SS-064 Ver 1.0 (May 23)
1. SOC (Security Operations Centre) Trends
Confidential & Proprietary | 2024 CBRE Inc.
Traditionally, organisations have relied on in-house security to monitor their networks and systems for potential threats. However, the increasing complexity of IT environments and the proliferation of advanced cyber threats have made it more challenging for these teams to keep up with the latest security threats. MDR services provide organisations with access to specialised expertise and advanced tools that can help them more effectively monitor their systems and detect potential security issues.
SOAR tools are designed to help organisations automate and streamline security response processes. By using SOAR tools, organisations can quickly and efficiently respond to potential security threats, such as malware attacks or data breaches. One of the key ways that SOAR tools can automate security response activities is by providing a centralised platform for coordinating and managing the various steps involved in responding to a security incident. SOAR tools can automatically gather and analyse data from multiple sources. Examples of such sources are network devices, servers and applications. Data from these sources is amassed and used to identify potential security threats and determine the appropriate response to a specific threat or security incident.Once a potential threat has been identified, SOAR tools can automate the execution of response actions, such as isolating hosts or setting blocks on a firewall.
Security, Orchestration, Automation and Response (SOAR)
The use of artificial intelligence (AI) and machine learning (a specific subset of AI) to detect unknown threats. While traditional security monitoring tends to focus on detecting known threats, AI-powered tools can help organisations identify and respond to new and emerging threats that may not have been previously identified. For example, machine learning algorithms can analyse large volumes of security data to identify patterns and anomalies that may indicate the presence of a potential threat. This can enable organisations to proactively detect and respond to security incidents well before these threats cause significant financial, operational or reputational damage.
AI and Machine Learning
2. Virtual Patrols
The concept of virtual guard patrols is based on the approach of covering local patrols via video camera, which is operated and watched by a skilled personal out of a video monitoring center. Instead of one security guide, walking the patrol, various video cameras – in the best case dome cameras – are hooked to the monitoring center in following sequences.
The guide needs to confirm each camera action out of the monitoring center. On various screens, different patrols can be displayed. Each situation is checked for irregularities by comparing the picture with how the site should look regularly, documented by audit-proof protocols.
In case the guide recognizes an irregular person at the monitoring center through the video-system, he can react immediately, speak to the intruder via local speakers and simultaneously send the alert to the police station or security service.
3. Telematic Locks (for Transportation)
Telematics Security Locks make it possible to open locks remotely – without the use of keys. They allow a user to track the security status of the vehicle, container or items in "real time". Locks can be connected to a Telematics module located in the vehicle, container or item and meet all quality and safety standards, including the requirements of TAPA TSR and BAT V1 / V2 / V3.
This is a rapidly growing segment of the Security industry and is being heaviiy used in the transportation sector.
4. Video Analytics
There are three (3) distinct types of video analytics: Fixed algorithm analytics, Artificial Intelligence learning algorithms and Facial Recognition. Each of these processes digital video signals via an algorithm to perform a security-related function.
Fixed algorithm analytics detect suspicious behaviour caught by a video camera and alert the security personnel monitoring those cameras. Fixed algorithm analytics works by performing a dedicated task and looking for a specific behaviour – for example, someone moving in the wrong direction in a passageway
AI algorithms learn ‘on the job’ by being connected to a camera for several weeks. During this period the camera learns what is ‘normal’ and issues alerts when something happens outside of that experience.
Facial recognition works by matching points on a face with a sample stored in a database. If there’s no match, the system tries to create a new record using the best available image of the subject. Some use 3D mapping in real time, with recourse to a much larger database. A subject can also be identified via ‘faceless recognition’, where someone’s physical characteristics such as height, posture and build can be used to identify them in a crowd.
5. Autonomous Security Robots (ASR)
Autonomous Security Robots (ASR) are automated guards used to surveille and perform security tasks, combining self-driving technologies, robotics, and artificial intelligence. ASRs can patrol surveillance areas, report, monitor, investigate, and detect intruders.
Autonomous Security robots have the ability to move in complex environments, detecting and reporting anomalies in the environment. Their sensors and cameras allow them not to lose their balance, even when moving through complex terrain. With improvements in 5G networks, robots can traverse even larger and more complex areas.
Cost-Effectiveness: These automated robots are the perfect choice for organisations that need an acceleration of their Security operations and want to invest in a device that can be more cost-effective in doing a task that is too time-consuming and exhaustive.
Reduced Worker Exposure to Danger: You move from a traditional method of light curtains or safety controllers to a no-contact environment 24 / 7.
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