This comprehensive survey paper offers a panoramic exploration of the dynamic realm of
cybercrime policing, encompassing a wide spectrum of intricacies from cybercrime …

Phishing is an identity theft, which deceives Internet users into revealing their sensitive data,
eg, login information, credit/debit card details, and so on. Researchers have developed …

Detecting anomalies in data is a vital task, with numerous high-impact applications in areas
such as security, finance, health care, and law enforcement. While numerous techniques …

Machine learning (ML) based malicious traffic detection is an emerging security paradigm,
particularly for zero-day attack detection, which is complementary to existing rule based …

Blacklists are commonly used to protect computer systems against the tremendous number
of malware threats. These lists include abusive hosts such as malware sites or botnet …

We investigate the emergence of the exploit-as-a-service model for driveby browser
compromise. In this regime, attackers pay for an exploit kit or service to do the" dirty work" of …

Significant recent research advances have made it possible to design systems that can
automatically determine with high accuracy the maliciousness of a target website. While …

Malware remains one of the most significant security threats on the Internet. Antivirus
solutions and blacklists, the main weapons of defense against these attacks, have only been …

Machine learning has been widely applied to building security applications. However, many
machine learning models require the continuous supply of representative labeled data for …

In technical support scams, cybercriminals attempt to convince users that their machines are
infected with malware and are in need of their technical support. In this process, the victims …