Intelligent Security: Key Principles and Elements Composition

The voluminous generation of data and the rise in the significant implementation of disruptive technologies to harness its value has given a complementary push to privacy threats as well. Placing their data online is still a nightmare for some threatened by the potentials of hackers' games. Amid this cybersecurity becomes an essential part of the ecosystem to keep progressing in the digital arena without any restrictions. A number of technologies are handy today to ensure cybersecurity, however, they might not be effective equally. Where the threat is coming from various ends, cybersecurity should be strengthened further by adding several other dimensions of security technologies together. As it stands now, the corporate world is in need of intelligent security that comes from an amalgamation of different technological potentials.

Here are the elements of Intelligent Security.

The platform of intelligent security has been developed consisting of these crucial elements – log management, SIEMs, NBADs, and network forensics.

Log management is usually collective processes and policies used to administer and facilitate the generation, transmission, analysis, storage and ultimate disposal of the large volumes of log data created within an information system. SIEM that is also known as security information and event management is an approach to security management that provides a holistic view of an organization's information technology (IT) security. Today majority of SIEMs deploy multiple collection agents to gather security-related events from end-user devices, servers, network equipment and specialized security equipment like firewalls, antivirus or intrusion prevention systems. The collectors forward events to a centralized management console, which performs inspections and flags anomalies.

Further, network behavior anomaly detection or NBAD is the continuous monitoring of a network for unusual events or trends. Such program tracks critical network characteristics in real-time and generates an alarm if a strange event or trend is detected that could indicate the presence of a threat. NBAD is an integral part of network behavior analysis. Next comes risk management which is the process of identifying, assessing and controlling threats to an organization's capital and earnings. Such threats include financial uncertainty, legal liabilities, strategic management errors, accidents, natural disasters, and information technology (IT) security threats. Moreover, network forensics is the capturing, recording, and analysis of network events to discover the source of security attacks or other problem incidents. "Catch-it-as-you-can" systems capture all packets passing through a certain traffic point, store the data and perform analysis subsequently in batch mode. "Stop, look and listen" systems perform a rudimentary analysis in memory and save only certain data for future analysis.

What are the key principles of Security Intelligence?

Real-Time Analysis, Pre-Exploit Analysis, Collection, Normalization and Analysis, Actionable Insights, Scalable, Adjustable Size and Cost and Data Security & Risk are some of the key principles of the intelligent security system.

Real-time analysis means being able to understand what is happening currently across the network. It becomes critical when identifying threats. While dealing with zero-day exploits and immediate risks, solely depending on the view log record is not enough. Intelligent Security can evaluate potential present threats. Further, modern security intelligence blends pre-exploit vulnerability management with real-time analysis. Therefore, by identifying risks before they become breaches, organizations may reduce and more easily detect attacks. Collecting as much applicable data as possible from pertinent devices on the network, creating relations between those devices, and then analyzing their behavior to identify aberrant actions is the most relevant and complete method of identifying security incidents. Security intelligence is capable of fully understanding a situation, identifying the key components and surrounding information, and effectively notifying security analysts of potential threats.

As aforementioned, solely amassing, evaluating, and logging data is not enough. There is a need for more proactive security solutions like security intelligence must identify threats, remove false positives, and present potential threats to security analysts in a meaningful and comprehensive way. Moreover, previous security tools and platforms have struggled with the sheer bulk of data larger organizations need to process, security intelligence solutions, however, are designed to scale and handle these large volumes of data. They utilize purpose-built databases to gather and analyze extensive amounts of data in real-time with ease.

In terms of size and cost, cybersecurity threats are no longer limited to large companies and organizations. Today even smaller organizations require security solutions. Security intelligence does not require extensive implementation or a large organization's budget rather it is a significant change from other security solutions, which requires extensive customization, skilled personnel staffing, and large budgets. Furthermore, to maintain an organization's reputation, it is important to secure data and intellectual property from attackers. Security intelligence's main goal is to protect the data an organization has by compiling and scrutinizing as much of the data as possible.