2023 IEEE International Conference on Cyber Security and Resilience (CSR)最新文献_第6页

Early Detection of Reconnaissance Attacks on IoT Devices by Analyzing Performance and Traffic Characteristics 通过分析物联网设备的性能和流量特征，早期发现对物联网设备的侦察攻击

2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224986

Prathibha Keshavamurthy, Sarvesh Kulkarni

{"title":"Early Detection of Reconnaissance Attacks on IoT Devices by Analyzing Performance and Traffic Characteristics","authors":"Prathibha Keshavamurthy, Sarvesh Kulkarni","doi":"10.1109/CSR57506.2023.10224986","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224986","url":null,"abstract":"Cyber attackers use various techniques to gather information about a target in order to identify the vulnerabilities of the target and plan their attack on the target. The first step in planning an attack is reconnaissance. A simple port scan can reveal a lot of useful information about the target machine. Open source tools like ‘nmap’ can quickly scan and gather significant information about hosts on the Internet and provide a great insight into these systems. One cannot attack a system that is not visible to them. When a target system does not respond to scans by attackers, that can be an effective ‘prevention is better than cure’ approach to defense. When a host is actively scanned for multiple open ports by one or more sources, unusual transformations occur in its CPU utilization, the number of incoming and outgoing packets and their average sizes. The purpose of this work is to identify the reliable anomaly markers and demonstrate how they may be used in detecting and preventing reconnaissance scans extremely quickly. We demonstrate promising results for automated early reconnaissance detection and blocking, with live packet capture and analysis. Our proposed solution requires only modest computational resources and can thus operate on resource-constrained Internet of Things (loT) devices and other embedded systems.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130250275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient Early Anomaly Detection of Network Security Attacks Using Deep Learning 基于深度学习的网络安全攻击早期异常检测

2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224923

Tanwir Ahmad, D. Truscan

引用次数: 0

Detecting Subspace Malicious Vectors Attack Against Smart Grid Using Sequence-Alignment Method 基于序列比对的智能电网子空间恶意向量攻击检测

2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224936

Khaled F. Alotaibi, Rafat Rob, Dana Nour, Doaa Zamzami

{"title":"Detecting Subspace Malicious Vectors Attack Against Smart Grid Using Sequence-Alignment Method","authors":"Khaled F. Alotaibi, Rafat Rob, Dana Nour, Doaa Zamzami","doi":"10.1109/CSR57506.2023.10224936","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224936","url":null,"abstract":"The energy sector is moving toward the new Digital Substation Architecture which will introduce new opportunities for the smart grid, applications, monitoring and control. Nevertheless, the new advancements come with its own risk, such as the creation of new security attack surfaces. For example, targeting the data integrity of system, the attacker can manipulate the critical operational data using sophisticated algorithms resulting in incorrect operation decision making. This attack method is aimed to create subspace malicious vectors according to the system configuration to be launched as augmented vectors to the actual field data. This attack will impose the operators to take actions based on altered data which will lead to system failure or blackout. The malicious subspaces vectors will impact the state variables of power grid buses and bypass integrity data validation test. This paper used IEEE-9 bus system to demonstrate the methods for generating malicious subspace vectors to be used and alter the data integrity. The corrupted data can be applied to the integrity validation test and assure the operator that the data integrity has been verified successfully. This paper is proposing a practical solution to detect such an attack scenario by comparing sequences of malicious behaviors used in the analysis of attack activity patterns. Therefore, the proposed method is to evaluate behavior method which is employed on IEEE 9-bus system, and the result has demonstrated the effectiveness of using sequence-alignment methods to detect certain behaviors of generating subspace attacking vectors against smart Grid.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125145364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IoT Forensics: Investigating the Mobile App of Dahua Technology 物联网取证:调查大华科技的移动应用

2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224982

Evangelos Dragonas, C. Lambrinoudakis, Michael Kotsis

引用次数: 0

Evaluating Machine Learning Approaches for Cyber and Physical Anomalies in SCADA Systems 评估SCADA系统中网络和物理异常的机器学习方法

2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224915

L. Faramondi, Francesco Flammini, S. Guarino, R. Setola

{"title":"Evaluating Machine Learning Approaches for Cyber and Physical Anomalies in SCADA Systems","authors":"L. Faramondi, Francesco Flammini, S. Guarino, R. Setola","doi":"10.1109/CSR57506.2023.10224915","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224915","url":null,"abstract":"In recent years, machine learning (ML) techniques have been widely adopted as anomaly-based Intrusion Detection System in order to evaluate cyber and physical attacks against Industrial Control Systems. Nevertheless, a performance comparison of such techniques applied to multiple Cyber-Physical Systems datasets is still missing. In light of this, we propose a comparative study about the performance of four supervised ML-algorithms, Random Forest, k-nearest-Neighbors, Support-Vector-Machine and Naïve-Bayes, applied to three different publicly available datasets from water testbeds. Specifically, we consider three different scenarios where we evaluate: (1) the ability to detect cyber and physical anomalies with respect to the nominal samples, (2) the ability to detect specific types of cyber and physical attacks and (3) the ability to recognize unforeseen attacks without providing any previous knowledge about them. Results show the effectiveness of the ML-techniques in identifying cyber and physical anomalies under some assumptions about their effects on the process dynamics.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128132898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Multi-Class Intrusion Detection System Based on Continual Learning 基于持续学习的多类入侵检测系统

2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224974

Chrysoula Oikonomou, Ilias Iliopoulos, D. Ioannidis, D. Tzovaras

引用次数: 0

A Game of Age of Incorrect Information Against an Adversary Injecting False Data 一场充斥着错误信息的游戏，对抗注入虚假数据的对手

2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224952

Valeria Bonagura, S. Panzieri, F. Pascucci, L. Badia

{"title":"A Game of Age of Incorrect Information Against an Adversary Injecting False Data","authors":"Valeria Bonagura, S. Panzieri, F. Pascucci, L. Badia","doi":"10.1109/CSR57506.2023.10224952","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224952","url":null,"abstract":"Remote sensing enables fast and cost-effective data collection and monitoring, but can be subject to the injection of false data by adversaries. We consider a remote transmitter that is sending status updates about a process to a receiver, incurring a cost when doing so. The system is modeled as transiting between two conditions, implying that the receiver may start with correct knowledge about the process, but this information may become obsolete due to a natural drift of the process toward another regime and the lack of updates by the transmitter. In normal conditions, the transmitter would estimate the age of incorrect information (AoII), a metric proposed in the literature to quantify the time elapsed from the last instant in which the receiver had correct knowledge about the process, to determine the required frequency of updates, balancing it with the transmission cost. We assume the presence of an adversary that may increase the process drift, also incurring its own cost when doing so. The resulting interaction can be analyzed through game theory, with the transmitter and the adversary as strategic players. We present an analysis to determine the conditions for the costs paid by the players and the consequences of their actions on the resulting system performance.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128042841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Verified Value Chains, Innovation and Competition 验证价值链、创新和竞争

2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224911

A. Weber, S. Guilley, René Rathfelder, Marc Stöttinger, Christoph Lüth, Maja Malenko, Torsten Grawunder, S. Reith, A. Puccetti, Jean-Pierre Seifert, N. Herfurth, Hagen Sankowski, G. Heiser

引用次数: 0

Formal Verification of a V2X Privacy Preserving Scheme Using Proverif 使用Proverif的V2X隐私保护方案的形式化验证

2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224908

Simone Bussa, R. Sisto, Fulvio Valenza

引用次数: 0

Nudge to Promote Employees' Information Security Compliance Behavior: A Field Study 助推促进员工信息安全合规行为的实证研究

2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224994

M. Inaba, Takeaki Terada

引用次数: 0