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نتیجه جستجو - cyber attack

تعداد مقالات یافته شده: 16
ردیف عنوان نوع
1 A comprehensive review on detection of cyber-attacks: Data sets, methods, challenges, and future research directions
بررسی جامع تشخیص حملات سایبری: مجموعه داده‌ها، روش‌ها، چالش‌ ها و جهت‌گیری‌های تحقیقاتی آینده-2022
Rapid developments in network technologies and the amount and scope of data transferred on networks are increasing day by day. Depending on this situation, the density and complexity of cyber threats and attacks are also expanding. The ever-increasing network density makes it difficult for cybersecurity professionals to monitor every movement on the network. More frequent and complex cyberattacks make the detection and identification of anomalies in network events more complex. Machine learning offers various tools and techniques for automating the detection of cyber attacks and for rapid prediction and analysis of attack types. This study discusses the approaches to machine learning methods used to detect attacks. We examined the detection, classification, clustering, and analysis of anomalies in network traffic. We gave the cyber-security focus, machine learning methods, and data sets used in each study we examined. We investigated which feature selection or dimension reduction method was applied to the data sets used in the studies. We presented in detail the types of classification carried out in these studies, which methods were compared with other methods, the performance metrics used, and the results obtained in tables. We examined the data sets of network attacks presented as open access. We suggested a basic taxonomy for cyber attacks. Finally, we discussed the difficulties encountered in machine learning applications used in network attacks and their solutions
Keywords: Cyber attacks | Machine learning | Deep learning | Geometric deep learning | Cyber security | Adversarial machine learning | Intrusion detection
مقاله انگلیسی
2 Advanced digital forensics and anti-digital forensics for IoT systems: Techniques, limitations and recommendations
پزشکی قانونی دیجیتال پیشرفته و پزشکی قانونی ضد دیجیتال برای سیستم های اینترنت اشیا: تکنیک ها، محدودیت ها و توصیه ها-2022
Recently, the number of cyber attacks against IoT domains has increased tremendously. This resulted into both human and financial losses at all IoT levels especially individual and organization levels. Recently, cyber-criminals have kept on leveraging new skills and capabilities by conducting anti-forensics activities and employing techniques and tools to cover their tracks to evade any possible detection of the attack’s events, which has targeted either the IoT system or/and its component(s). Consequently, IoT cyber-attacks are becoming more efficient and more sophisticated with higher risks and threat levels based on their more frequent likelihood to occur and their impact. However, traditional security and forensics solutions are no longer enough to prevent nor investigate such cyber attacks, especially in terms of acquiring evidence for attack investigation. Hence, the need for well-defined, sophisticated, and advanced forensics investigation techniques is highly required to prevent anti-forensics techniques and track down cyber criminals. This paper reviews the different forensics and anti-forensics methods that can be applied in the IoT domain including tools, techniques, types, and challenges, while also discussing the rise of the anti-anti-forensics as a new forensics protection mechanism against anti-forensics activities. This would help forensics investigators to better understand the different anti-forensics tools, methods and techniques that cyber criminals employ while launching their attacks. Moreover, the limitations of the current forensics techniques are discussed, especially in terms of issues and challenges. Finally, this paper presents a holistic view from a literature point of view over the forensics domain in general and for IoT in particular.
Keywords: IoT digital-forensics | IoT anti-forensics | Anti-anti-forensics techniques | Counter anti-forensics | Internet of things forensics | Internet of Forensics Things | IoT digital forensics investigation | IoT source of evidences | Protecting and preserving IoT evidences
مقاله انگلیسی
3 Problems of Poison: New Paradigms and "Agreed" Competition in the Era of AI-Enabled Cyber Operations
مسئله سم: پارادایم های جدید و رقابت "توافق شده" در عصر عملیات سایبری با هوش مصنوعی-2020
Few developments seem as poised to alter the characteristics of security in the digital age as the advent of artificial intelligence (AI) technologies. For national defense establishments, the emergence of AI techniques is particularly worrisome, not least because prototype applications already exist. Cyber attacks augmented by AI portend the tailored manipulation of human vectors within the attack surface of important societal systems at great scale, as well as opportunities for calamity resulting from the secondment of technical skill from the hacker to the algorithm. Arguably most important, however, is the fact that AI-enabled cyber campaigns contain great potential for operational obfuscation and strategic misdirection. At the operational level, techniques for piggybacking onto routine activities and for adaptive evasion of security protocols add uncertainty, complicating the defensive mission particularly where adversarial learning tools are employed in offense. Strategically, AI-enabled cyber operations offer distinct attempts to persistently shape the spectrum of cyber contention may be able to pursue conflict outcomes beyond the expected scope of adversary operation. On the other, AI-augmented cyber defenses incorporated into national defense postures are likely to be vulnerable to “poisoning” attacks that predict, manipulate and subvert the functionality of defensive algorithms. This article takes on two primary tasks. First, it considers and categorizes the primary ways in which AI technologies are likely to augment offensive cyber operations, including the shape of cyber activities designed to target AI systems. Then, it frames a discussion of implications for deterrence in cyberspace by referring to the policy of persistent engagement, agreed competition and forward defense promulgated in 2018 by the United States. Here, it is argued that the centrality of cyberspace to the deployment and operation of soon-to-be-ubiquitous AI systems implies new motivations for operation within the domain, complicating numerous assumptions that underlie current approaches. In particular, AI cyber operations pose unique measurement issues for the policy regime.
Keywords: deterrence | persistent engagement | cyber | AI | machine learning
مقاله انگلیسی
4 Hacking the AI - the Next Generation of Hijacked Systems
هک کردن هوش مصنوعی - نسل بعدی سیستم های ربوده شده-2020
Within the next decade, the need for automation, intelligent data handling and pre-processing is expected to increase in order to cope with the vast amount of information generated by a heavily connected and digitalised world. Over the past decades, modern computer networks, infrastructures and digital devices have grown in both complexity and interconnectivity. Cyber security personnel protecting these assets have been confronted with increasing attack surfaces and advancing attack patterns. In order to manage this, cyber defence methods began to rely on automation and (artificial) intelligence supporting the work of humans. However, machine learning (ML) and artificial intelligence (AI) supported methods have not only been integrated in network monitoring and endpoint security products but are almost omnipresent in any application involving constant monitoring, complex or large volumes of data. Intelligent IDS, automated cyber defence, network monitoring and surveillance as well as secure software development and orchestration are all examples of assets that are reliant on ML and automation. These applications are of considerable interest to malicious actors due to their importance to society. Furthermore, ML and AI methods are also used in audio-visual systems utilised by digital assistants, autonomous vehicles, face-recognition applications and many others. Successful attack vectors targeting the AI of audio-visual systems have already been reported. These attacks range from requiring little technical knowledge to complex attacks hijacking the underlying AI. With the increasing dependence of society on ML and AI, we must prepare for the next generation of cyber attacks being directed against these areas. Attacking a system through its learning and automation methods allows attackers to severely damage the system, while at the same time allowing them to operate covertly. The combination of being inherently hidden through the manipulation made, its devastating impact and the wide unawareness of AI and ML vulnerabilities make attack vectors against AI and ML highly favourable for malicious operators. Furthermore, AI systems tend to be difficult to analyse post-incident as well as to monitor during operations. Discriminating a compromised from an uncompromised AI in real-time is still considered difficult. In this paper, we report on the state of the art of attack patterns directed against AI and ML methods. We derive and discuss the attack surface of prominent learning mechanisms utilised in AI systems. We conclude with an analysis of the implications of AI and ML attacks for the next decade of cyber conflicts as well as mitigations strategies and their limitations.
Keywords: AI hijacking | artificial intelligence | machine learning | cyber attack | cyber security
مقاله انگلیسی
5 Intelligent conditional collaborative private data sharing
به اشتراک گذاری داده های خصوصی شرطی هوشمند-2019
With the advent of distributed systems, secure and privacy-preserving data sharing between different entities (individuals or organizations) becomes a challenging issue. There are several real-world scenarios in which different entities are willing to share their private data only under certain circumstances, such as sharing the system logs when there is indications of cyber attack in order to provide cyber threat intelligence. Therefore, over the past few years, several researchers proposed solutions for collaborative data sharing, mostly based on existing cryptographic algorithms. However, the existing approaches are not appropriate for conditional data sharing, i.e., sharing the data if and only if a pre-defined condition is satisfied due to the occurrence of an event. Moreover, in case the existing solutions are used in conditional data sharing scenarios, the shared secret will be revealed to all parties and re-keying process is necessary. In this work, in order to address the aforementioned challenges, we propose, a ‘‘conditional collaborative private data sharing’’ protocol based on Identity-Based Encryption and Threshold Secret Sharing schemes. In our proposed approach, the condition based on which the encrypted data will be revealed to the collaborating parties (or a central entity) could be of two types: (i) threshold, or (ii) pre-defined policy. Supported by thorough analytical and experimental analysis, we show the effectiveness and performance of our proposal.
مقاله انگلیسی
6 Privacy-friendly platform for healthcare data in cloud based on blockchain environment
بسترهای سازگار با حریم خصوصی برای داده های بهداشت و درمان در ابر مبتنی بر محیط بلاکچین-2019
Data in cloud has always been a point of attraction for the cyber attackers. Nowadays healthcare data in cloud has become their new interest. Attacks on these healthcare data can result in annihilating consequences for the healthcare organizations. Decentralization of these cloud data can minimize the effect of attacks. Storing and running computation on sensitive private healthcare data in cloud are possible by decentralization which is enabled by peer to peer (P2P) network. By leveraging the decentralized or distributed property, blockchain technology ensures the accountability and integrity. Different solutions have been proposed to control the effect of attacks using decentralized approach but these solutions somehow failed to ensure overall privacy of patient centric systems. In this paper, we present a patient centric healthcare data management system using blockchain technology as storage which helps to attain privacy. Cryptographic functions are used to encrypt patient’s data and to ensure pseudonymity. We analyze the data processing procedures and also the cost effectiveness of the smart contracts used in our system.
Keywords: Blockchain | Decentralization | Healthcare data in cloud | Pseudonymity | Privacy | Security | Smart contract
مقاله انگلیسی
7 Big Data Mining of Users Energy Consumption Patterns in the Wireless Smart Grid
کاوش داده های بزرگ الگوهای مصرف انرژی کاربران در شبکه هوشمند بی سیم-2018
A growing number of utility companies are starting to use cellular wireless networks to transmit data in the smart grid. Consequently, millions of users daily energy consumption data are sent by wireless smart meters. However, the broadcast transfer manner of wireless communication makes it naturally vulnerable to cyber attacks. Since smart meter readings can easily be leaked, users energy patterns could be inferred. Hence, users privacy at home is under serious threat. This article begins by introducing the existing work on stealing data from wireless communication networks. Then three types of big data mining schemes for analyzing stolen data are represented. Finally, we discuss several ongoing defense strategies in the era of the wireless smart grid.
Keywords: Big Data, cellular radio, data mining, data privacy, energy consumption, power engineering computing, power system security, security of data,smart meters, smart power grids
مقاله انگلیسی
8 Security analysis of an advanced metering infrastructure
تجزیه و تحلیل امنیت یک زیرساخت اندازه گیری پیشرفته-2017
Article history:Received 28 December 2016Revised 23 February 2017Accepted 25 February 2017 Available online xxxKeywords:Advanced Metering Infrastructure Smart MetersData Collectors Attack Vectors Targets Functionality Attacks ImpactsAn advanced metering infrastructure is an integrated system of smart meters, communica- tions networks and data management systems designed to support the safe, efficient and re- liable distribution of electricity while providing advanced functionality to energy customers. Unfortunately, sophisticated cyber attacks on advanced metering infrastructures are a clear and present danger. The most devastating scenario involves a computer worm that traverses advanced metering infrastructures and permanently disables millions of smart meters.This paper presents a security analysis of an advanced metering infrastructure com- prising more than one million smart meters, 100+ data collectors and two meter data man- agement systems. Specifically, it provides detailed evaluations of the attack surface, targets– especially the critical data collectors – and their functionality, and possible attacks and their impacts. The systematic identification of each target and its functionality, and possi- ble attacks and their direct impacts, are essential to understanding the security landscape as well as specifying and prioritizing mitigation efforts as part of a robust risk management program. Although this work is based on an analysis of one large advanced metering infras- tructure, strong attempts have been undertaken to extract and articulate the commonalities when describing the attack surface, targets, possible attacks and their impacts. Thus, the re- sults presented in this paper can be used as a foundation upon which the unique aspects of an advanced metering infrastructure can be added to create a robust risk management program geared for the specific deployment.© 2017 Elsevier B.V. All rights reserved.
Keywords:Advanced Metering Infrastructure | Smart Meters | Data Collectors | Attack Vectors | Targets | Functionality | Attacks | Impacts
مقاله انگلیسی
9 Dynamic risk management response system to handle cyber threats
سیستم پاسخ ریسک پویا برای پاسخگوئی به تهدیدات سایبری-2017
Appropriate response strategies against new and ongoing cyber attacks must be able to reduce risks down to acceptable levels, without sacrificing a mission for security. Existing approaches either evaluate impacts without considering missions’ negative-side effects, or are manually based on traditional risk assess ments, leaving aside technical difficulties. In this paper we propose a dynamic risk management response system (DRMRS) consisting of a proactive and reactive management software aiming at evaluating threat scenarios in an automated manner, as well as anticipating the occurrence of potential attacks. We adopt a quantitative risk-aware approach that provides a comprehensive view of the threats, by considering their likelihood of success, the induced impact, the cost of the possible responses, and the negative side-effects of a response. Responses are selected and proposed to operators based on financial, operational and threat assessments. The DRMRS is applied to a real case study of a critical infrastructure with multiple threat scenarios.
Keywords: Dynamic system | Automated response | Risk assessment | Graph attack | Security assurance | Cybersecurity
مقاله انگلیسی
10 Design and implementation of UPnP-based energy gateway for demand side management in smart grid
طراحی و پیاده سازی دروازه انرژی مبتنی بر UPnP برای مدیریت سمت تقاضا در شبکه های هوشمند -2017
Legacy electrical grids are urged to evolve towards smart grids, the smarter power delivery system that relies heavily on ICT. Numerous smart grids applications are expected to be developed for efficient man agement and utilization of electricity at the demand side such as home automation, Advanced Metering Infrastructure (AMI), dynamic energy pricing, efficient load management, etc. For easing and boosting the development of new demand side services, the concept of Home Energy Gateway (HEG) has recently been proposed in literature. It involves communication with the utility as well as with devices at the consumer sites. The literature still lacks a comprehensive HEG design that could provide all essential fea tures such as zero-configuration, auto-discovery, seamless plug & play communication, interoperability and integration, customers privacy and communication security. This paper addresses the HEG challenges in an effective way through the design of suitable communi cation frameworks and a security mechanism for enabling strong protection against cyber attacks. The proposed system effectively copes with the interoperability and integration issues between plethora of heterogeneous devices at the consumer sites. The devices in proposed system inherit plug & play fea tures and support zero-configuration and seamless networking. Further, the proposed system design is technology-agnostic and flexible enough to be adopted for the implementation of any specific demand side service. This paper also evaluates the proposed system in real-networking environment and presents performance metrics.
Keywords: Smart grid | Home energy gateway | Universal plug & play | Utility services | Demand side management | Smart home | Privacy | Security
مقاله انگلیسی
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