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Zombie (computing)

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Compromised computer used for malicious tasks on a network

This article is about the term "zombie" in computer security. For "zombie" in UNIX programming, seeZombie process.

Incomputing, azombie is a computer connected to the Internet that has beencompromised by ahacker via acomputer virus,computer worm, ortrojan horse program and can be used to perform malicious tasks under the remote direction of the hacker. Zombie computers often coordinate together in abotnet controlled by the hacker, and are used for activities such as spreadinge-mail spam and launchingdistributed denial-of-service attacks (DDoS attacks) against web servers. Most victims are unaware that their computers have become zombies. The concept is similar to thezombie ofHaitian Voodoo folklore, which refers to a corpse resurrected by asorcerer via magic and enslaved to the sorcerer's commands, having no free will of its own.[1] A coordinatedDDoS attack by multiple botnet machines also resembles a "zombie horde attack", as depicted in fictionalzombie films.

(1) Spammer's web site (2) Spammer (3) Spamware (4) Infected computers (5) Virus or trojan (6) Mail servers (7) Users (8) Web traffic

Advertising

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Zombie computers have been used extensively to sende-mail spam; as of 2005, an estimated 50–80% of all spam worldwide was sent by zombie computers.[2] This allowsspammers to avoid detection and presumably reduces theirbandwidth costs, since the owners of zombies pay for their own bandwidth. This spam also greatly increases the spread ofTrojan horses, as Trojans are not self-replicating. They rely on the movement of e-mails or spam to grow, whereas worms can spread by other means.[3] For similar reasons, zombies are also used to commitclick fraud against sites displayingpay-per-click advertising. Others can hostphishing ormoney mule recruiting websites.

Distributed denial-of-service attacks

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Zombies can be used to conductdistributed denial-of-service (DDoS) attacks, a term which refers to the orchestrated flooding of target websites by large numbers of computers at once. The large number of Internet users making simultaneous requests of a website's server is intended to result in crashing and the prevention of legitimate users from accessing the site.[4] A variant of this type of flooding is known as distributed degradation-of-service. Committed by "pulsing" zombies, distributed degradation-of-service is the moderated and periodical flooding of websites intended to slow down rather than crash a victim site. The effectiveness of this tactic springs from the fact that intense flooding can be quickly detected and remedied, but pulsing zombie attacks and the resulting slow-down in website access can go unnoticed for months and even years.[5]

The computing facilitated by theInternet of Things (IoT) has been productive for modern-day usage, yet it has played a significant role in the increase in web attacks. The potential of IoT enables every device to communicate efficiently, but this also intensifies the need for policy enforcement regarding security threats. Among these threats, Distributed Denial-of-Service (DDoS) attacks are prevalent. Research has been conducted to study the impact of such attacks on IoT networks and to develop compensating provisions for defense.[6] Consultation services specialized in IoT security, such as those offered byIoT consulting firms[dead link], play a vital role in devising comprehensive strategies to safeguard IoT ecosystems from cyber threats.

Notable incidents of distributed denial- and degradation-of-service attacks in the past include the attack upon theSPEWS service in 2003, and the one againstBlue Frog service in 2006. In 2000, several prominent Web sites (Yahoo,eBay, etc.) were clogged to a standstill by a distributed denial of service attack mounted by 'MafiaBoy', a Canadian teenager.

Smartphones

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Beginning in July 2009, similar botnet capabilities have also emerged for the growingsmartphone market. Examples include the July 2009 in the "wild" release of the Sexy Spacetext message worm, the world's first botnet capableSMS worm, which targeted theSymbian operating system inNokia smartphones. Later that month, researcherCharlie Miller revealed aproof of concept text message worm for theiPhone atBlack Hat Briefings. Also in July,United Arab Emirates consumers were targeted by theEtisalat BlackBerryspyware program. In the 2010s, the security community is divided as to the real world potential of mobile botnets. But in an August 2009 interview withThe New York Times, cyber security consultantMichael Gregg summarized the issue this way: "We are about at the point with [smart]phones that we were with desktops in the '80s."[7]

"Malware" has become a serious challenge in smartphones. There are many different kinds, so advances in malware must keep up. One option is the fuzzy logic-based dynamic ensemble (FL-BDE).[8]

See also

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References

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  1. ^"Zombie - Port Security". August 3, 2021.
  2. ^Tom Spring (June 20, 2005)."Spam Slayer: Slaying Spam-Spewing Zombie PCs". PC World.Archived from the original on July 16, 2017. RetrievedDecember 19, 2015.
  3. ^White, Jay D. (2007).Managing Information in the Public Sector. M.E. Sharpe. p. 221.ISBN 978-0-7656-1748-4.
  4. ^Weisman, Steve (2008).The Truth about Avoiding Scams. FT Press. p. 201.ISBN 978-0-13-233385-6.
  5. ^Schwabach, Aaron (2006).Internet and the Law. ABC-CLIO. p. 325.ISBN 1-85109-731-7.
  6. ^Lohachab, Ankur; Karambir, Bidhan (September 1, 2018)."Critical Analysis of DDoS—An Emerging Security Threat over IoT Networks".Journal of Communications and Information Networks.3 (3):57–78.doi:10.1007/s41650-018-0022-5.ISSN 2509-3312.S2CID 52924506.
  7. ^Furchgott, Roy (August 14, 2009)."Phone Hacking Threat Is Low, but it Exists".Gadgetwise Blog.New York Times.Archived from the original on July 16, 2017. RetrievedJuly 16, 2017.
  8. ^Ali, Mushtaq; Zain, Jasni Mohamad; Zolkipli, Mohamad Fadli; Badshah, Gran (January 2023)."An Ensemble Approach Based on Fuzzy Logic Using Machine Learning Classifiers for Android Malware Detection".Gadgetwise Blog. RetrievedJuly 13, 2025.

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