最终用户可以更快地缓解零日攻击

Vivek Bardia, Crs Kumar
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引用次数: 2

摘要

过去的十年向我们展示了网络空间的力量,我们也越来越依赖它。该领域的指数级发展同样吸引了技术的攻击者和捍卫者。这个不可避免的领域也导致了人类平均意识和知识的增加。当我们看到攻击变得越来越复杂时,保护程序一直是缓解攻击的一个步骤。对各种威胁检测、保护和缓解系统的研究向我们揭示了一个共同点,即用户被完全忽视,或者系统严重依赖用户输入才能正常运行。综合以上内容,我们设计了一项研究,其中除了独立的检测和预防系统外,还采用了用户输入来识别和减轻风险。这种方法使我们得出结论,用户的参与成倍地增强了机器学习,并更快地分割数据集以获得更可靠的输出。
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End Users Can Mitigate Zero Day Attacks Faster
The past decade has shown us the power of cyberspace and we getting dependent on the same. The exponentialevolution in the domain has attracted attackers and defenders oftechnology equally. This inevitable domain has led to the increasein average human awareness and knowledge too. As we see theattack sophistication grow the protectors have always been a stepahead mitigating the attacks. A study of the various ThreatDetection, Protection and Mitigation Systems revealed to us acommon similarity wherein users have been totally ignored or thesystems rely heavily on the user inputs for its correct functioning. Compiling the above we designed a study wherein user inputswere taken in addition to independent Detection and Preventionsystems to identify and mitigate the risks. This approach led us toa conclusion that involvement of users exponentially enhancesmachine learning and segments the data sets faster for a morereliable output.
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