FEATURE : CYBER SECURITY mindful of the existing tools and technologies in their environment . security even more critical .
As organisations digitise more aspects of their operations , the attack surface expands , requiring more nuanced and comprehensive security strategies .
Integrating diverse security technologies and systems poses significant challenges including interoperability issues , increased complexity and potential security gaps . However , it also offers opportunities for creating more comprehensive and layered security postures .
Effective integration can lead to better data correlation , unified threat intelligence and streamlined incident response processes . Organisations must carefully plan and execute integration strategies , often leveraging security frameworks and standards to ensure compatibility and effectiveness .
Internal challenges
Economic factors significantly impact decision-making in the security industry . Budget constraints can limit the ability to invest in the latest security technologies and hire skilled personnel . Market demand influences what security solutions can be prioritised and developed .
Ethical considerations in the security market include privacy concerns , the potential for misuse of surveillance technologies and the responsibility of protecting user data . Developers and providers of security solutions must ensure that their products do not infringe on individual rights or contribute to unjust practices .
Transparency , accountability and the ethical use of AI and data are paramount . Companies must also navigate the ethical implications of balancing security with user convenience and accessibility .
The Cisco approach
Thamsanqa Mbangata , Cybersecurity Business Development Manager , Comstor Southern Africa
Organisations often have to balance between cost and the level of security , opting for solutions that provide the best value . Economic downturns can lead to increased cyberthreats , as adversaries exploit weakened defences , making strategic investment in
AI and ML are pivotal in addressing security challenges by automating threat detection , analysis and response . They can analyse vast amounts of data to identify patterns and anomalies that might indicate a security threat . Machine Learning models continuously improve
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