CISOs Harness Machine Learning to Combat Ransomware

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CISOs are increasing their use of machine learning and data analytics tools to combat the rising threat of ransomware attacks, according to a new survey. The research, conducted by Evaluator Group on behalf of Index Engines, found that more than two-thirds of CISO respondents plan to embrace new technology to detect suspicious activity, particularly ransomware activity, over the next year. The top analytics requested include earlier detection of ransomware corruption and support for faster discovery of the last clean backup.

Jim McGann, Vice President of Business Development and Marketing at Index Engines, emphasized the critical role of machine learning and analytics in the fight against cyber criminals. As ransomware attacks become increasingly sophisticated and evade traditional security tools, machine learning and analytics can analyze data, delve deep into files, and make informed decisions about whether they have been corrupted or are safe for recovery.

The survey also highlighted the challenges faced by CISOs in detecting attacks and finding the last known good copy of data for recovery. With minimal recovery expected to take hours and full recovery taking weeks or even months, valuable data is often lost due to malicious corruption. Currently, security professionals lack the in-house ability to conduct deep forensic analysis and determine the best recovery strategies. Only 11% of respondents indicated they have all the necessary capabilities from their current vendors.

To address these challenges, two-thirds of the respondents plan to add data analytics and/or machine learning tools to detect suspicious activity. Additionally, more than half of the CISOs plan to incorporate data loss prevention software and tools for continuous monitoring of malicious software. Other popular choices for bolstering cybersecurity measures include audit data for sensitive content and data forensics analysis for post-ransomware attacks.

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The survey also revealed that cybersecurity budgets are increasing to combat the growing sophistication of ransomware attacks. In fact, 84% of respondents reported that their cybersecurity budget is increasing this year. While 49% of budgets are increasing by up to 10%, only 12% anticipate an increase of more than 25%. Additionally, only 4% of respondents stated that their cybersecurity budget is decreasing.

The full report, which provides more insights into the data management challenges faced by CISOs, can be accessed via the link provided. By embracing machine learning and data analytics tools, CISOs are taking proactive steps to mitigate ransomware risks and protect valuable data from malicious corruption.

Frequently Asked Questions (FAQs) Related to the Above News

Why are CISOs increasing their use of machine learning and data analytics tools?

CISOs are increasing their use of machine learning and data analytics tools to combat the rising threat of ransomware attacks, as traditional security tools are increasingly being evaded by sophisticated ransomware attacks.

What are the top analytics requested by CISOs?

The top analytics requested by CISOs include earlier detection of ransomware corruption and support for faster discovery of the last clean backup.

What role do machine learning and analytics play in the fight against cyber criminals?

Machine learning and analytics can analyze data, delve deep into files, and make informed decisions about whether they have been corrupted or are safe for recovery, helping detect and combat ransomware attacks.

What challenges do CISOs face in detecting attacks and finding the last known good copy of data for recovery?

CISOs face challenges in detecting attacks and finding the last known good copy of data for recovery, often resulting in valuable data being lost due to malicious corruption. They lack the in-house ability to conduct deep forensic analysis and determine the best recovery strategies.

What steps are CISOs taking to address these challenges?

Two-thirds of CISOs plan to add data analytics and/or machine learning tools to detect suspicious activity. They also plan to incorporate data loss prevention software, tools for continuous monitoring of malicious software, and other measures such as audit data for sensitive content and data forensics analysis.

How are cybersecurity budgets being affected by the growing sophistication of ransomware attacks?

The survey revealed that cybersecurity budgets are increasing, with 84% of respondents reporting an increase this year. While 49% of budgets are increasing by up to 10%, only 12% anticipate an increase of more than 25%, and only 4% stated that their cybersecurity budget is decreasing.

Where can I access the full report?

The full report, which provides more insights into the data management challenges faced by CISOs, can be accessed via the link provided.

Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.

Kunal Joshi
Kunal Joshi
Meet Kunal, our insightful writer and manager for the Machine Learning category. Kunal's expertise in machine learning algorithms and applications allows him to provide a deep understanding of this dynamic field. Through his articles, he explores the latest trends, algorithms, and real-world applications of machine learning, making it accessible to all.

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