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• Firewall and Antivirus Software: Using firewall and antivirus software can stop and
alert users of any suspicious activity happening on their devices. With the timely
updated versions of the same, can go a long way in ensuring data security. Firewalls
use pre-configured rules to inspect all the packets entering and exiting a network and,
therefore, help stop malware and other unauthorised traffic from connecting to
devices on a network.
• Data Masking: It obscures data so that, even if criminals exfiltrate it, they can't make
sense of what they stole. Unlike encryption, which uses encryption algorithms to
encode data, data masking involves replacing legitimate data with similar but fake
data. This data can also be used by the company in scenarios where using real data
isn't required, such as for software testing or user training.
• Training: Corporates must take up regular Data Security sessions of their staff to
sensitise them about following the data protection processes being implemented
and the importance of doing so. Making them conscious of suspicious emails,
links that they might receive, not leaving their devices unlocked when unattended,
keeping software's up to date and not sharing passwords, are some of the things
that can be taken up.
• Audits and Testing of Security System: Regular audits and testing of security policies, integrated malware
protection, firewalls, Wi-Fi connections security, Hardware-based security, checking applications security, email
security and compliance also play very important role in maintaining data privacy and providing data security.
• Other Basic Preventions: Being aware of surroundings and threats from insiders, complying with security
regulations which might be shared by entrusted agencies or bodies which track online cyber activities all across
the world are few other ways to provide cyber security.
Differences between Data Security and Data Privacy
Data Privacy Data Security
Data privacy ensures the ethical and lawful use of data. Data security ensures the protection of data from
unauthorised access and breaches.
It focuses on how data is collected, used, shared, and It focuses on safeguarding personal data, business
stored so that the rights of individuals over their data data, intellectual property, and many more from
is protected. various threats.
How are Data Security and Data Privacy related to AI?
Data security and data privacy are crucial components of Artificial Intelligence (AI).
Data Security in AI
AI systems often rely on vast amounts of data for training and operation. Unauthorised access and tampering
could lead to inaccurate AI models and compromised outcomes. Many AI applications process sensitive data,
such as personal, financial, or health-related information. Strong data security measures can stop data breaches
and unauthorised access.
Data Privacy in AI
Data privacy brings the ethical use of AI. This ensures that AI systems comply with data privacy laws and
regulations (such as GDPR, CCPA) to help protect individuals’ rights and maintain public trust. AI systems must
ensure that data is collected, shared, and used in ways that users have explicitly consented to, maintaining
transparency and trust.
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