Malicious Bots

I wrote an affidavit describing the circumstances detailed above and received a court order from a magistrate to obtain all the registration details for the domain names found hard-coded in the malicious IRC bot.

Author: Ken Dunham

Publisher: CRC Press

ISBN: 1420069063

Category: Computers

Page: 168

View: 136


Originally designed as neutral entities, computerized bots are increasingly being used maliciously by online criminals in mass spamming events, fraud, extortion, identity theft, and software theft. Malicious Bots: An Inside Look into the Cyber-Criminal Underground of the Internet explores the rise of dangerous bots and exposes the nefarious methods of “botmasters”. This valuable resource assists information security managers in understanding the scope, sophistication, and criminal uses of bots. With sufficient technical detail to empower IT professionals, this volume provides in-depth coverage of the top bot attacks against financial and government networks over the last several years. The book presents exclusive details of the operation of the notorious Thr34t Krew, one of the most malicious bot herder groups in recent history. Largely unidentified by anti-virus companies, their bots spread globally for months, launching massive distributed denial of service (DDoS) attacks and warez (stolen software distributions). For the first time, this story is publicly revealed, showing how the botherders got arrested, along with details on other bots in the world today. Unique descriptions of the criminal marketplace – how criminals make money off of your computer – are also a focus of this exclusive book! With unprecedented detail, the book goes on to explain step-by-step how a hacker launches a botnet attack, providing specifics that only those entrenched in the cyber-crime investigation world could possibly offer. Authors Ken Dunham and Jim Melnick serve on the front line of critical cyber-attacks and countermeasures as experts in the deployment of geopolitical and technical bots. Their work involves advising upper-level government officials and executives who control some of the largest networks in the world. By examining the methods of Internet predators, information security managers will be better able to proactively protect their own networks from such attacks.

Social Informatics

Despite the long history of causing ongoing negative impact, malicious bots did not quit on being the Grand Villain on the OSNs. They have been emerging, evolving, and participating in new types of destructive activities.

Author: Samin Aref

Publisher: Springer Nature

ISBN: 9783030609757

Category: Computers

Page: 462

View: 875


This volume constitutes the proceedings of the 12th International Conference on Social Informatics, SocInfo 2020, held in Pisa, Italy, in October 2020. The 30 full and 3 short papers presented in these proceedings were carefully reviewed and selected from 99 submissions. The papers presented in this volume cover a broad range of topics, ranging from works that ground information-system design on social concepts, to papers that analyze complex social systems using computational methods, or explore socio-technical systems using social sciences methods.

Computer Security

The 2018 annual report of Distil Networks [2] reveals that web bots account for 42.2% of all website traffic while human traffic makes up the rest 57.8%. The bot landscape is fairly polarized between benign bots and malicious bots [1].

Author: Javier Lopez

Publisher: Springer

ISBN: 9783319989891

Category: Computers

Page: 571

View: 660


The two-volume set, LNCS 11098 and LNCS 11099 constitutes the refereed proceedings of the 23nd European Symposium on Research in Computer Security, ESORICS 2018, held in Barcelona, Spain, in September 2018. The 56 revised full papers presented were carefully reviewed and selected from 283 submissions. The papers address issues such as software security, blockchain and machine learning, hardware security, attacks, malware and vulnerabilities, protocol security, privacy, CPS and IoT security, mobile security, database and web security, cloud security, applied crypto, multi-party computation, SDN security.

Social Informatics

work, the bots defined in [4] are more of malicious nature, and the study did not provide further categorization/analysis of benign and malicious bots in Twitter. To investigate on spam bots, Stringhini et al.

Author: Emma Spiro

Publisher: Springer

ISBN: 9783319478807

Category: Computers

Page: 545

View: 385


The two-volume set LNCS 10046 and 10047 constitutes the proceedings of the 8th International Conference on Social Informatics, SocInfo 2016, held in Bellevue, WA, USA, in November 2016. The 36 full papers and 39 poster papers presented in this volume were carefully reviewed and selected from 120 submissions. They are organized in topical sections named: networks, communities, and groups; politics, news, and events; markets, crowds, and consumers; and privacy, health, and well-being.

Detection of Intrusions and Malware and Vulnerability Assessment

Web Runner 2049: Evaluating Third-Party Anti-bot Services Babak Amin Azad1(B), Oleksii Starov2, Pierre Laperdrix3, ... Given the ever-increasing number of malicious bots scouring the web, many websites are turning to specialized ...

Author: Clémentine Maurice

Publisher: Springer Nature

ISBN: 9783030526832

Category: Computers

Page: 281

View: 424


This book constitutes the proceedings of the 17th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2020, held in Lisbon, Portugal, in June 2020.* The 13 full papers presented in this volume were carefully reviewed and selected from 45 submissions. The contributions were organized in topical sections named: vulnerability discovery and analysis; attacks; web security; and detection and containment. ​*The conference was held virtually due to the COVID-19 pandemic.

Combating Security Challenges in the Age of Big Data

Bots are programs to automate tasks. The word is originated from 'Robot'. These programs can be used for good or bad. Malicious bots are self-propagating. They can be designed to carry out attacks like Denial of Service attacks.

Author: Zubair Md. Fadlullah

Publisher: Springer Nature

ISBN: 9783030356422

Category: Computers

Page: 266

View: 220


This book addresses the key security challenges in the big data centric computing and network systems, and discusses how to tackle them using a mix of conventional and state-of-the-art techniques. The incentive for joining big data and advanced analytics is no longer in doubt for businesses and ordinary users alike. Technology giants like Google, Microsoft, Amazon, Facebook, Apple, and companies like Uber, Airbnb, NVIDIA, Expedia, and so forth are continuing to explore new ways to collect and analyze big data to provide their customers with interactive services and new experiences. With any discussion of big data, security is not, however, far behind. Large scale data breaches and privacy leaks at governmental and financial institutions, social platforms, power grids, and so forth, are on the rise that cost billions of dollars. The book explains how the security needs and implementations are inherently different at different stages of the big data centric system, namely at the point of big data sensing and collection, delivery over existing networks, and analytics at the data centers. Thus, the book sheds light on how conventional security provisioning techniques like authentication and encryption need to scale well with all the stages of the big data centric system to effectively combat security threats and vulnerabilities. The book also uncovers the state-of-the-art technologies like deep learning and blockchain which can dramatically change the security landscape in the big data era.

Securing Web Applications

Authors Stephen Gates, edge security evangelist and SME at Oracle Dyn, and Allan Liska, threat intelligence architect at Recorded Future, explore how advanced DNS services, web application firewall (WAF) services, bot management, API ...

Author: Stephen Gates


ISBN: OCLC:1096331823

Category: Data protection


View: 820


Graph Data Mining

Some researchers have proposed some detection algorithms for malicious social bots. Liu et al. [3] analyzed community structure and used community similarity to separate malicious social bots from humans. Mehrotra et al.

Author: Qi Xuan

Publisher: Springer Nature

ISBN: 9789811626098

Category: Artificial intelligence

Page: 243

View: 844


Graph data is powerful, thanks to its ability to model arbitrary relationship between objects and is encountered in a range of real-world applications in fields such as bioinformatics, traffic network, scientific collaboration, world wide web and social networks. Graph data mining is used to discover useful information and knowledge from graph data. The complications of nodes, links and the semi-structure form present challenges in terms of the computation tasks, e.g., node classification, link prediction, and graph classification. In this context, various advanced techniques, including graph embedding and graph neural networks, have recently been proposed to improve the performance of graph data mining. This book provides a state-of-the-art review of graph data mining methods. It addresses a current hot topic--the security of graph data mining-- and proposes a series of detection methods to identify adversarial samples in graph data. In addition, it introduces readers to graph augmentation and subgraph networks to further enhance the models, i.e., improve their accuracy and robustness. Lastly, the book describes the applications of these advanced techniques in various scenarios, such as traffic networks, social and technical networks, and blockchains. .

Detection of Intrusions and Malware and Vulnerability Assessment

Most commonly, security-motivated tainting has been used to identify vulnerabilities in or exploitations of non-malicious programs. Host-Based Intrusion Detection. The problem of distinguishing execution of an installed malicious bot ...

Author: Bernhard Hämmerli

Publisher: Springer

ISBN: 9783540736141

Category: Computers

Page: 254

View: 108


This book constitutes the refereed proceedings of the 4th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2007, held in Lucerne, Switzerland in July 2007. The 14 revised full papers presented were carefully reviewed and selected from 57 submissions. The papers are organized in topical sections on Web security, intrusion detection, traffic analysis, network security, and host security.

Advances in Malware and Data Driven Network Security

The white circles (〇) of Figure 1 represent white-hat bots produced by those worms. C&C: The BDS controls the white-hat botnet to exterminates the malicious bots. The BDS will finally exterminate the malicious botnet. 4.

Author: Gupta, Brij B.

Publisher: IGI Global

ISBN: 9781799877912

Category: Computers

Page: 304

View: 313


Every day approximately three-hundred thousand to four-hundred thousand new malware are registered, many of them being adware and variants of previously known malware. Anti-virus companies and researchers cannot deal with such a deluge of malware – to analyze and build patches. The only way to scale the efforts is to build algorithms to enable machines to analyze malware and classify and cluster them to such a level of granularity that it will enable humans (or machines) to gain critical insights about them and build solutions that are specific enough to detect and thwart existing malware and generic-enough to thwart future variants. Advances in Malware and Data-Driven Network Security comprehensively covers data-driven malware security with an emphasis on using statistical, machine learning, and AI as well as the current trends in ML/statistical approaches to detecting, clustering, and classification of cyber-threats. Providing information on advances in malware and data-driven network security as well as future research directions, it is ideal for graduate students, academicians, faculty members, scientists, software developers, security analysts, computer engineers, programmers, IT specialists, and researchers who are seeking to learn and carry out research in the area of malware and data-driven network security.