Taking Identity and Access Management (IAM) to the next level with a data security approach

Sonit Jain, CEO, GajSheild Infotech

By Sonit Jain, CEO, GajShield Infotech

Accomplished cyber-attackers create newer online threats relentlessly. As companies have increasingly digitised their operations and storage databases, their sensitive data is vulnerable to such threats. This is where effective data security in Identity and Access Management (IAM) enters the fray. Currently, many organisations secure their access and identity systems in one conventional way or another.

Such organisations can take their data protection protocols to the next level by using these hyper-effective solutions:

Context-aware data security

Companies use Multi-Factor Authentication (MFA) systems to secure confidential information in their networks. The security cushion in these systems for sensitive data comes in the form of two or more levels of identification for access-seeking users. Usually, the identification credentials are in the form of user passwords, security questions, numerical codes, patterns and biometric details. Worryingly, unauthorised users may be capable of accessing sensitive company data if they provide these details to the MFA systems.

As an idea, context-related security focuses on basing decisions on the when, what, why, who and where behind user requests for system access. Context-based security systems intend to provide access to the right users and closely monitor behavioural patterns to verify whether such users are performing tasks specific to their respective designations or not. Hence, it makes sense for organisations to secure each level of their MFA identification systems with contextual data security.

Identity as a service (IDaaS)

To strengthen data connectivity across the board, organisations can adopt the Software as a Service (SaaS)-enabled IDaaS. The basic utility of IDaaS is that it allows individuals to use a single sign-on (SSO) authentication to secure access to an entire suite of company software and applications within the organisation. In that sense, IDaaS implementation at the workplace is driven more by convenience than security requirements. However, the enhanced connectivity also means that tightening of security controls is easier to achieve for all the company systems and software applications at once.

In addition to seamless connectivity, IDaaS enhanced with context-aware security can be applied to cloud-based files and folders to safeguard the virtual information stored within the database of the organisation.

Data protection and Internet of Things (IoT)

IoT consists of multiple devices in either workplace or domestic settings linked by an advanced connective tissue of Artificial Intelligence (AI). It is increasingly being utilised in its various forms across different environments. In an organisation, IoT systems can be attacked in four ways:


  • Unauthorised access to communication lines between devices and servers
  • Life-cycle attacks during user-to-maintenance transition
  • Malicious activities to corrupt IoT software
  • Physical targeting of the IoT chips

Data security in IoT is ensured in a few ways, such as deploying advanced cryptography to prevent unauthorised data access. Tamper prevention and mitigation techniques are used to protect chip-related physical attacks. Isolation measures can be adopted to prevent software damage and data compromise.

AI-assisted intelligent firewalls

On the surface, intelligent firewalls do not appear much different from their regular counterparts. Differences between regular and intelligent firewalls are more pronounced internally. Typically, the level of data security provided by a regular firewall depends on the information it receives from network administrators.

AI plays a significant part in diversifying an intelligent firewall’s identification and protection capabilities against various types of threats that cannot be handled by static firewalls. Apart from possessing information about pre-defined malicious activities, detection engines can allow the security systems to find newer threats in a company’s data network.

Identity analytics for behavioural data tracking

Identity analytics, along with User and Entity Behaviour Analytics (UEBA) monitor the network activities of users. Over a period, the data security systems ‘learn’ the behavioural patterns of different users within an organisation. The system collects this data by using several resources such as AI, machine learning, and cognitive system analytics, among others. The sources of the details mainly consist of the access governance files stored by the organisation. Other information sources include IoT and blog databases.

Firstly, the network administrators set the rules in the system to receive warnings whenever there is a break from regular behaviour by users. For example, company employees logging in at unusual times or visiting potentially malicious websites are recorded. Security Identity Event Management (SIEM) tools are used to constantly monitor user activities regarding firewalls, servers, and anti-virus software, amongst others. The data security system prepares a detailed report with this information for security analysis.

Cloud-based data security

As we know, organisations are swiftly moving towards cloud-based data storage and operations. Therefore, it is essential for them to secure virtual databases with acceptable levels of user access protection. Context-based data security systems such as intelligent firewalls help in providing secure IAM in such cloud networks.

Generally, the cloud-based storage and processing of data in organisations are provided by third-party vendors. Such service providers need to create efficient data security and frameworks to ensure that unauthorised users are denied entry into the organisation’s databases. IAM in cloud systems performs a few main actions:

  • Restricting data viewing and editing
  • Create conditional access for users based on operational designations
  • Track user behaviour continuously

Customer Identity Access Management (CIAM)

CIAM systems are used to store customer data and identity details. It also serves the purpose of restricting customer access within certain services and applications. CIAM systems provide a host of features such as customer registration, user identity management, consent and preference management, SSO, MFA, directory management and identity governance.

CIAM systems adopt a context-aware approach to data security and can be implemented on cloud-based networks, IDaaS and IoT. These security systems achieve their prime objectives of enhancing customer experience through simple and attractive user interfaces while also preventing a compromise of user’s data.


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