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A multi-level DDoS defense mechanism in container based cloud environment

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2025年第5期28卷 1-19页

作者： Kumar, Anmol Agarwal, Mayank Indian Inst Technol Dept Comp Sci & Engn Patna 801103 Bihar India

DDoS attacks target the victim's service availability. In this paper, we propose a multi-level DDoS defense mechanism that combines two approaches: bandwidth limitation and resource isolation. We consider requests coming from the same source IP that exceed a threshold value as suspicious and treat other requests as genuine. To achieve this goal, we serve suspicious and legitimate user requests in separate containers. We also apply the bandwidth limitation to incoming traffic from containers that serve suspicious requests, ensuring that the victim container does not create a resource contention problem. We chose three different strategies to test our proposed mechanisms: the 50-25-75 strategy, the 100-50-150 strategy, and the 150-75-225 strategy. The experimental results demonstrate that the proposed approach, when subjected to DDoS attacks, reduces the failure rate of genuine requests and maintains response times that are comparable to those under normal network conditions. When there is a DDoS attack, the proposed defense system can make the target service available 87% of the time with the 50-25-75 strategy, 70% of the time with the 100-50-150 strategy, and 85% of the time with the 150-75-225 strategy, in contrast to a single-level DDoS defense system.

关键词： security and protection Distributed denial of service (DDoS) Availability Cloud security Containers Network security

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Reducing Internal Collateral Damage From DDoS Attacks Through Micro-Service Cloud Architecture

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND security 2025年 20卷 1081-1091页

作者： Kumar, Anmol Agarwal, Mayank Indian Inst Technol Patna Dept Comp Sci & Engn Patna 801103 Bihar India

Mitigating DDoS attacks poses a significant challenge for cyber security teams within victim organizations, as these attacks directly target service availability. Most DDoS mitigation solutions focus address the direct effects of DDoS attacks, such as service unavailability and network congestion, while the indirect effects, including collateral damage to legitimate users, receive substantially less attention in the present state-of-the-art. To address this gap, we propose a novel defense architecture designed to mitigate collateral damage and ensure service availability for legitimate users even under attack conditions. The proposed approach employs containerization, micro-services architecture, and traffic segmentation to enhance system resilience and fortify security. We send requests for two distinct services, namely an HTTP-based service and an SSH service, in order to analyze the collateral damage caused by the DDoS attack. The proposed architecture classifies incoming HTTP traffic into two categories: "benign traffic" and "suspicious traffic," determined by the number of requests originating from the same source address. We tested this approach in three different scenarios (S-1, S-2, and S-3). Experimental results demonstrate that the proposed architecture effectively isolates suspicious traffic, mitigating its impact on benign services. This ensures the availability of critical services during a DDoS attack while minimizing collateral damage. In scenarios S-1, S-2, and S-3, it maintains service availability at 3%, 67%, and 98%, respectively, highlighting its efficacy in the face of varying levels of DDoS attack intensity. Furthermore, the architecture is extremely effective in reducing the collateral effects on SSH requests during a DDoS attack. In the S-1 scenario, SSH login time was reduced by 25%, 46%, and 27%, respectively. In the S-2 scenario, the reductions were 99%, 53%, and 29%. In the same vein, the system achieved reductions of 4%, 17%, and 99% in

关键词： Denial-of-service attack Computer crime Cloud computing Prevention and mitigation Containers Virtual machines Computer architecture Computational modeling Accuracy security security and protection cloud computing DDoS attacks containerization

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Medical Systems Data security and Biometric Authentication in Public Cloud Servers

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 2024年第2期12卷 572-582页

作者： Santos, Nelson Ghita, Bogdan Masala, Giovanni Luca Univ Plymouth Sch Engn Comp & Math Plymouth PL4 8AA England Univ Plymouth Ctr Secur Commun & Network Res Plymouth PL4 8AA England Univ Kent Sch Comp Canterbury CT2 7NZ England

Advances in distributed computing and virtualization allowed cloud computing to establish itself as a popular data management and storage option for organizations. However, unclear safeguards, practices, as well as the evolution of legislation around privacy and data protection, contribute to data security being one of the main concerns in adopting this paradigm. Another important aspect hindering the absolute success of cloud computing is the ability to ensure the digital identity of users and protect the virtual environment through logical access controls while avoiding the compromise of its authentication mechanism or storage medium. Therefore, this paper proposes a system that addresses data security wherein unauthorized access to data stored in a public cloud is prevented by applying a fragmentation technique and a NoSQL database. Moreover, a system for managing and authenticating users with multimodal biometrics is also suggested along with a mechanism to ensure the protection of biometric features. When compared with encryption, the proposed fragmentation method indicates better latency performance, highlighting its strong potential use-case in environments with lower latency requirements such as the healthcare IT infrastructure.

关键词： Cloud computing Biometrics (access control) Data security Biomedical imaging Encryption Authentication security Data fragmentation cloud security NoSQL database security and protection

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Lore a Red Team Emulation Tool

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2023年第2期20卷 1596-1608页

作者： Holm, Hannes Swedish Def Res Agcy FOI Dept Informat Secur SE-17290 Stockholm Sweden

This article presents the red team emulation tool Lore, which uses boolean logic and trained models to automatically select and execute red team actions. Lore improves the current state of red team automation, and is the first such tool shown to provide a more fun and educational experience than a manual red team during a cyber defence exercise. In addition to the cyber defence exercise, empirical tests are performed to examine the accuracy of Lore's trained models. The results show that application of these models lead to two times more compromised machines than when applying expert-defined models, and five times more compromised machines than when randomly selecting actions.

关键词： Servers Computational modeling Planning Databases Proposals Automation Manuals Network-level security and protection security and protection machine learning

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Extended Research on the security of Visual Reasoning CAPTCHA

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2023年第6期20卷 4976-4992页

作者： Wang, Ping Gao, Haichang Xiao, Chenxuan Guo, Xiaoyan Gao, Yipeng Zi, Yang Xidian Univ Sch Comp Sci & Technol Xian 710071 Shaanxi Peoples R China

CAPTCHA is an effective mechanism for protecting computers from malicious bots. With the development of deep learning techniques, current mainstream text-based and traditional image-based CAPTCHAs have been proven to be insecure. Therefore, a major effort has been directed toward developing new CAPTCHAs by utilizing some other hard Artificial Intelligence (AI) problems. Recently, some commercial companies (Tencent, NetEase, Geetest, etc.) have begun deploying a new type of CAPTCHA based on visual reasoning to defend against bots. As a newly proposed CAPTCHA, it is therefore natural to ask a fundamental question: are visual reasoning CAPTCHAs as secure as their designers expect? This paper explores the security of visual reasoning CAPTCHAs. We proposed a modular attack and evaluated it on six different real-world visual reasoning CAPTCHAs, which achieved overall success rates ranging from 79.2% to 98.6%. The results show that visual reasoning CAPTCHAs are not as secure as anticipated;this latest effort to use novel, hard AI problems for CAPTCHAs has not yet succeeded. Then, we summarize some guidelines for designing better visual-based CAPTCHAs, and based on the lessons we learned from our attacks, we propose a new CAPTCHA based on commonsense knowledge (CsCAPTCHA) and show its security and usability experimentally.

关键词： CAPTCHAs Visualization Cognition Artificial intelligence security Task analysis Computers CAPTCHA common sense knowledge deep learning security and protection visual reasoning

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LoMar: A Local Defense Against Poisoning Attack on Federated Learning

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2023年第1期20卷 437-450页

作者： Li, Xingyu Qu, Zhe Zhao, Shangqing Tang, Bo Lu, Zhuo Liu, Yao Mississippi State Univ Dept Elect & Comp Engn Mississippi State MS 39762 USA Univ S Florida Dept Elect Engn Tampa FL 33620 USA Univ Oklahoma Sch Comp Sci Tulsa OK 74135 USA Univ S Florida Dept Comp Sci & Engn Tampa FL 33620 USA

Federated learning (FL) provides a high efficient decentralized machine learning framework, where the training data remains distributed at remote clients in a network. Though FL enables a privacy-preserving mobile edge computing framework using IoT devices, recent studies have shown that this approach is susceptible to poisoning attacks from the side of remote clients. To address the poisoning attacks on FL, we provide a two-phase defense algorithm called Local Malicious Factor (LoMar). In phase I, LoMar scores model updates from each remote client by measuring the relative distribution over their neighbors using a kernel density estimation method. In phase II, an optimal threshold is approximated to distinguish malicious and clean updates from a statistical perspective. Comprehensive experiments on four real-world datasets have been conducted, and the experimental results show that our defense strategy can effectively protect the FL system. Specifically, the defense performance on Amazon dataset under a label-flipping attack indicates that, compared with FG+Krum, LoMar increases the target label testing accuracy from 96.0% to 98.8%, and the overall averaged testing accuracy from 90.1% to 97.0%.

关键词： Data models Training Training data Analytical models Optimization Machine learning Kernel Distributed artificial intelligence security and protection defense distribution functions distributed architectures

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MagBox: Keep the risk functions running safely in a magic box

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2023年 140卷 282-298页

作者： Li, YongGang Lin, GuoYuan Chung, Yeh-Ching Ma, YaoWen Lu, Yi Bao, Yu China Univ Min & Technol Sch Comp Sci & Technol Xuzhou 221116 Jiangsu Peoples R China CUHK SZ Sch Data Sci Shenzhen 518172 Guangdong Peoples R China

Address space layout randomization (ASLR) has been widely deployed in operating systems (OS) to hide memory layout, which mitigates code reuse attacks (CRAs). Unfortunately, the memory probing techniques can still provide attackers with enough information to bypass ASLR. Although the control flow integrity (CFI) methods are not affected by code probing, they face the precision problem of control flow graphs (CFG). To make matters worse, most methods rely on the source code of the targets to be protected, which leads to their restrictions on the protection of the objects without source code. To solve these problems, MagBox is proposed in this paper. It identifies the risk functions that can provide gadgets for CRAs by detecting and analyzing attackers' code probing activities. If the function is probed, it will be moved to a new address space. After that, the control flow transfers of the function will be tracked and analyzed in real time to judge their legitimacy. Experiment results and analysis show that MagBox can mitigate CRAs, and only introduces 3.4% performance overhead to the CPU.(c) 2022 Elsevier B.V. All rights reserved.

关键词： Integrity System architecture security and protection Software and system safety side -channel attacks [9]

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A Taxonomy for Python Vulnerabilities

IEEE OPEN JOURNAL OF THE COMPUTER SOCIETY

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IEEE OPEN JOURNAL OF THE COMPUTER SOCIETY 2024年第1期5卷 368-379页

作者： Bogaerts, Frederic C. G. Ivaki, Naghmeh Fonseca, Jose Univ Coimbra Dept Informat Engn CISUC DEI P-3004531 Coimbra Portugal Univ Coimbra Polytech Inst Guarda Dept Informat Engn CISUC P-6300559 Guarda Portugal

Python is one of the most widely adopted programming languages, with applications from web development to data science and machine learning. Despite its popularity, Python is susceptible to vulnerabilities compromising the systems that rely on it. To effectively address these challenges, developers, researchers, and security teams need to identify, analyze, and mitigate risks in Python code, but this is not an easy task due to the scattered, incomplete, and non-actionable nature of existing vulnerability data. This article introduces a comprehensive dataset comprising 1026 publicly disclosed Python vulnerabilities sourced from various repositories. These vulnerabilities are meticulously classified using widely recognized frameworks, such as Orthogonal Defect Classification (ODC), Common Weakness Enumeration (CWE), and Open Web Application security Project (OWASP) Top 10. Our dataset is accompanied by patched and vulnerable code samples (some crafted with the help of AI), enhancing its utility for developers, researchers, and security teams. In addition, a user-friendly website was developed to allow its interactive exploration and facilitate new contributions from the community. Access to this dataset will foster the development and testing of safer Python applications. The resulting dataset is also analyzed, looking for trends and patterns in the occurrence of Python vulnerabilities, with the aim of raising awareness of Python security and providing practical, actionable guidance to assist developers, researchers, and security teams in bolstering their practices. This includes insights into the types of vulnerabilities they should focus on, the most exploited categories, and the common errors that programmers tend to make while coding that can lead to vulnerabilities.

关键词： Python security Taxonomy Codes Artificial intelligence Training Testing Computing milieux error handling and recovery management of computing and information systems reliability software engineering software/software engineering software quality/SQA security and protection testing and debugging

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Rise of the Metaverse?s Immersive Virtual Reality Malware and the Man-in-the-Room Attack & Defenses

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COMPUTERS & security 2023年 127卷

作者： Vondracek, Martin Baggili, Ibrahim Casey, Peter Mekni, Mehdi Brno Univ Technol Fac Informat Technol Bozetechova 2 Brno 61200 Czech Republic Louisiana State Univ Div Comp Sci & Engn Baton Rouge LA 70803 USA Ctr Computat & Technol Baton Rouge LA 70803 USA Univ New Haven West Haven CT 06516 USA Univ New Haven Lab Appl Software Engn Res LASER West Haven CT 06516 USA

The allure of the metaverse along with Virtual Reality (VR) technologies and speed at which they are deployed may shift focus away from security and privacy fundamentals. In this work we employ classic exploitation techniques against cutting edge devices to obtain equally novel results. The unique features of the Virtual Reality landscape set the stage for our primary account of a new attack, the Man-in-the-Room (MitR). This attack, realized from a vulnerable social networking application led to both worming and botnet capabilities being adapted for VR with potential critical impacts affecting millions of users. Our work improves the state-of-the-art in Virtual Reality (VR) security and socio-technical research in VR. It shares several analytical and attacking tools, example exploits, evaluation dataset, and vulnerability signatures with the scientific and professional communities to ensure secure VR software development. The presented results demonstrate the detection and prevention of VR vulnerabilities, and raise questions in the law and policy domains pertaining to VR security and privacy. Published by Elsevier Ltd.

关键词： Emerging technologies Network-level security and protection Network communications Network Protocols protection mechanisms Quality analysis and evaluation System issues security and Privacy protection Authentication Communications Applications Virtual reality security and protection Artificial augmented and virtual realities Invasive software (viruses worms Trojan horses) Unauthorized access (hacking phreaking)

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Secure Connections in Local Networks Despite Multiple Stakeholders 1

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9th International Congress on Information and Communication Technology (ICICT)

作者： Karnapke, Reinhardt Heuer, Dilmari Seidel Hoeckner, Soeren Walther, Karsten Brandenburg Univ Technol Cottbus Senftenberg Cottbus Germany Perinet GmbH Berlin Berlin Germany

ISBN: (数字)9789819735624

ISBN: (纸本)9789819735617;9789819735624

Computer usage authentication mostly comes in two flavors: Either as a key-value pair (name and password) or as certificates from a thrusted authority. Both approaches have their advantages and drawbacks when used for authentication of users on their computer and their computers on the Internet. However, in Industrial Internet of Things environments, when authenticating machines against machines that do not have a permanent Internet connection, this becomes an even bigger issue. In this paper we describe the insufficiencies of these classic approaches when dealing with attacks that originate inside a local network and present our methods of mutual authentication for devices in environments where multiple stakeholders are involved and a permanent Internet connection is not a given.

关键词： Network-level security and protection Local-area networks Software and system safety security and privacy protection Industrial automation Industrial control Process control security and protection Authentication

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