Relevant bibliographies by topics / Internet attack

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Internet attack'

Author: Grafiati
Published: 5 June 2025
Last updated: 24 June 2025

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Journal articles on the topic "Internet attack"

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Ourston, Dirk, Sara Matzner, William Stump, and Bryan Hopkins. "Coordinated Internet attacks: responding to attack complexity." Journal of Computer Security 12, no. 2 (2004): 165–90. http://dx.doi.org/10.3233/jcs-2004-12201.

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Peterson, A. Padgett. "Internet attack mechanisms." Network Security 1996, no. 5 (1996): 17–19. http://dx.doi.org/10.1016/1353-4858(96)81911-8.

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R., Ramkumar, Rahul R., and Gowtham Sri. "Anomaly Based Approach for Defending Denial of Service Attack in Web Traffic." COMPUSOFT: An International Journal of Advanced Computer Technology 04, no. 04 (2015): 1657–64. https://doi.org/10.5281/zenodo.14776346.

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Distributed Denial of Service (DDOS) attacks has become a great threat for internet security. This attackis an advanced form of DOS (Denial of Service) attack. This attack changes its whole origin ID and it gives trouble to find it out and it has become a serious threat for internet security. Almost all traditional services such as bank websites, power resources, medical, educational institutions and military are extended to World Wide Web and thus many people widely use internet services. As many users of Internet is mandatory, network security for attacks are also increasing. Current DDoS attacks are carried out by hacking tools, viruses and botnets using different packet-transmission strategies and various forms of attack packets to beat defense system networks. These problems lead to defense system network requiring various detection methods in order to identify attacks. But DDoS attacks can mix their traffics during flash crowds. By doing this, the network of defense systems cannot detect the attack traffic in time. Denial of service (DOS) attack is potential damaging attack which degrades the performance of online servers in no time. This attack performs an intensive attack on the target server by flooding it with large useless packets. Our Triangular MCAbased DoS attack detection system employs the principle of anomaly based detection in attack recognition. To cope with such damaging attacks becomes challenge for the researchers. Preventing and avoiding this attack mainly focuses on the development of network-based detection mechanisms. Detection systems based on these techniques monitor traffic transmitting over the protected networks. This makes our solution capable of detecting known and unknown DoS attacks effectively by learning the patterns of legitimate network traffic only. In this paper Detection of denial of service attack is done using anamoly based approach, multivariate correlation analysis. 
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Christopher, Mitchel, Ghaleb Baraq, M. Ghaleb Safwan, Jaroucheh Zakwan, and Ali Saleh Al-rimy Bander. "The Impact of Mobile DIS and Rank-Decreased Attacks in Internet of Things Networks." International Journal of Engineering and Advanced Technology (IJEAT) 10, no. 2 (2020): 66–72. https://doi.org/10.35940/ijeat.B1962.1210220.

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With a predicted 50 billion devices by the end of 2020, the Internet of things has grown exponentially in the last few years. This growth has seen an increasing demand for mobility support in low power and lossy sensor networks, a type of network characterized by several limitations in terms of their resources including CPU, memory and batter, causing manufactures to push products out to the market faster, without the necessary security features. IoT networks rely on the Routing Protocol for Low Power and Lossy Network (RPL) for communication, designed by the Internet Engineering Task Force (IETF). This protocol has been proven to be efficient in relation to the handling of routing in such constrained networks, However, research studies revealed that RPL was inherently designed for static networks, indicating poor handling of mobile or dynamic topologies which is worsen when introducing mobile attacker. In this paper, two IoT routing attacks are evaluated under a mobile attacker with the aim of providing a critical evaluation of the impact the attacks have on the network in comparison to the case with static attacker. The first attack is the Rank attack in which the attacker announces false routing information to its neighbour attracting them to forward their data via the attacker. The second attack is the DIS attack in which the attacker floods the network with DIS messages triggering them to reset their transmission timers and sending messages more frequently. The comparison were conducted in terms of average power consumption and also the packet delivery ratio (PDR). Based on the results collected from the simulations, it was established that when an attacking node is mobile, there’s an average increase of 36.6 in power consumption and a decrease of 14 for packet delivery ratios when compared to a static attacking node.
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Rastenis, Justinas, Simona Ramanauskaitė, Justinas Janulevičius, Antanas Čenys, Asta Slotkienė, and Kęstutis Pakrijauskas. "E-mail-Based Phishing Attack Taxonomy." Applied Sciences 10, no. 7 (2020): 2363. http://dx.doi.org/10.3390/app10072363.

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The amount of fraud on the Internet is increasing along with the availability and the popularity of the Internet around the world. One of the most common forms of Internet fraud is phishing. Phishing attacks seek to obtain a user’s personal or secret information. The variety of phishing attacks is very broad, and usage of novel, more sophisticated methods complicates its automated filtering. Therefore, it is important to form up-to-date and detailed phishing attack taxonomy, which could be used for both human education purposes as well as phishing attack discrete notation. In this paper, we propose an e-mail-based phishing attack taxonomy, which includes six phases of the attack. Each phase has at least one criterion for the attack categorization. Each category is described, and in some cases the categories have sub-classes to present the full variety of phishing attacks. The proposed taxonomy is compared to similar taxonomies. Our taxonomy outperforms other phishing attack taxonomies in numbers of phases, criteria and distinguished classes. Validation of the proposed taxonomy is achieved by adapting it as a phishing attack notation for an incident management system. Taxonomy usage for phishing attack notation increases the level of description of phishing attacks compared to free-form phishing attack descriptions.
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Zafri, Fizza. "Ransomware Attacks in History of Cyber World." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (2022): 39–43. http://dx.doi.org/10.22214/ijraset.2022.39758.

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Abstract: Technology advancement since last few decades creates cyber attack a critical issue. Cyber security has become an important part today. It has also become an important and crucial subject in the field of forensic science. Increased in the growth of internet technology and internet devices have increased the risk of cyber attack. Almost every organization today are depends on the internet and devices. There are many types of cyber attack. This paper is the detailed review about Ransomware attack. This paper is consisted about vast of the information about What is Ransomware Attack, how does it work, how ransomware attack emerged. After reading this paper you will learn about the ransomware attacks in history of cyber world. This will help you to learn and understand about ransomware attack, how to prevent yourself from ransomware attack. As a forensic science student, it is always important to be aware about the attacks that have happened in the history of cyber world. Before writing this paper, I have read and analyze many research paper and internet articles, so that I can write a detailed review paper which can help students and for the forensic awareness. Keywords: Cyberattack, Hacking, Ransomware, cyberworld, cyber security, ransomware, forensic, network security
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Karthikeyani, R., and E. Karthikeyan. "A Review on Distributed Denial of Service Attack." Asian Journal of Research in Computer Science 16, no. 4 (2023): 133–44. http://dx.doi.org/10.9734/ajrcos/2023/v16i4378.

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Today’s world, technology has become an inevitable part of human life. In fact, during the Covid-19 pandemic, everything from the corporate world to educational institutions has shifted from offline to online. It leads to exponential increase in intrusions and attacks over the internet-based technologies. Distributed denial of service (DDOS) attack is one of the most dangerous attack that could cause devastating effects on the internet. These attacks are becoming more complex and expected to expand in number day after day, rendering detecting and combating these threats challenging. In network security this attack is very dangerous. The main aim of DDOS attack is to collapse the network or server with abnormal traffic to make server unavailable for the legitimate users. In this paper reviews various type of DDOS attacks, Symptoms of DDOS attack, role of botnet on DDOS attack and give some mitigation and prevention technique for DDOS attack.
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Wu, Yixin, Cheng Huang, Xing Zhang, and Hongyi Zhou. "GroupTracer: Automatic Attacker TTP Profile Extraction and Group Cluster in Internet of Things." Security and Communication Networks 2020 (December 4, 2020): 1–14. http://dx.doi.org/10.1155/2020/8842539.

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As Advanced Persistent Threat (APT) becomes increasingly frequent around the world, security experts are starting to look at how to observe, predict, and mitigate the damage from APT attacks. In the meantime, the Internet of things devices are also risky and heavily exposed to the Internet, making them more easily used by hacker organizations to launch APT attacks. An excellent attacker can take down millions of Internet of things devices in a short time. Once the IoT botnet is built, attackers can use it to launch complex attacks which could damage Internet infrastructure and cause network disconnection. This paper proposes GroupTracer, a framework for observing and predicting the Internet of things attacks. GroupTracer is designed to automatically extract the TTP profiles (i.e., tactics, techniques, and procedures) that can describe the behavior of attackers through their tactics, techniques, and processes and dig out the potential attacker groups behind complex attacks. Firstly, it captures attacks by IoT honeypots and extracts relevant fields from logs. Then, attack behaviors are automatically mapped to the ATT&CK framework to achieve automatic TTP profiles extraction. After that, GroupTracer presents four feature groups, including TTP profiles, Time, IP, and URL features, a total of 18 features, mines potential attack groups through hierarchical clustering algorithm, and compares the clustering results with two baseline algorithms. As the ground truth labels are unknown, we apply three internal validation indexes to evaluate the cluster quantity. Experimental results showed that the proposed framework has achieved an excellent performance in exploiting potential groups as the Calinski–Harabasz index reaches 3416.93. Eventually, attack trees are generated for each cluster where nodes indicate attack commands and edges represent command sequences. These attack trees could help better understand each attack group’s actions and techniques.
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Singh, Rajeev, and T. P. Sharma. "Present Status of Distributed Denial of Service (DDoS) Attacks in Internet World." International Journal of Mathematical, Engineering and Management Sciences 4, no. 4 (2019): 1008–17. http://dx.doi.org/10.33889/ijmems.2019.4.4-080.

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Distributed Denial of Service (DDoS) attack harms the digital availability in Internet. The user’s perspective of getting quick and effective services may be badly hit by the DDoS attackers. There are several reports of DDoS attack incidences that have caused devastating effects on the user and web services in the Internet world. In the present digital world dominated by wireless, mobile and IoT devices, the numbers of users are increasing day by day. Most of the users are novice and therefore their devices either fell prey to DDoS attacks or unknowingly add themselves to the DDoS attack Army. We soon will witness the 5G mobile revolution but there are reports that 5G networks are also falling prey to DDoS attacks and hence, the realization of DoS attack as a threat needs to be understood. The paper targets to assess the DDoS attack threat. It identifies the impact of attack and also reviews existing Indian laws.
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Singhal, Prateek, Puneet Sharma, and Deepak Arora. "An approach towards preventing iot based sybil attack based on contiki framework through cooja simulator." International Journal of Engineering & Technology 7, no. 2.8 (2018): 261. http://dx.doi.org/10.14419/ijet.v7i2.8.10421.

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In this paper we propagate the Sybil attack in WSN (Wireless sensor network), by the researchers many attacks have been recognized in WSN till now and there are many attacks which can attack over through internet, Internet of thing means all devices is interconnected to each other M2M over internet and can be attacked by any of the attacker on any devices. Sybil attack is the detrimental attack against sensor network where several counterfeit identities and legitimate identities are used to get prohibited pass in a network. This is major attack which results an information loss and misinterpretation in the network, and it also minimizes the routing disturbance, trustworthiness and dropping sensitivity packets into a network. In this instance node can trust the imaginary node and sharing of information starts, owed to this security of node is get affected and information is lost. In this paper, a survey of CONTIKI OS-2.7, stimulation tool COOJA and the Sybil attack and proposed the defense mechanisms and CAM (Compare and Match) approach to verify the Sybil attack position and prevent it. This Sybil attack can be stimulated on the stimulation tool COOJA which helps to identify the attacker position node, whereas these attacks outcome in uni-casting as well as multicasting and in this paper specifically given the secure security for Wireless sensor network.
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Dissertations / Theses on the topic "Internet attack"

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Arikan, Erinc. "Attack profiling for DDoS benchmarks." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file Mb., 96 p, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:1435821.

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Atiiq, Syafiq Al. "Adaptive Counteraction Against Denial of Service Attack." Thesis, KTH, Nätverk och systemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-219382.

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The Internet of Things (IoT) is the next generation of networked society where billions of, everyday-life, devices are directly connected to the Internet and able to communicate with each other. In particular, the Constrained Application Protocol (CoAP) has become the de-facto IoT standard for communication at the application layer, as a lightweight web transfer protocol affordable also for resource-constrained platforms. However, as IoT devices are directly connected to the Internet, they are especially vulnerable to a number of security attacks including Denial of Service (DoS), which can seriously worsen their performance and responsiveness, and even make them totally unavailable to serve legitimate requests. In this Master's Thesis project, we have developed a cross-layer and context-aware approach that adaptively counteracts DoS attacks against CoAP server devices, by dynamically adjusting their operative state according to the attack intensity. This considerably limits the impact of DoS attacks and preserves service availability of victim devices to the best possible extent. The proposed approach leverages a trusted Proxy that adaptively shields victim devices, while effectively forwarding and caching messages if needed. We have made a proof-of-concept implementation of our solution for the Californium framework and the CoAP protocol, and experimentally evaluated its effectiveness in counteracting DoS and preserving availability of devices under attack. This Master's Thesis project has been conducted in collaboration with RISE SICS, a research institute for applied information and communication technology in Sweden.<br>Sakernas Internet (IoT) är nästa generations nätverkssamhälle där miljarder av, vardagliga, enheter är direkt anslutna till Internet och har möjlighet att kommunicera med varandra. Särskilt har CoAP, ett lättviktsprotokoll för webbtrafik som även fungerar för plattformar med begränsade resurser, blivit Sakernas Internets standard för kommunikation på applikationslagret. Men eftersom IoT-enheter är direkt anslutna till Internet så är de också speciellt utsatta för ett antal säkerhetsattacker, inklusive DoS, som kan försämra deras prestanda och mottaglighet avsevärt och i värsta fall göra dem helt otillgängliga för legitima förfrågningar. I detta examensarbete har vi utvecklat en lageröverskridande och kontextmedveten metod som adaptivt motverkar DoS attacker mot CoAP serverenheter genom att dynamiskt anpassa enhetens operativa tillstånd i enlighet med attackintensiteten. Detta begränsar DoS-attackers påverkan på enheterna avsevärt samtidigt som det bibehåller tillgänglighet för tjänster på utsatta enheter till största möjliga utsträckning. Den föreslagna metoden utnyttjar en betrodd proxy som adaptivt skyddar utsatta enheter, samtidigt som den effektivt vidarebefordrar och sparar meddelanden om så behövs. I detta arbete har vi skapat en proof of concept-implementation av vår lösning för Californium-ramverket och CoAP protokollet. Arbetet har utvärderats experimentellt för att undersöka lösningens effektivitet när det gäller att motarbeta DoS-attacker samt hur den bibehåller enheters tillgänglighet under attacker. Detta uppsatsprojekt har utförts i samarbete med RISE SICS som är ett forskningsinstitut för tillämpad informations- och kommunikationsteknik i Sverige.
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Beaulaton, Delphine. "Security Analysis of IoT Systems using Attack Trees." Thesis, Lorient, 2019. http://www.theses.fr/2019LORIS548.

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L’Internet des Objects (IoT) est un modèle qui évolue rapidement et qui permet à des utilisateursd’utiliser et contrôler une large variété d’objets connectés entre eux. Ces environnementsconnectés augmentent la surface d’attaque d’un système puisque les risques sont multipliés parle nombre d’appareils connectés. Ces appareils sont responsables de tâches plus ou moinscritiques, et peuvent donc être la cible d’utilisateurs malveillants. Dans ce travail de thèse nousprésentons une méthodologie pour évaluer la sécurité de systèmes IoT. Nous proposons unemanière de représenter les systèmes IoT, couplée avec des arbres d’attaques afin d’évaluer leschances de succès d’une attaque sur un système donné. La représentation des systèmes est faitevia un langage formel que nous avons développé : SOML (Security Oriented Modeling Language).Ce langage permet de définir le comportement des différents acteurs du système et d’ajouterdes probabilités sur leurs actions. L’abre d’attaque nous offre un moyen simple et formel dereprésenter de possibles attaques sur le système. L’analyse probabiliste est ensuite effectuée viaun outil de Statistical Model Checking : Plasma. Nous utilisons deux algorithmescomplémentaires pour effectuer cette analyse : Monte Carlo et importance splitting<br>LoT is a rapidly emerging paradigm that provides a way to the user to instrument and control a large variety of objects interacting between each other over the Internet. In IoT systems, the security risks are multiplied as they involve hetero- geneous devices that are connected to a shared network and that carry critical tasks, and hence, are targets for malicious users. In this thesis, we propose a security-based framework for modeling IoT systems where attack trees are defined alongside the model to detect and prevent security risks in the system. The language we implemented aims to model the IoT paradigm in a simple way. The IoT systems are composed of entities having some communication capabilities between each other. Two entities can communicate if (i) they are connected through a communication protocol and (ii) they satisfy some constraints imposed by the protocol. In order to identify and analyze attacks on the security of a system we use attack trees which are an intuitive and practical formal method to do so. A successful attack can be a rare event in the execution of a well-designed system. When rare, such attacks are hard to detect with usual model checking techniques. Hence, we use importance splitting as a statistical model checking technique for rare events
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Pathan, Sakib, and Erik Stenström. "Säkerhetsfrågor beträffande Sakernas Internet med fokus på fastighetsinfrastruktur." Thesis, KTH, Data- och elektroteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-168949.

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I detta examensarbete görs en analys av säkerheten hos några av de driftundercentraler som används i fastigheter som Riksbyggen förvaltar. Driftundercentralerna används för att kontrollera olika delar i en fastighet, exempelvis belysning och temperatur. I de flesta fall nås respektive driftundercentral via en egen publik IP-adress, medan vissa tillverkare har en molntjänst för sina driftundercentraler. Syftet med examensarbetet har varit att undersöka de olika driftundercentralernas säkerhet, upptäcka brister och ge förbättringsförslag till dessa. Därutöver ges också exempel på hur smarta hem kan byggas upp. Undersökningen har gjorts på flera sätt, dels med hjälp av kontrollerade attacker men även genom att samla information om driftundercentralerna och hur de fungerar. Utifrån de undersökningar som gjorts har ett antal brister kunnat konstateras, bl.a. när det gäller lösenordens styrka och kryptering av dessa. Generella förslag på förbättringar har getts för att minska sårbarheten för eventuella attacker som kan ske i framtiden.<br>This project presents an analysis of the security regarding some of the controllers which are used in real estates managed by Riksbyggen. The controllers are used to control different parts of a property, such as lighting and temperature. In most cases, the controllers are reached via their own public IP address, while some manufacturers have a cloud service for their controllers. The purpose with this project has been to examine the different controllers’ security, discover weaknesses and provide suggestions for improvements to these. In addition, examples are also given on how smart homes can be built. The study has been made in several ways, partly with the help of controlled attacks but also by gathering information about the controllers and how they operate. Based on the studies that were made, a number of weaknesses have been observed, including passwords’ strength and encryption of these. General suggestions for improvements have been given to reduce the vulnerability for possible attacks that may occur in the future.
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Sung, Minho. "Scalable and efficient distributed algorithms for defending against malicious Internet activity." Diss., Available online, Georgia Institute of Technology, 2006, 2006. http://etd.gatech.edu/theses/available/etd-07172006-134741/.

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Thesis (Ph. D.)--Computing, Georgia Institute of Technology, 2007.<br>Xu, Jun, Committee Chair ; Ahamad, Mustaque, Committee Member ; Ammar, Mostafa, Committee Member ; Bing, Benny, Committee Member ; Zegura, Ellen, Committee Member.
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Chan, Yik-Kwan Eric, and 陳奕鈞. "Investigation of a router-based approach to defense against Distributed Denial-of-Service (DDoS) attack." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30173309.

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Alserhani, Faeiz. "A framework for correlation and aggregation of security alerts in communication networks : a reasoning correlation and aggregation approach to detect multi-stage attack scenarios using elementary alerts generated by Network Intrusion Detection Systems (NIDS) for a global security perspective." Thesis, University of Bradford, 2011. http://hdl.handle.net/10454/5430.

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The tremendous increase in usage and complexity of modern communication and network systems connected to the Internet, places demands upon security management to protect organisations' sensitive data and resources from malicious intrusion. Malicious attacks by intruders and hackers exploit flaws and weakness points in deployed systems through several sophisticated techniques that cannot be prevented by traditional measures, such as user authentication, access controls and firewalls. Consequently, automated detection and timely response systems are urgently needed to detect abnormal activities by monitoring network traffic and system events. Network Intrusion Detection Systems (NIDS) and Network Intrusion Prevention Systems (NIPS) are technologies that inspect traffic and diagnose system behaviour to provide improved attack protection. The current implementation of intrusion detection systems (commercial and open-source) lacks the scalability to support the massive increase in network speed, the emergence of new protocols and services. Multi-giga networks have become a standard installation posing the NIDS to be susceptible to resource exhaustion attacks. The research focuses on two distinct problems for the NIDS: missing alerts due to packet loss as a result of NIDS performance limitations; and the huge volumes of generated alerts by the NIDS overwhelming the security analyst which makes event observation tedious. A methodology for analysing alerts using a proposed framework for alert correlation has been presented to provide the security operator with a global view of the security perspective. Missed alerts are recovered implicitly using a contextual technique to detect multi-stage attack scenarios. This is based on the assumption that the most serious intrusions consist of relevant steps that temporally ordered. The pre- and post- condition approach is used to identify the logical relations among low level alerts. The alerts are aggregated, verified using vulnerability modelling, and correlated to construct multi-stage attacks. A number of algorithms have been proposed in this research to support the functionality of our framework including: alert correlation, alert aggregation and graph reduction. These algorithms have been implemented in a tool called Multi-stage Attack Recognition System (MARS) consisting of a collection of integrated components. The system has been evaluated using a series of experiments and using different data sets i.e. publicly available datasets and data sets collected using real-life experiments. The results show that our approach can effectively detect multi-stage attacks. The false positive rates are reduced due to implementation of the vulnerability and target host information.
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Margotta, Fabrizio. "DoS and DDoS attacks in Named Data Networking." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21855/.

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La nascita di Internet ha portato benefici senza precedenti in termini sociali ed economici. Le tecnologie e i protocolli inizialmente adottati andavano a risolvere i problemi causati dall’inaffidabilità della preesistente linea telefonica e nel corso dei vari decenni hanno garantito il funzionamento delle comunicazioni globali. Tuttavia ci si pone delle domande sulla necessità di un nuovo cambio di paradigma che risponda alle nuove esigenze riscontrate nell’evoluzione di Internet stesso e dei servizi offerti. Named Data Networking, come progetto della famiglia delle Future Internet Architectures, propone una visione di Internet rinnovata in cui l’entità fondamentale scambiata è il Nome. L’attenzione viene posta sul cosa i nodi richiedono alla rete e non sul dove reperiscono le informazioni. Come nuova architettura, NDN propone approcci innovativi sui fronti dell’inoltro e dell’instradamento dei pacchetti nella rete e garantisce l’implementazione di diversi aspetti di sicurezza by design. Ciò non è però sufficiente a proteggere da tutte le minacce della rete, tra cui gli attacchi DDoS che costituiscono ancora oggi un rischio importante per i fornitori di servizi in Internet. Sono quindi necessari ulteriori sforzi per partorire un’architettura che risponda a requisiti di efficienza e sicurezza.
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Ahmim, Ilyes. "L'amélioration de la sécurité dans l'internet des objets." Electronic Thesis or Diss., Université Gustave Eiffel, 2025. https://these.univ-paris-est.fr/intranet/2025/UEFL-2025/TH2025UEFL2011.pdf.

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L'internet des objets (IoT) représente l'avenir de l'informatique, son but principal consiste à faciliter notre vie quotidienne via l'omniprésence des différents services informatiques qui assurent l'automatisation de nos différentes tâches. Afin d'atteindre cet objectif, diverses installations sont nécessaires en commençant par les capteurs et les actionneurs, en passant par les réseaux filaires et sans fils à haut débit tels que les réseaux FTTH, 4G et 5G. Vu la diversité des équipements, des protocoles, des technologies et des entreprises impliquées dans le développement de l'IoT de nombreux défis s'imposent à savoir la sécurité, la connectivité, la compatibilité et la longévité, les normes ainsi que les analyses et les actions intelligentes. La sécurité informatique représente le souci majeur de l'IoT, en raison de ses différentes failles de sécurités existantes d'un côté et de son implication dans la vie quotidienne de l'autre côté. Ces soucis de sécurités vont des grands problèmes comme la santé dans les solutions e-Health, jusqu'aux problèmes de la vie privée des petites fertilités comme la chaîne que nous avons regardée, l'heure du réveil…etc. Le but de cette thèse consiste à étudier profondément l'internet des objets, ses technologies, ses protocoles, ses standards, ses applications, ses défis, etc. Puis se focaliser sur son défi majeur qui est la sécurité dans ses différents niveaux architecturaux. Suite à cette étude des différents problèmes et failles de sécurité qui peuvent être exploités par les attaquants, notre objectif sera d'améliorer la sécurité de l'internet des objets en améliorant les protocoles de sécurité lèges afin d'utiliser ses différentes applications, solutions et services de manière saine et sûre<br>The Internet of Things (IoT) represents the future of IT, its main purpose is facilitating our daily life through the ubiquity of the different IT services that ensure the automation of our different tasks. In order to achieve this goal, a variety of facilities are needed, starting with sensors and actuators, as well as high-speed wired and wireless networks such as FTTH, 4G, and 5G. Given the diversity of equipment, protocols, technologies, and companies involved in the development of the IoT, there are many challenges to deal with, namely security, connectivity, compatibility, longevity, standards, and intelligent action. IT security is the major concern of the IoT, because of its various existing security gaps on one side and its involvement in everyday life on the other one. These security concerns range from large issues, such as health in e-Health solutions, to small fertility issues, such as the TV chain that we watched, and our awakening time. The aim of this thesis is to deeply study the Internet of Things namely its technologies, protocols, standards, applications, challenges, etc. Then focus on its major challenge, which is security in its different architectural levels. Following this study of the various security problems and vulnerabilities that can be exploited by attackers, our objective will be to improve the security of the Internet of Things by enhancing the lightweight security protocols in order to use its various applications, solutions, and services in a safe and secure manner
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Nguyen, Lien K. "Predicting catastrophic BGP routing instabilities." Thesis, Monterey, California. Naval Postgraduate School, 2004. http://hdl.handle.net/10945/1642.

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Approved for public release, distribution is unlimited<br>Inter-domain routing connects individual pieces of Internet topology, creating an integral, global data delivery infrastructure. Currently, this critical function is performed by the Border Gateway Protocol (BGP) version 4 [RFC1771]. Like all routing protocols, BGP is vulnerable to instabilities that reduce its effectiveness. Among the causes of these instabilities are those which are maliciously induced. Although there are other causes, e.g., natural events and network anomalies, this thesis will focus exclusively on maliciously induced instabilities. Most current models that attempt to predict a BGP routing instability confine their focus to either macro- or micro-level metrics, but not to both. The inherent limitations of each of these forms of metric gives rise to an excessive rate of spurious alerts, both false positives and false negatives. It is the original intent of this thesis to develop an improved BGP instability prediction model by statistically combining BGP instability metrics with user level performance metrics. The motivation for such a model is twofold. 1) To provide sufficient prior warning of impending failure to facilitate proactive protection measures. 2) To improve warning reliability beyond existing models, by demonstrably reducing both false positives and false negatives. However, our analysis of actual network trace data shows that a widely used BGP instability metric, the total number of update messages received in a time period, is not a good indicator of future user level performance.<br>Civilian, Department of Defense
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Books on the topic "Internet attack"

1

Elmer, Robert. Hack attack. WaterBrook Press, 2005.

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Jelena, Mirkovic, ed. Internet denial of service: Attack and defense mechanisms. Prentice Hall Professional Technical Reference, 2005.

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E, Goodman Seymour, and Longhurst David W, eds. Protecting critical infrastructures against cyber-attack. Oxford University Press, 2003.

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1953-, Rubin Charles, ed. Guerrilla marketing online attack: 100 low-cost, high-impact strategies for creating profits on the Internet. Piatkus, 1996.

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Science, United States Congress House Committee on. Cyber security-how can we protect American computer networks from attack?: Hearing before the Committee on Science, House of Representatives, One Hundred Seventh Congress, first session, October 10, 2001. U.S. G.P.O., 2002.

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United States. Congress. House. Committee on Science. Cyber security--how can we protect American computer networks from attack?: Hearing before the Committee on Science, House of Representatives, One Hundred Seventh Congress, first session, October 10, 2001. U.S. G.P.O., 2002.

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United, States Congress Senate Committee on the Judiciary Subcommittee on Technology Terrorism and Government Information. "Cyber attack: Improving prevention and prosecution" : hearing before the Subcommittee on Technology, Terrorism, and Government Information of the Committee on the Judiciary, United States Senate, One Hundred Sixth Congress, second session, on examining how to combat cyber attacks by improving prevention and prosecution, Scottsdale, AZ, April 21, 2000. U.S. G.P.O., 2001.

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Dwivedi, Himanshu. Hacking VoIP: Protocols, attacks, and countermeasures. No Starch Press, 2009.

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Krinklebine, Karlos. Hacking Wall Street: Attacks and countermeasures. [Darkwave Press], 2009.

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Li, Wenjuan, Steven Furnell, and Weizhi Meng, eds. Attacks and Defenses for the Internet-of-Things. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-21311-3.

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Book chapters on the topic "Internet attack"

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Haber, Morey J., and Brad Hibbert. "Internet of Things (IoT)." In Privileged Attack Vectors. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-3048-0_14.

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Haber, Morey J. "Industrial Control Systems (ICS) and Internet of Things (IoT)." In Privileged Attack Vectors. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5914-6_14.

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Chow, Man Chun, Maode Ma, and Zhijin Pan. "Attack Models and Countermeasures for Autonomous Vehicles." In Internet of Things. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76493-7_12.

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Goyal, Sanjeev, Shahin Jabbari, Michael Kearns, Sanjeev Khanna, and Jamie Morgenstern. "Strategic Network Formation with Attack and Immunization." In Web and Internet Economics. Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-54110-4_30.

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Chen, Zhou, Yukun Cheng, Xiaotie Deng, Qi Qi, and Xiang Yan. "Limiting User’s Sybil Attack in Resource Sharing." In Web and Internet Economics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71924-5_8.

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Shin, Seung-won, Ki-young Kim, and Jong-soo Jang. "LSAD: Lightweight SYN Flooding Attack Detector." In Distributed Computing and Internet Technology. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30555-2_45.

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Anwar, Raja Waseem, and Kashif Naseer Qureshi. "Attack Detection Mechanisms for Internet of Everything (IoE) Networks." In Internet of Things. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-45162-1_3.

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Halvorsen, Finn M., Olav Haugen, Martin Eian, and Stig F. Mjølsnes. "An Improved Attack on TKIP." In Identity and Privacy in the Internet Age. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04766-4_9.

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Chang, Chunjie, Changhua Zhu, Honggang Wang, and Changxing Pei. "Survivability Evaluation of Cluster-Based Wireless Sensor Network under DoS Attack." In Internet of Things. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32427-7_18.

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Thomas, Arun, T. Gireesh Kumar, and Ashok Kumar Mohan. "Neighbor Attack Detection in Internet of Things." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8237-5_18.

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Conference papers on the topic "Internet attack"

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Wang, Yikun, Hewu Li, Zeqi Lai, and Jihao Li. "StarMaze: Ring-based Attack in Satellite Internet Constellations." In 2024 IEEE/ACM 32nd International Symposium on Quality of Service (IWQoS). IEEE, 2024. http://dx.doi.org/10.1109/iwqos61813.2024.10682867.

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ElSalamony, Fares, Nahla Barakat, and Ahmad Mostafa. "Unravelling the Sequential Patterns of Cyber Attacks: A Temporal Analysis of Attack Dependencies." In 10th International Conference on Internet of Things, Big Data and Security. SCITEPRESS - Science and Technology Publications, 2025. https://doi.org/10.5220/0013436500003944.

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Umesh, Umesh, Sunil Kumar, Kamlesh Dutta, and Aparna Kumari. "Securing Internet of Medical Things: Exploring Vulnerabilities and Attack Vectors." In 2024 Eighth International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2024. https://doi.org/10.1109/pdgc64653.2024.10984079.

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Yang, Kun, Tianyi Luo, Yanjie Dong, and Aohan Li. "A Seesaw Model Attack Algorithm for Distributed Learning." In 2024 IEEE International Conference on Smart Internet of Things (SmartIoT). IEEE, 2024. https://doi.org/10.1109/smartiot62235.2024.00025.

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Ghafoori, Nasratullah, and Atsuko Miyaji. "The Boomerang Attack on ChaCha Stream Cipher Permutation." In 2024 6th International Conference on Computer Communication and the Internet (ICCCI). IEEE, 2024. http://dx.doi.org/10.1109/iccci62159.2024.10674399.

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Al-Qudah, Rabiah, Neveen Mohammad Hijazi, Moayad Aloqaily, Mohsen Guizani, and Bassem Ouni. "Federated Learning Security: An Incremental Distributed Attack Approach." In 2024 IEEE 10th World Forum on Internet of Things (WF-IoT). IEEE, 2024. https://doi.org/10.1109/wf-iot62078.2024.10811131.

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Murthy, Ashwin, Muralidhar Kurni, Souptik Sen, and Ramesh Krishnamaneni. "A Modified Linknet Architecture for Attack Detection in Internet of Things." In 2024 IEEE International Conference on Communication, Computing and Signal Processing (IICCCS). IEEE, 2024. http://dx.doi.org/10.1109/iicccs61609.2024.10763633.

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Mansoor-ul-haque, Hassan Asghart, Muhammad Hanif Durad, and Anila Usmanl. "Detection of Internet Layer DoS Attack on Cloud Using Deep Learning." In 2023 20th International Bhurban Conference on Applied Sciences and Technology (IBCAST). IEEE, 2023. http://dx.doi.org/10.1109/ibcast59916.2023.10713027.

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Happy, Asif Iqubal, and Subodh Kant Tiwari. "Internet of Vehicle (IoV) Cyber Attack Detection using Machine Learning Techniques." In 2024 4th International Conference on Advancement in Electronics & Communication Engineering (AECE). IEEE, 2024. https://doi.org/10.1109/aece62803.2024.10911517.

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Shrivastava, Anurag, Tanusha Mittal, Muntather Almusawi, Yogendra Kumar, R. J. Anandhi, and Munugapati Bhavana. "Analysis of Apt Attack for Source Tracing in Industrial Internet Environment." In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2024. https://doi.org/10.1109/ic3i61595.2024.10828843.

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Reports on the topic "Internet attack"

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Lee, David, and Ten H. Lai. Internet Attack Traceback: Cross-Validation and Pebble-Trace. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada578556.

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Moriarty, K., and M. Ford. Coordinating Attack Response at Internet Scale (CARIS) Workshop Report. RFC Editor, 2017. http://dx.doi.org/10.17487/rfc8073.

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Moriarty, K. Coordinating Attack Response at Internet Scale 2 (CARIS2) Workshop Report. RFC Editor, 2020. http://dx.doi.org/10.17487/rfc8953.

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Droogan, Julian, Lise Waldek, Brian Ballsun-Stanton, and Jade Hutchinson. Mapping a Social Media Ecosystem: Outlinking on Gab & Twitter Amongst the Australian Far-right Milieu. RESOLVE Network, 2022. http://dx.doi.org/10.37805/remve2022.6.

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Attention to the internet and the online spaces in which violent extremists interact and spread content has increased over the past decades. More recently, that attention has shifted from understanding how groups like the self-proclaimed Islamic State use the internet to spread propaganda to understanding the broader internet environment and, specifically, far-right violent extremist activities within it. This focus on how far right violent extremist—including far-right racially and ethnically motivated violent extremists (REMVEs) within them—create, use, and exploit the online networks in which they exist to promote their hateful ideology and reach has largely focused on North America and Europe. However, in recent years, examinations of those online dynamics elsewhere, including in Australia, is increasing. Far right movements have been active in Australia for decades. While these movements are not necessarily extremist nor violent, understanding how violent far right extremists and REMVEs interact within or seek to exploit these broader communities is important in further understanding the tactics, reach, and impact of REMVEs in Australia. This is particularly important in the online space access to broader networks of individuals and ideas is increasingly expanding. Adding to a steadily expanding body of knowledge examining online activities and networks of both broader far right as well as violent extremist far right populations in Australia, this paper presents a data-driven examination of the online ecosystems in which identified Australian far-right violent extremists exist and interact,1 as mapped by user generated uniform resource locators (URL), or ‘links’, to internet locations gathered from two online social platforms—Twitter and Gab. This link-based analysis has been used in previous studies of online extremism to map the platforms and content shared in online spaces and provide further detail on the online ecosystems in which extremists interact. Data incorporating the links was automatically collected from Twitter and Gab posts from users existing within the online milieu in which those identified far right extremists were connected. The data was collected over three discrete one-month periods spanning 2019, the year in which an Australian far right violent extremist carried out the Christchurch attack. Networks of links expanding out from the Twitter and Gab accounts were mapped in two ways to explore the extent and nature of the online ecosystems in which these identified far right Australian violent extremists are connected, including: To map the extent and nature of these ecosystems (e.g., the extent to which other online platforms are used and connected to one another), the project mapped where the most highly engaged links connect out to (i.e., website domain names), and To explore the nature of content being spread within those ecosystems, what sorts of content is found at the end of the most highly engaged links. The most highly engaged hashtags from across this time are also presented for additional thematic analysis. The mapping of links illustrated the interconnectedness of a social media ecosystem consisting of multiple platforms that were identified as having different purposes and functions. Importantly, no links to explicitly violent or illegal activity were identified among the top-most highly engaged sites. The paper discusses the implications of the findings in light of this for future policy, practice, and research focused on understanding the online ecosystems in which identified REMVE actors are connected and the types of thematic content shared and additional implications in light of the types of non-violent content shared within them.
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Hoffman, P., and B. Schneier. Attacks on Cryptographic Hashes in Internet Protocols. RFC Editor, 2005. http://dx.doi.org/10.17487/rfc4270.

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Leathers, Emily, Clayton Thurmer, and Kendall Niles. Encryption for edge computing applications. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48596.

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As smart sensors and the Internet of Things (IoT) exponentially expand, there is an increased need for effective processing solutions for sensor node data located in the operational arena where it can be leveraged for immediate decision support. Current developments reveal that edge computing, where processing and storage are performed close to data generation locations, can meet this need (Ahmed and Ahmed 2016). Edge computing imparts greater flexibility than that experienced in cloud computing architectures (Khan et al. 2019). Despite these benefits, the literature highlights open security issues in edge computing, particularly in the realm of encryption. A prominent limitation of edge devices is the hardware’s ability to support the computational complexity of traditional encryption methodologies (Alwarafy et al. 2020). Furthermore, encryption on the edge poses challenges in key management, the process by which cryptographic keys are transferred and stored among devices (Zeyu et al. 2020). Though edge computing provides reduced latency in data processing, encryption mechanism utilization reintroduces delay and can hinder achieving real-time results (Yu et al. 2018). The IoT is composed of a wide range of devices with a diverse set of computational capabilities, rendering a homogeneous solution for encryption impractical (Dar et al. 2019). Edge devices are often deployed in operational locations that are vulnerable to physical tampering and attacks. Sensitive data may be compromised if not sufficiently encrypted or if keys are not managed properly. Furthermore, the distributed nature and quantity of edge devices create a vast attack surface that can be compromised in other ways (Xiao et al. 2019). Understanding established mechanisms and exploring emerging methodologies for encryption reveals potential solutions for developing a robust solution for edge computing applications. The purpose of this document is to detail the current research for encryption methods in the edge computing space and highlight the major challenges associated with executing successful encryption on the edge.
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Kim, Kyoung-Sook, and Jiyeong Lee, eds. An Extension Model to attach Points of Interest into IndoorGML. Open Geospatial Consortium, Inc., 2021. http://dx.doi.org/10.62973/20-054r1.

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Christie, Lorna. Physical threats to infrastructure. Parliamentary Office of Science and Technology, 2021. http://dx.doi.org/10.58248/hs23.

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Nir, Y., and V. Smyslov. Protecting Internet Key Exchange Protocol Version 2 (IKEv2) Implementations from Distributed Denial-of-Service Attacks. RFC Editor, 2016. http://dx.doi.org/10.17487/rfc8019.

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Tayeb, Shahab. Taming the Data in the Internet of Vehicles. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2014.

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As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and feature selection/reduction. These pre-processing techniques play an important role in training a neural network to optimize its performance. This research studies the impact of applying normalization techniques as a pre-processing step to learning, as used by the IDSs. The impacts of pre-processing techniques play an important role in training neural networks to optimize its performance. This report proposes a Deep Neural Network (DNN) model with two hidden layers for IDS architecture and compares two commonly used normalization pre-processing techniques. Our findings are evaluated using accuracy, Area Under Curve (AUC), Receiver Operator Characteristic (ROC), F-1 Score, and loss. The experimentations demonstrate that Z-Score outperforms no-normalization and the use of Min-Max normalization.
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