cloud-based digital transformation. Though the hybrid infrastructure has various advantages, the lack of right capabilities can make managing it challenging.
The three major challenges faced by organizations using a hybrid setup are:
Securing identities and data access Organizations lack the capability to streamline and manage identities and user access across hybrid environments during the user life cycle. Often, employees retain access permissions across critical business processes even after termination. This lack of a central identity and access management platform can critically damage the security posture of hybrid environments.
Ensuring compliance and IT governance Organizations often lack IT governance capabilities such as defining and assigning granular roles for stakeholders, enforcing a policy of least privilege, segregation of duties for privileged accounts, etc. from a centralized platform. Without these capabilities, businesses will find it difficult to ensure IT regulatory compliance, and may end up paying millions of dollars in fines.
Lack of comprehensive visibility Another major challenge is checking for suspicious activities and data accesses across cloud and on-premises environments. Without a central monitoring capability,
threats can enter and remain undetected in an environment for many months. Only complete visibility into both environments can help in faster threat detection and response.
To overcome routine hybrid IAM challenges, organizations need a comprehensive tool that offers the following capabilities:
Streamlined user life cycle management IAM best practices require organizations to automate user provisioning and deprovisioning tasks to ensure that every user has the right amount of access. To achieve this, admins need tools that can automatically create user accounts from HR databases, and add them to appropriate groups based on their roles. The tools should also strip the users' permissions when necessary and remove them automatically when a user leaves the organization.
Single sign-on (SSO) Single sign-on capabilities eliminate the need for end users to remember multiple passwords, and prevent them from entering credentials multiple times to log in to different applications. To enhance the user experience, organizations need a tool that provides seamless access to all the enterprise applications through SSO without compromising on security.
Intelligent threat alerts to overcome alert fatigue Unlike tools that provide alerts for all events, organizations now need tools that leverage machine learning (ML) techniques. With ML-based user behavior analytics (UBA), admins don't have to sift through tons of alerts to zero in on threats; instead, UBA creates a baseline of typical user behavior specific to each user, then detects anomalous user behavior and threats quickly and accurately.
Total visibility on AD, Azure AD, and file servers Admins need a tool that provides insights into all the changes happening in Active Directory (AD), Office 365, Windows Server, Exchange Server, and more from a central platform. This will help them track critical events such as user logon and log off activities, files and folder accesses and changes, folder permission changes, and devices connected to thwart attacks faster.
Prebuilt compliance reports Organizations need long-term access to audit information to meet compliance regulations that require several years' worth of data, and need a tool with comprehensive out-of-the-box reports that can make compliance auditing easy.
Most organizations have set up alerts for the events happening in their IT environment. Admins have to sort through thousands of these notifications daily, make sense of them, and initiate appropriate action. In a hybrid environment, admins are overwhelmed with messages from both their on-premises and cloud environments.
When security professionals are overwhelmed with alerts, it becomes difficult to scrutinize all the alerts and determine their priority.
One effective solution for admins to overcome this challenge is to use tools that leverage machine learning (ML). ML-based tools can analyze all the information contained in the logs generated by user activities, and compare it with a dynamic baseline of each user's typical activities. These tools then generate alerts if there is an anomaly in user behavior. In this way, user behavior analytics (UBA) breaks through the noise of false positives and provides actionable recommendations to admins.
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