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Добірка наукової літератури з теми "Computer attack"

Автор: Grafiati

Опубліковано: 17 травня 2025

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Статті в журналах з теми "Computer attack"

Sukma Aji, Davito Rasendriya Rizqullah Putra, Imam Riadi, Abdul Fadlil, and Muhammad Nur Faiz. "A Classification Data Packets Using the Threshold Method for Detection of DDoS." Journal of Innovation Information Technology and Application (JINITA) 6, no. 1 (June 28, 2024): 28–36. http://dx.doi.org/10.35970/jinita.v6i1.2224.

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Анотація:

Computer communication is done by first synchronizing one computer with another computer. This synchronization contains Data Packages which can be detrimental if done continuously, it will be categorized as an attack. This type of attack, when performed against a target by many computers, is called a distributed denial of service (DDoS) attack. Technology and the Internet are growing rapidly, so many DDoS attack applications result in these attacks still being a serious threat. This research aims to apply the Threshold method in detecting DDoS attacks. The Threshold method is used to process numeric attributes so obtained from the logfile in a computer network so that data packages can be classified into 2, namely normal access and attack access. Classification results using the Threshold method after going through the fitting process, namely detecting 8 IP Addresses as computer network users and 6 IP addresses as perpetrators of DDoS attacks with optimal accuracy.

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van Heerden, R. P., B. Irwin, I. D. Burke, and L. Leenen. "A Computer Network Attack Taxonomy and Ontology." International Journal of Cyber Warfare and Terrorism 2, no. 3 (July 2012): 12–25. http://dx.doi.org/10.4018/ijcwt.2012070102.

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Computer network attacks differ in the motivation of the entity behind the attack, the execution and the end result. The diversity of attacks has the consequence that no standard classification exists. The benefit of automated classification of attacks, means that an attack could be mitigated accordingly. The authors extend a previous, initial taxonomy of computer network attacks which forms the basis of a proposed network attack ontology in this paper. The objective of this ontology is to automate the classification of a network attack during its early stages. Most published taxonomies present an attack from either the attacker's or defender's point of view. The authors’ taxonomy presents both these points of view. The framework for an ontology was developed using a core class, the “Attack Scenario”, which can be used to characterize and classify computer network attacks.

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Paradise, Paradise, Wahyu Adi Prabowo, and Teguh Rijanandi. "Analysis of Distributed Denial of Service Attacks Using Support Vector Machine and Fuzzy Tsukamoto." JURNAL MEDIA INFORMATIKA BUDIDARMA 7, no. 1 (January 28, 2023): 66. http://dx.doi.org/10.30865/mib.v7i1.5199.

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Анотація:

Advances in technology in the field of information technology services allow hackers to attack internet systems, one of which is the DDOS attack, more specifically, the smurf attack, which involves multiple computers attacking database server systems and File Transfer Protocol (FTP). The DDOS smurf attack significantly affects computer network traffic. This research will analyze the classification of machine learning Support Vector Machine (SVM) and Fuzzy Tsukamoto in detecting DDOS attacks using intensive simulations in analyzing computer networks. Classification techniques in machine learning, such as SVM and fuzzy Tsukamoto, can make it easier to distinguish computer network traffic when detecting DDOS attacks on servers. Three variables are used in this classification: the length of the packet, the number of packets, and the number of packet senders. By testing 51 times, 50 times is the DDOS attack trial dataset performed in a computer laboratory, and one dataset derived from DDOS attack data is CAIDA 2007 data. From this study, we obtained an analysis of the accuracy level of the classification of machine learning SVM and fuzzy Tsukamoto, each at 100%.

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Ramli, Hartini, and Maharaja Yasin Alifsyah. "Analisis Keamanan Komputer Terhadap Serangan Distributed Denial of Service (DDOS)." Journal of Renewable Energy and Smart Device 1, no. 1 (October 17, 2023): 25–30. http://dx.doi.org/10.61220/joresd.v1i1.235.

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Анотація:

Distributed Denial of Service (DDoS) is a type of active attack, an attack that can overwhelm a system by flooding a computer or server with network traffic, disrupting user services. The goal of this attack is usually to disable services and disconnect from the compromised computer or network. The impact is very large for companies or agencies that offer services. Victims of these attacks are unable to provide the services they are supposed to. Due to a bug or constraint on the server you are trying to use and one of the ways to deal with these attacks is to use a computer network firewall, which is useful for protecting computers from various outer space attacks. If the computer has a firewall security system, it is likely that no one on the Internet can access the data on the connected computer or web server. Firewall, works like a partition or wall that blocks the computer from the Internet. This "firewall" allows you to control what data, information, and activity can be transferred from the Internet to your computer and vice versa. With better data security and can avoid DDOS attacks that want to be carried out by irresponsible parties.

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Gunawan, Teddy Surya, Muhammad Kasim Lim, Mira Kartiwi, Noreha Abdul Malik, and Nanang Ismail. "Penetration Testing using Kali Linux: SQL Injection, XSS, Wordpres, and WPA2 Attacks." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 2 (November 1, 2018): 729. http://dx.doi.org/10.11591/ijeecs.v12.i2.pp729-737.

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Анотація:

Nowadays, computers, smart phones, smart watches, printers, projectors, washing machines, fridges, and other mobile devices connected to Internet are exposed to various threats and exploits. Of the various attacks, SQL injection, cross site scripting, Wordpress, and WPA2 attack were the most popular security attacks and will be further investigated in this paper. Kali Linux provides a great platform and medium in learning various types of exploits and peneteration testing. All the simulated attack will be conducted using Kali Linux installed on virtual machine in a compuer with Intel Core i5 and 8 GB RAM, while the victim’s machine is the host computer which run Windows 10 version 1709. Results showed that the attacks launched both on web and firewall were conducted successfully.

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Widodo, Tri, and Adam Sekti Aji. "Pemanfaatan Network Forensic Investigation Framework untuk Mengidentifikasi Serangan Jaringan Melalui Intrusion Detection System (IDS)." JISKA (Jurnal Informatika Sunan Kalijaga) 7, no. 1 (January 25, 2022): 46–55. http://dx.doi.org/10.14421/jiska.2022.7.1.46-55.

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Анотація:

Intrusion Detection System (IDS) is one of the technology to ensure the security of computers. IDS is an early detection system in the event of a computer network attack. The IDS will alert the computer network administrator in the event of a computer network attack. IDS also records all attempts and activities aimed at disrupting computer networks and other computer network attacks. The purpose of this study is to implement IDS on network systems and analyze IDS logs to determine the different types of computer network attacks. Logs on the IDS will be analyzed and will be used as leverage to improve computer network security. The research was carried out using the Network Forensic Investigation Framework proposed by Pilli, Joshi, and Niyogi. The stages of the Network Forensic Investigation Framework are used to perform network simulations, analysis, and investigations to determine the types of computer network attacks. The results show that the Network Forensic Investigation Framework facilitates the investigation process when a network attack occurs. The Network Forensic Investigation Framework is effectively used when the computer network has network security support applications such as IDS or others. IDS is effective in detecting network scanning activities and DOS attacks. IDS gives alerts to administrators because there are activities that violate the rules on the IDS.

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Sun, Fei Xian. "Danger Theory Based Risk Evaluation Model for Smurf Attacks." Key Engineering Materials 467-469 (February 2011): 515–21. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.515.

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Анотація:

Smurf attack belongs to popular Denial-of-Service (DoS) attack, and they can cause devastating impact on computer systems. Inspired by the principles of immune danger theory, a novel risk evaluation model, referred to as DTRESA, for smurf attacks is proposed in this paper. Within the presented model, dangerous smurf attacks are compared to bacterium (or virus) of the immune danger theory, which induce danger signal by simulating cellular distress or cell unnatural death; through immune recognition of artificial lymphocytes, the attacks are detected, and the attack risk is evaluated by calculating the danger signal of host computers. Simulation results and theoretical analysis show that the proposed model is feasible. Thus, it provides a novel solution to DoS detection and computer network security risk assessment.

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Khaliq, Abdul, and Sri Novida Sari. "PEMANFAATAN KERANGKA KERJA INVESTIGASI FORENSIK JARINGAN UNTUK IDENTIFIKASI SERANGAN JARINGAN MENGGUNAKAN SISTEM DETEKSI INTRUSI (IDS)." Jurnal Nasional Teknologi Komputer 2, no. 3 (August 18, 2022): 150–58. http://dx.doi.org/10.61306/jnastek.v2i3.52.

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Анотація:

One of the media to secure computers is to apply Intrusion Detection System (IDS) technology. IDS is an early detection system in the event of a computer network attack. The IDS will alert the computer network administrator in the event of a computer network attack. IDS also records all attempts and activities aimed at disrupting computer networks and other computer network attacks. The purpose of this study is to implement IDS on network systems and analyze IDS logs to determine the types and types of computer network attacks. Logs on the IDS will be analyzed in depth to be used as an effort to improve computer network security. The research method that will be used is applied research. The research was carried out using the Network Forensic Investigation Framework proposed by Pilli, Joshi and Niyogi. The stages of the Network Forensic Investigation Framework are used to perform network simulations, analysis and investigations to determine the types of computer network attacks. The results show that the Network Forensic Investigation Framework facilitates the investigation process when a network attack occurs. The Network Forensic Investigation Framework is effectively used when the computer network has network security support applications such as IDS or others. IDS is effective in detecting network scanning activities and DOS attacks. IDS provides alerts to administrators because there are activities that violate the rules on the IDS.

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Li, Biao. "Research on Computer Network Security and Prevention Strategy." Applied Mechanics and Materials 608-609 (October 2014): 526–30. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.526.

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Анотація:

With the development and popularization of the computer network, the security problem has increasingly become the focus of common concern. The computer network safety problems mainly include: protocol design issues, awareness, management system and technical operation. Hackers on the computer network attack techniques: Deceptive attack, masquerade attacks, vulnerability attack, covert attack and technical attack. Accordingly, we should take the corresponding safety countermeasures: strengthen network security education, using the network protection technology, detection technology and anti-virus technology. This paper mainly analyzes the defects and the security problems of computer network, discusses about the maintenance of computer network security and the way for computer network attack technology defense strategy.

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Miao, Yuantian, Chao Chen, Lei Pan, Qing-Long Han, Jun Zhang, and Yang Xiang. "Machine Learning–based Cyber Attacks Targeting on Controlled Information." ACM Computing Surveys 54, no. 7 (July 2021): 1–36. http://dx.doi.org/10.1145/3465171.

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Анотація:

Stealing attack against controlled information, along with the increasing number of information leakage incidents, has become an emerging cyber security threat in recent years. Due to the booming development and deployment of advanced analytics solutions, novel stealing attacks utilize machine learning (ML) algorithms to achieve high success rate and cause a lot of damage. Detecting and defending against such attacks is challenging and urgent so governments, organizations, and individuals should attach great importance to the ML-based stealing attacks. This survey presents the recent advances in this new type of attack and corresponding countermeasures. The ML-based stealing attack is reviewed in perspectives of three categories of targeted controlled information, including controlled user activities, controlled ML model-related information, and controlled authentication information. Recent publications are summarized to generalize an overarching attack methodology and to derive the limitations and future directions of ML-based stealing attacks. Furthermore, countermeasures are proposed towards developing effective protections from three aspects—detection, disruption, and isolation.

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Дисертації з теми "Computer attack"

Mowery, Keaton. "Beneath the Attack Surface." Thesis, University of California, San Diego, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3712726.

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Анотація:

Computer systems are often analyzed as purely virtual artifacts, a collection of software operating on a Platonic ideal of a computer. When software is executed, it runs on actual hardware: an increasingly complex web of analog physical components and processes, cleverly strung together to present an illusion of pure computation. When an abstract software system is combined with individual hardware instances to form functioning systems, the overall behavior varies subtly with the hardware. These minor variations can change the security and privacy guarantees of the entire system, in both beneficial and harmful ways. We examine several such security effects in this dissertation.

First, we look at the fingerprinting capability of JavaScript and HTML5: when invoking existing features of modern browsers, such as JavaScript execution and 3-D graphics, how are the results affected by underlying hardware, and how distinctive is the resulting fingerprint?

Second, we discuss AES side channel timing attacks, a technique to extract information from AES encryption running on hardware. We present several reasons why we were unable to reproduce this attack against modern hardware and a modern browser.

Third, we examine positive uses of hardware variance: namely, seeding Linux's pseudorandom number generator at kernel initialization time with true entropy gathered during early boot. We examine the utility of these techniques on a variety of embedded devices, and give estimates for the amount of entropy each can generate.

Lastly, we evaluate a cyberphysical system: one which combines physical processes and analog sensors with software control and interpretation. Specifically, we examine the Rapiscan Secure~1000 backscatter X-ray full-body scanner, a device for looking under a scan subject's clothing, discovering any contraband secreted about their person. We present a full security analysis of this system, including its hardware, software, and underlying physics, and show how an adaptive, motivated adversary can completely subvert the scan to smuggle contraband, such as knives, firearms, and plastic explosives, past a Secure~1000 checkpoint. These attacks are entirely based upon understanding the physical processes and sensors which underlie this cyberphysical system, and involve adjusting the contraband's location and shape until it simply disappears.

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Hersén, Nicklas. "Measuring Coverage of Attack Simulations on MAL Attack Graphs." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-292640.

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With the transition from traditional media and the increasing number of digital devices, the threats against digital infrastructure is greater than ever before. New and stricter security requirements are placed on digital platform in order to protect sensitive information against external cyber threats. Threat modeling is a process which involves identifying threats and weakness of a system with the purpose of eliminating vulnerabilities before they are exploited. The Meta Attack Language is a probabilistic threat modeling language which allows security researchers to instantiate specific attack scenarios through the use of attack simulations. Currently there is no support for gathering coverage data from these simulations other than manually checking the compromised state of all objects present in a simulation. The purpose of this work is to develop a coverage extension in order to simplify the threat modeling process. The coverage extension is able to produce coverage estimates from attack simulations executed on specific Meta Attack Language threat models. These metrics are adaptations of existing code- and model coverage metrics commonly used for software- and model testing. There are limitations in what type of data can be effectively presented (such as for exponentially growing data sets) due to the simplicity of the models.
Övergången från traditionella medier till digitala plattformar har lett till en ökad hotbild mot digital infrastruktur. Vikten av att designa säkra plattformar och enheter för att skydda känslig information har lett till framkomsten av nya strängare säkerhetskrav. Hotmodellering är en process med syfte att förebygga att svagheter i ett system utnyttjas av externa parter genom att identifiera brister i systemet. Meta Attack Language är ett hotmodelleringsspråk med stöd för simulering av specifika attack scenarion genom attacksimuleringar. I nuläget finns inget stöd för insamling av täckningsdata från dessa simuleringar. Syftet med detta arbete är att utveckla en tilläggstjänst för insamling av täckningsdata i syfte att underlätta hotmodelleringsprocessen. Den utvecklade tillägstjänsten kan ge en uppskattning av hur väl en modell täcks av en mängd simuleringar. Täckningsvärderna som används av tilläggstjänsten är anpassningar av befintliga mätvärden som används inom uppskattning av källkods- och modelltäckning. Nuvarande implementation har ett flertal begränsningar gällande presentationen av viss typ av data, till exempel exponentiellt växande mätvärden. Detta beror på att modellerna inte är anpassade för denna typ av testning.

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Fang, Pengcheng. "REPTRACKER:TOWARDS AUTOMATIC ATTACK INVESTIGATION." Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1550696995596089.

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Tajdini, M. "Developing an advanced IPv6 evasion attack detection framework." Thesis, Liverpool John Moores University, 2018. http://researchonline.ljmu.ac.uk/9864/.

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Анотація:

Internet Protocol Version 6 (IPv6) is the most recent generation of Internet protocol. The transition from the current Internet Version 4 (IPv4) to IPv6 raised new issues and the most crucial issue is security vulnerabilities. Most vulnerabilities are common between IPv4 and IPv6, e.g. Evasion attack, Distributed Denial of Service (DDOS) and Fragmentation attack. According to the IPv6 RFC (Request for Comment) recommendations, there are potential attacks against various Operating Systems. Discrepancies between the behaviour of several Operating Systems can lead to Intrusion Detection System (IDS) evasion, Firewall evasion, Operating System fingerprint, Network Mapping, DoS/DDoS attack and Remote code execution attack. We investigated some of the security issues on IPv6 by reviewing existing solutions and methods and performed tests on two open source Network Intrusion Detection Systems (NIDSs) which are Snort and Suricata against some of IPv6 evasions and attack methods. The results show that both NIDSs are unable to detect most of the methods that are used to evade detection. This thesis presents a detection framework specifically developed for IPv6 network to detect evasion, insertion and DoS attacks when using IPv6 Extension Headers and Fragmentation. We implemented the proposed theoretical solution into a proposed framework for evaluation tests. To develop the framework, "dpkt" module is employed to capture and decode the packet. During the development phase, a bug on the module used to parse/decode packets has been found and a patch provided for the module to decode the IPv6 packet correctly. The standard unpack function included in the "ip6" section of the "dpkt" package follows extension headers which means following its parsing, one has no access to all the extension headers in their original order. By defining, a new field called all_extension_headers and adding each header to it before it is moved along allows us to have access to all the extension headers while keeping the original parse speed of the framework virtually untouched. The extra memory footprint from this is also negligible as it will be a linear fraction of the size of the whole set of packet. By decoding the packet, extracting data from packet and evaluating the data with user-defined value, the proposed framework is able to detect IPv6 Evasion, Insertion and DoS attacks. The proposed framework consists of four layers. The first layer captures the network traffic and passes it to second layer for packet decoding which is the most important part of the detection process. It is because, if NIDS could not decode and extract the packet content, it would not be able to pass correct information into the Detection Engine process for detection. Once the packet has been decoded by the decoding process, the decoded packet will be sent to the third layer which is the brain of the proposed solution to make a decision by evaluating the information with the defined value to see whether the packet is threatened or not. This layer is called the Detection Engine. Once the packet(s) has been examined by detection processes, the result will be sent to output layer. If the packet matches with a type or signature that system admin chose, it raises an alarm and automatically logs all details of the packet and saves it for system admin for further investigation. We evaluated the proposed framework and its subsequent process via numerous experiments. The results of these conclude that the proposed framework, called NOPO framework, is able to offer better detection in terms of accuracy, with a more accurate packet decoding process, and reduced resources usage compared to both exciting NIDs.

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Van, Heerden Renier Pelser. "A formalised ontology for network attack classification." Thesis, Rhodes University, 2014. http://hdl.handle.net/10962/d1011603.

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Анотація:

One of the most popular attack vectors against computers are their network connections. Attacks on computers through their networks are commonplace and have various levels of complexity. This research formally describes network-based computer attacks in the form of a story, formally and within an ontology. The ontology categorises network attacks where attack scenarios are the focal class. This class consists of: Denial-of- Service, Industrial Espionage, Web Defacement, Unauthorised Data Access, Financial Theft, Industrial Sabotage, Cyber-Warfare, Resource Theft, System Compromise, and Runaway Malware. This ontology was developed by building a taxonomy and a temporal network attack model. Network attack instances (also know as individuals) are classified according to their respective attack scenarios, with the use of an automated reasoner within the ontology. The automated reasoner deductions are verified formally; and via the automated reasoner, a relaxed set of scenarios is determined, which is relevant in a near real-time environment. A prototype system (called Aeneas) was developed to classify network-based attacks. Aeneas integrates the sensors into a detection system that can classify network attacks in a near real-time environment. To verify the ontology and the prototype Aeneas, a virtual test bed was developed in which network-based attacks were generated to verify the detection system. Aeneas was able to detect incoming attacks and classify them according to their scenario. The novel part of this research is the attack scenarios that are described in the form of a story, as well as formally and in an ontology. The ontology is used in a novel way to determine to which class attack instances belong and how the network attack ontology is affected in a near real-time environment.

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Cullum, James J. "Performance analysis of automated attack graph generation software." Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FCullum.pdf.

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Thesis (M.S. in Computer Science)--Naval Postgraduate School, December 2006.
Thesis Advisor(s): Cynthia Irvine, Timothy Levin. "December 2006." Includes bibliographical references (p. 137- 138). Also available in print.

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Harris, Rae. "Spectre: Attack and Defense." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/scripps_theses/1384.

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Анотація:

Modern processors use architecture like caches, branch predictors, and speculative execution in order to maximize computation throughput. For instance, recently accessed memory can be stored in a cache so that subsequent accesses take less time. Unfortunately microarchitecture-based side channel attacks can utilize this cache property to enable unauthorized memory accesses. The Spectre attack is a recent example of this attack. The Spectre attack is particularly dangerous because the vulnerabilities that it exploits are found in microprocessors used in billions of current systems. It involves the attacker inducing a victim’s process to speculatively execute code with a malicious input and store the recently accessed memory into the cache. This paper describes the previous microarchitecture side channel attacks. It then describes the three variants of the Spectre attack. It describes and evaluates proposed defenses against Spectre.

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Almohri, Hussain. "Security risk prioritization for logical attack graphs." Thesis, Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/1114.

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Jafarian, Jafar Haadi. "Cyber Agility for Attack Deterrence and Deception." Thesis, The University of North Carolina at Charlotte, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10686943.

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Анотація:

In recent years, we have witnessed a rise in quantity and sophistication of cyber attacks. Meanwhile, traditional defense techniques have not been adequate in addressing this status quo. This is because the focus has remained mostly on either identifying and patching exploits, or detecting and filtering them. These techniques are only effective when intrusions are known or detectable. However, unknown (zero-day) vulnerabilities are constantly being discovered, and known vulnerabilities are not often patched promptly. Even worse, while defenders need to patch all vulnerabilities and intrusions paths against unknown malicious entities, the attackers only need to discover only one successful intrusion path in a system that is known and static. These asymmetric advantages have constantly kept attackers one step ahead of defenders.

To reverse this asymmetry in cyber warfare, we aim to propose new proactive defense paradigms that can deter or deceive cyber attackers without relying on intrusion detection and prevention and by offering cyber agility as a system property. Cyber agility allows for system configuration to be changed dynamically without jeopardizing operational and mission requirements of the system. In this thesis, we introduce two novel cyber agility techniques based on two paradigms of cyber deterrence and cyber deception. Cyber deterrence techniques aim to deter cyber threats by changing system configurations randomly and frequently. In contrast, cyber deception techniques aim to deflect attacks to fake targets by misrepresenting system configurations strategically and adaptively.

In the first part of this dissertation, we propose a multi-strategy, multi-parameter and multi-dimensional host identity mutation technique for deterring reconnaissance attacks. This deterrence is achieved by mutating IP addresses and anonymizing fingerprints of network hosts both proactively and adaptively. Through simulation and analytical investigation, we show that our approach significantly increases the attack cost for coordinated scanning worms, advanced network reconnaissance techniques, and multi-stage APT attacks.

In the second part, we propose a formal framework to construct active cyber deception plans that are goal-oriented and dynamic. Our framework introduces a deception logic that models consistencies and conflicts among various deception strategies (e.g., lies) and quantifies the benefit and cost of potential deception plans.

In the third part, we demonstrate and evaluate our deception planning framework by constructing an effective deception plan against multi-stage attacks. Through our experimentation, we show that the generated deception plans are effective and economical, and outperform existing or random deception plans.

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Ong, Hoang. "Semantic attack on transaction data anonymised by set-based generalisation." Thesis, Cardiff University, 2015. http://orca.cf.ac.uk/74553/.

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Анотація:

Publishing data that contains information about individuals may lead to privacy breaches. However, data publishing is useful to support research and analysis. Therefore, privacy protection in data publishing becomes important and has received much recent attention. To improve privacy protection, many researchers have investigated how secure the published data is by designing de-anonymisation methods to attack anonymised data. Most of the de-anonymisation methods consider anonymised data in a syntactic manner. That is, items in a dataset are considered to be contextless or even meaningless literals, and they have not considered the semantics of these data items. In this thesis, we investigate how secure the anonymised data is under attacks that use semantic information. More specifically, we propose a de-anonymisation method to attack transaction data anonymised by set-based generalisation. Set-based generalisation protects data by replacing one item by a set of items, so that the identity of an individual can be hidden. Our goal is to identify those items that are added to a transaction during generalisation. Our attacking method has two components: scoring and elimination. Scoring measures semantic relationship between items in a transaction, and elimination removes items that are deemed not to be in the original transaction. Our experiments on both real and synthetic data show that set-based generalisation may not provide adequate protection for transaction data, and about 70% of the items added to the transactions during generalisation can be detected by our method with a precision greater than 85%.

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Книги з теми "Computer attack"

Wilson, Clay. Computer attack and cyberterrorism. NY: Nova Science Publishers, 2009.

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Richard, Mansfield. Hacker attack. San Francisco, Calif: SYBEX, 2000.

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College), Symposium on Computer Network Attack and International Law (1999 Naval War. Computer network attack and international law. Newport, R. I: Naval War College, 2002.

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Briggs, Andy. Virus attack. New York: Walker Books for Young Readers, 2010.

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

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Rooney, Anne. Computer science and IT: Investigating a cyber attack. Chicago, Ill: Capstone Heinemann Library, 2014.

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Mesley, Wendy. Can you hack it?: The attack on personal information. Princeton, NJ: Films for the Humanities & Sciences, 2007.

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Cobb, Adam. Australia's vulnerability to information attack: Towards a national information policy. Canberra, Australia: Strategic and Defence Studies Centre, Australian National University, 1997.

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

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Stevens, Cara J. Redstone Junior High: When Endermen attack. New York: Sky Pony, 2018.

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Більше джерел

Частини книг з теми "Computer attack"

Weik, Martin H. "attack." In Computer Science and Communications Dictionary, 72. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_968.

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Weik, Martin H. "text attack." In Computer Science and Communications Dictionary, 1773. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_19457.

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Weik, Martin H. "analytical attack." In Computer Science and Communications Dictionary, 49. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_649.

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Weik, Martin H. "exhaustion attack." In Computer Science and Communications Dictionary, 549. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_6545.

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Weik, Martin H. "NAK attack." In Computer Science and Communications Dictionary, 1067. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_12053.

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Weik, Martin H. "attack time." In Computer Science and Communications Dictionary, 72. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_969.

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Oe, Issa, Keiichiro Yamamura, Hiroki Ishikura, Ryo Hamahira, and Katsuki Fujisawa. "Superpixel Attack." In Lecture Notes in Computer Science, 141–52. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-8388-9_12.

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Baksi, Anubhab. "Fault Attack." In Computer Architecture and Design Methodologies, 59–98. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6522-6_3.

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Abdoli, F., N. Meibody, and R. Bazoubandi. "An Attacks Ontology for computer and networks attack." In Innovations and Advances in Computer Sciences and Engineering, 473–76. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3658-2_83.

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Nishihara, Hideaki, Yasuyuki Kawanishi, Daisuke Souma, and Hirotaka Yoshida. "On Validating Attack Trees with Attack Effects." In Lecture Notes in Computer Science, 309–24. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54549-9_21.

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Тези доповідей конференцій з теми "Computer attack"

Dadkhah, Pouria, Siavash Ahmadi, and Mohammad Reza Aref. "GenAtt NIDS Attack: A Practical Generative Adversarial Attack Against Network Intrusion Detection Systems." In 2025 29th International Computer Conference, Computer Society of Iran (CSICC), 1–7. IEEE, 2025. https://doi.org/10.1109/csicc65765.2025.10967427.

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Fares, Samar, and Karthik Nandakumar. "Attack To Defend: Exploiting Adversarial Attacks for Detecting Poisoned Models." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 24726–35. IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.02335.

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Al Kader Hammoud, Hasan Abed, Shuming Liu, Mohammed Alkhrashi, Fahad AlBalawi, and Bernard Ghanem. "Look, Listen, and Attack: Backdoor Attacks Against Video Action Recognition." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 3439–50. IEEE, 2024. http://dx.doi.org/10.1109/cvprw63382.2024.00348.

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Amenu, Edwin Xorsenyo, and Sridaran Rajagopal. "Mitigating Address Resolution Protocol (ARP) Attack on Computer System." In 2024 International Conference on Intelligent & Innovative Practices in Engineering & Management (IIPEM), 1–6. IEEE, 2024. https://doi.org/10.1109/iipem62726.2024.10925724.

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Tahat, Majd Z., William B. Glisson, and Baker Al Smadi. "VR Headset Ransomware Attack Vulnerability." In 2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 740–45. IEEE, 2024. http://dx.doi.org/10.1109/ccece59415.2024.10667339.

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Lopuhaä-Zwakenberg, Milan. "Attack Tree Metrics are Operad Algebras." In 2024 IEEE 37th Computer Security Foundations Symposium (CSF), 665–79. IEEE, 2024. http://dx.doi.org/10.1109/csf61375.2024.00005.

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Fezooni, Abdulhady Younes, Ehab Ahmad Ghannoum, Malek Ahmad Ayesh, and Qutaibah Malluhi. "How to Attack a Disconnected Computer." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0251.

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Анотація:

This poster presents how a disconnected computer, that has no network access, can be attacked to retrieve data. Air-gapped devices are thought to be an impenetrable setup because the device is disconnected from the network and cannot be reached by an attacker. Therefore, an infected airgapped computer cannot affect others around it preventing any potential information leaks. People believe/assume that leaking information from an air-gapped machine is impossible. This research effort invalidates this assumption by exploring possible covert channels to get data from victim machines. We take advantage of a hidden acoustic channel that employs the computer speakers and a tiny audio recording device to communicate sensitive data over inaudible near-ultrasonic signals. Data stored on this device can then be processed and displayed as useful information on the attacker’s computer. Hacking methods and the search for new system exploits are being continuously developed and new techniques to obtain data unlawfully are on the rise. Therefore, this work alerts organizations regarding potential threats that they typically ignore by assuming that air-gapped systems are safe. In the past, security researchers have not devoted sufficient time and effort to innovate counter measures for such niche but capable attacks. Spreading awareness is one of the main objectives of this project. This is done by demonstrating that data can be stolen from an ‘air-gapped’ computer, by using methods that people neglect to consider when coming up with plans to protect their computers from attackers. An experiment, such as this, will hopefully push the security field researchers and developers to explore the uncommon methods of unlawful data acquisition and their prevention.

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Kotenko, Igor, and Andrey Chechulin. "Computer attack modeling and security evaluation based on attack graphs." In 2013 IEEE 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS). IEEE, 2013. http://dx.doi.org/10.1109/idaacs.2013.6662998.

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Ingols, Kyle, Matthew Chu, Richard Lippmann, Seth Webster, and Stephen Boyer. "Modeling Modern Network Attacks and Countermeasures Using Attack Graphs." In 2009 Annual Computer Security Applications Conference (ACSAC). IEEE, 2009. http://dx.doi.org/10.1109/acsac.2009.21.

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Ma, Jian, and Da Luo. "Audio adversarial attack: HIS attack." In International Conference on Computer Network Security and Software Engineering (CNSSE 2022), edited by Wenshun Sheng and Yongquan Yan. SPIE, 2022. http://dx.doi.org/10.1117/12.2640809.

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Звіти організацій з теми "Computer attack"

Lenderman, Curtis C. Computer Network Attack: An Operational Tool? Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada415427.

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Busby, Daniel J. Peacetime Use of Computer Network Attack. Fort Belvoir, VA: Defense Technical Information Center, April 2000. http://dx.doi.org/10.21236/ada377624.

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Williamson, Jennie M. Information Operations: Computer Network Attack in the 21st Century. Fort Belvoir, VA: Defense Technical Information Center, April 2002. http://dx.doi.org/10.21236/ada402018.

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Pepyne, David L., and Yu-Chi Ho. Modeling and Analysis of Information Attack in Computer Networks. Fort Belvoir, VA: Defense Technical Information Center, March 2003. http://dx.doi.org/10.21236/ada416393.

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Rolston, Bri. Attack Methodology Analysis: Emerging Trends in Computer-Based Attack Methodologies and Their Applicability to Control System Networks. Office of Scientific and Technical Information (OSTI), June 2005. http://dx.doi.org/10.2172/911827.

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Hanson, Kraig. Organization of DoD Computer Network Defense, Exploitation, and Attack Forces. Fort Belvoir, VA: Defense Technical Information Center, March 2009. http://dx.doi.org/10.21236/ada500822.

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Presby, Timothy D. Computer Network Attack and Its Effectiveness against Non-State Actors. Fort Belvoir, VA: Defense Technical Information Center, February 2006. http://dx.doi.org/10.21236/ada463692.

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Younes, Paul R. Follow the Money: Using Computer Network Attack to Enforce Economic Sanctions. Fort Belvoir, VA: Defense Technical Information Center, May 2001. http://dx.doi.org/10.21236/ada390083.

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Best, Carole N. Computer Network Defense and Attack: Information Warfare in the Department of Defense. Fort Belvoir, VA: Defense Technical Information Center, April 2001. http://dx.doi.org/10.21236/ada394187.

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Pharmer, James, Kevin Cropper, Jennifer McKneely, and Earl Williams. Tactical Tomahawk Weapon Control System v6 Land Attack Combat System Prototype Human-Computer Interface. Fort Belvoir, VA: Defense Technical Information Center, July 2004. http://dx.doi.org/10.21236/ada426346.

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