Using Spamming Botnets: Signatures and Characteristics

Among various cyber threats, a DDoS attack is one of the major Internet threats that can affect anyone and even cause tremendous financial damage to organization that uses cloud-based services, while the mitigation of this threat can be highly difficult considering the complex infrastructure that it uses to perform its malicious activities. For that purpose it’s important to think proactively rather than reactively when addressing the protection against this type of attacks. The overview of botnets and some of the countermeasures against this threat were discussed in this paper.

Today very important means of communication is the e-mail that allows people all over the
world to communicate, share data, and perform business. Yet there is nothing worse than an
inbox full of spam; i.e., information crafted to be delivered to a large number of recipients
against their wishes. In this paper, we present a numerous anti-spam methods and solutions that
have been proposed and deployed, but they are not effective because most mail servers rely on
blacklists and rules engine leaving a big part on the user to identify the spam, while others rely
on filters that might carry high false positive rate.

–The Spam Emails are regularly causing huge losses to business on a regular basis. The Spam filtering is an automated technique to identity SPAM and HAM (Non-Spam). The Web Spam filters can be categorized as: Content based spam filters and List based spam filters. In this research work, we have studied the spam statistics of a famous Spambot 'Srizbi'. We have also discussed different approaches for Spam Filtering and finally proposed a new algorithm which is made on the basis of behavioral approaches of Spammers and to restrict the budding economical growth of Spam generating company's. We have used the hidden Honeypot and a Honeytrap module to minimize the spam generated from Contact and Feedback forms on public and social networking CMS websites.

The Internet or World Wide Web has become prominent platform for business and commerce and is witnessing user growth with increased penetration of mobile Internet. Huge traffic is being generated, some of it being legitimate and the rest being malicious. Hence the implementation and maintenance of Information Security programs is been done .In the age of the Internet, protecting our information has become just as important as protecting our property. Malware authors have found and exploited new zero-day vulnerabilities resulting in damage to end-user system. Ransomware, a malware that has taken malware attacks to a new level by locking files of the affected user and demand Bitcoin payment to unlock those files. On the other hand the Volume and frequency of Distributed Denial of Service (DDoS) attacks have increased. Many unpatched machines without the knowledge of its owners have become a part of Botnets which carry out DDoS attacks. This paper focuses on strategies to be adopted to protect individual hosts from malware attacks and other types of intrusions using Deception, White-Listing and Reputation Services.

Over the past decade, the digitization of services transformed the healthcare sector leading to a sharp rise in cybersecurity threats. Poor cybersecurity in the healthcare sector, coupled with high value of patient records attracted the attention of hackers. Sophisticated advanced persistent threats and malware have significantly contributed to increasing risks to the health sector. Many recent attacks are attributed to the spread of malicious software, e.g., ransomware or bot malware. Machines infected with bot malware can be used as tools for remote attack or even cryptomining. This paper presents a novel approach, called BotDet, for botnet Command and Control (C&C) traffic detection to defend against malware attacks in critical ultrastructure systems. There are two stages in the development of the proposed system: 1) we have developed four detection modules to detect different possible techniques used in botnet C&C communications and 2) we have designed a correlation framework to reduce the rate of false alarms raised by individual detection modules. Evaluation results show that BotDet balances the true positive rate and the false positive rate with 82.3% and 13.6%, respectively. Furthermore, it proves BotDet capability of real time detection. INDEX TERMS Critical infrastructure security, healthcare cyber attacks, malware, botnet, command and control server, intrusion detection system, alert correlation.