Q What were some spam filtering techniques used before the introduction of ML techniques Home, - What were some spam filtering techniques Question - The past decade has seen the gradual growth in the use of machine learning in cyber security to protect users from cyber-attacks. As they go about their day, users are quietly protected by several security features on their devices. When you use Gmail, Google automatically scans every email to determine if it is spam. Comment on the use of machine learning algorithms for spam detection. What were some spam filtering techniques used before the introduction of ML techniques for spam detection? Justify the statement, "Spam detection is perhaps the classic example of pattern recognition" Answer - Machine learning algorithm are used in the detection of the spam emails. Naïve bayes is the popular algorithm of the machine learning which is being used in the detection of spam emails. Random forest algorithm is also used in the detection of the spam. Support vector and the K nearest algorithm is also used in the detection of the spam emails. The data is extracted and the meta data is collected then, the messages are generalized. The machine learning algorithms are applied and spam text data and the information about the spammer is generated. Spam filtering techniques The first technique is the content based filtering techniques in which occurances of the words and the phrases as well as the distribution of the words and the phrases were analyzed. Then, this content was divided into the two categories named as the spam and the non spam. The second technique for spam filtering is case base spam filtering technique. In this, spam filtering is done on the basis of the training the system for classification. The third technique is the Rule based spam filtering technique in which the messages in the email are segregated into the spam or the non spam category based on some pre defined rules. Spam detection is instance of pattern recognition because there are many predictable set of the features in the in the spam and algorithm is trained in order to identify the spam and the non spam content. The words and the phrases are analyzed in this and the pattern is detected in order to detect the spam content. Related: Define and discuss malware analysis What were some spam filtering techniques Identify vulnerabilities to gain access to systems Write a report on Cyber Attacks Classification What is Conti ransomware
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