ENHANCING THE SECURITY IN CYBER-WORLD BY DETECTING THE BOTNETS USING ENSEMBLE CLASSIFICATION BASED MACHINE LEARNING

Enhancing the security in cyber-world by detecting the botnets using ensemble classification based machine learning

With various malware, botnets are the legitimate risk increasing against cybersecurity providing criminal operations like malware dispersal, distributed denial of service attacks, fraud clicking, phishing, and identification of theft.Existing techniques used for detection of botnet, which are suitable only for specific command of botnet and protoco

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Comparison of the diagnostic performance of 64-slice computed tomography coronary angiography in diabetic and non-diabetic patients with suspected coronary artery disease

Abstract Background Diabetics have high prevalence of subclinical coronary artery disease (CAD) with typical characteristics (diffuse disease, large calcifications).Although 64-slice multidetector computed tomography (MDCT) coronary angiography has high diagnostic accuracy to detect CAD, its diagnostic performance in diabetics with suspected CAD is

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