Article
Chemistry, Analytical
Osama Younes, Umar Albalawi
Summary: The session initiation protocol (SIP) is widely used for multimedia communication, but it faces various security threats. This paper introduces a new protocol called secure-SIP (S-SIP) to overcome the security flaws of SIP and provide authentication, confidentiality, and integrity. S-SIP consists of two protocols: A-SIP for authentication and KP-SIP for key management. Through security analyses, it is demonstrated that S-SIP is secure and outperforms other related protocols in terms of security and performance.
Article
Computer Science, Software Engineering
Nishant Gupta, Nitish Mahajan, Sakshi Kaushal, Naresh Kumar, Harish Kumar, Arun Kumar Sangaiah
Summary: VoIP technology transmits voice over IP networks, with key factors for QoS including choice of codec, packet loss, delay, and jitter, hardware calibration helps in selecting appropriate hardware for real-time processing and transmission. The widespread use of VoIP generates data that can be leveraged for system analysis and prediction to improve performance and cost effectiveness.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2021)
Article
Chemistry, Multidisciplinary
Ismail Melih Tas, Selcuk Baktir
Summary: This study introduces a novel defense mechanism against advanced attacks that exploit vulnerabilities in less-known features of SIP. The defense mechanism consists of statistics, inspection, and action modules to mitigate the SIP-DRDoS attack. Experimental results show that the defense approach can analyze SIP traffic, detect and mitigate SIP flood attacks, significantly reducing CPU usage of the SIP server.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Mitali Sinha, Pramit Bhattacharyya, Sidhartha Sankar Rout, Neha Bhairavi Prakriya, Sujay Deb
Summary: The increasing use of third-party accelerators in modern SoCs can introduce vulnerabilities and lead to system attacks. To detect flooding attacks, we propose a two-step attack detection framework using machine learning, which achieves accurate detection with minimal performance impact.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING
(2022)
Article
Computer Science, Information Systems
Setiyo Budiyanto, Dadang Gunawan
Summary: VoIP is an IP-based communication technology commonly used for mobile communication activities. The main concern in its application is maintaining information confidentiality and protection for users, which requires the addition of VPN features. This research aims to compare the Quality of Service (QoS) and analyze security system mechanisms to determine the best quality of tunneling security protocols for VoIP.
Article
Computer Science, Information Systems
Abdelwahed Berguiga, Ahlem Harchay
Summary: The successful deployment of Internet of Things (IoT) has led to important smart applications, with the Internet of Medical Things (IoMT) being one of the most widely deployed applications in the fight against COVID-19, providing extensive healthcare services. However, IoT faces security threats from attacks such as TCP SYN flooding, and this paper addresses the issue of detecting denial of service attacks in the Internet of Medical Things using a new intrusion detection algorithm.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Green & Sustainable Science & Technology
Chih-Hsiang Hsieh, Wei-Kuan Wang, Cheng-Xun Wang, Shi-Chun Tsai, Yi-Bing Lin
Summary: This study proposes a defense method based on deep learning to detect DDoS attacks through rerouting and network traffic monitoring, effectively distinguishing between malicious traffic and benign traffic, preventing link-flooding attacks.
Article
Engineering, Electrical & Electronic
Jasmina Barakovic Husic, Sabina Barakovic, Seudin Kasumovic
Summary: The growth of session control signalling in VoIP, based on SIP, may lead to infrastructure overload and degradation of service quality. This study looked at the impact of SIP message differentiation on the quality of VoIP session control procedures, proposing an algorithm for SIP message prioritization that improved performance metrics.
IETE TECHNICAL REVIEW
(2021)
Article
Chemistry, Analytical
Jin Wang, Liping Wang
Summary: This paper highlights the importance of SDN security and proposes an online attack detection and mitigation SDN defense system, consisting of anomaly detection and mitigation modules. Experimental results demonstrate the system's ability to accurately identify and effectively mitigate DDoS attacks.
Article
Computer Science, Information Systems
Vladimir Borgiani, Patrick Moratori, Juliano F. Kazienko, Emilio R. R. Tubino, Silvio E. Quincozes
Summary: Wireless sensor networks are commonly used in the Industrial Internet-of-Things, but vulnerable to security attacks. A distributed congestion control method has been proposed to mitigate DoS attacks, showing potential application in a sensor network scenario with 500 nodes.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Xu Chen, Wei Feng, Yantian Luo, Meng Shen, Ning Ge, Xianbin Wang
Summary: This article addresses the defense problem of link flooding attacks (LFA) in the Internet of Things (IoT) by establishing a two-person Bayesian game model and deriving the rational behaviors of the attacker and optimal strategies of the defender. Based on the obtained results, a cost-effective defense decision framework is proposed, along with feasible suggestions.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Public, Environmental & Occupational Health
Philippe Pirard, Yvon Motreff, Lise Eilin Stene, Gabrielle Rabet, Cecile Vuillermoz, Stephanie Vandentorren, Thierry Baubet, Antoine Messiah
Summary: This study investigates the initiation of multiple-session psychological care (MSPC) and associated factors after the Paris terrorist attacks. The findings suggest that witnesses were less likely to receive MSPC compared to those who were directly threatened, despite having psychological disorders. Associations for victims and outreach psychological support appear to facilitate access to MSPC. Additionally, training physicians to screen for psychological disorders in individuals with somatic symptoms is crucial.
ARCHIVES OF PUBLIC HEALTH
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Hafiz Muhammad Ashja Khan, Usman Inayat, Muhammad Fahad Zia, Fahad Ali, Taila Jabeen, Syed Moshin Ali
Summary: VoIP is an important technology in a network communication system, with security being a crucial factor. This paper discusses the use of Session Initiation Protocol in VoIP services and methods to prevent flooding attacks. Additionally, it describes vulnerabilities and tests related to VoIP security tools to identify weaknesses that pose threats to the security of Voice over Internet Protocol.
4TH INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING (IC)2
(2021)
Article
Engineering, Multidisciplinary
Ali K. Abdulrazzaq
Summary: This paper studies the performance impact of applying a set of bulk cipher algorithms of TLS over SIP server's communication. The research illustrates how each cipher algorithm affects SIP server performance, with results showing varying degrees of impact on CPU usage and throughput.
JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Ayman Al-Ani, Ahmed K. Al-Ani, Shams A. Laghari, Selvakumar Manickam, Khin Wee Lai, Khairunnisa Hasikin
Summary: IPv6 is positioned as the next-generation Internet Protocol for future internet connectivity and IT expansion. This paper proposes an NDP security mechanism based on the Ed25519 digital signature to authenticate IPv6 hosts and prevent unauthorized devices from joining the network. The proposed NDPsec mechanism successfully prevents cyberattacks with significantly reduced processing time and traffic overhead compared to other security mechanisms.
Article
Computer Science, Information Systems
Christos Lyvas, Costas Lambrinoudakis, Dimitris Geneiatakis
Summary: This paper studies the impact of Android task and hijacking attacks on end users' data confidentiality, and proposes an operating system level defense mechanism. The developed tool demonstrates various vulnerable configurations, while the proposed solution has been shown to have negligible impact on Android task management.
COMPUTERS & SECURITY
(2021)
Proceedings Paper
Computer Science, Information Systems
Bruno Marchand, Nikolaos Pitropakis, William J. Buchanan, Costas Lambrinoudakis
Summary: Web addresses serve as a vector for attackers to deliver harmful effects, but machine learning can automate the detection of malicious URLs. However, without defenses against adversarial manipulation, the accuracy of malicious URL detection can be significantly compromised.
TRUST, PRIVACY AND SECURITY IN DIGITAL BUSINESS (TRUSTBUS 2021)
(2021)
Article
Computer Science, Information Systems
Dimitra Georgiou, Costas Lambrinoudakis
Summary: This paper discusses the impact of the General Data Protection Regulation (GDPR) on the healthcare industry and provides guidelines on conducting a Data Protection Impact Assessment (DPIA). It focuses on identifying processing purposes, data categories, evaluating GDPR compliance, and conducting a Gap Analysis. The main contribution is outlining the organizational and legal requirements that healthcare organizations must meet.
Article
Computer Science, Information Systems
Christos Kalloniatis, Costas Lambrinoudakis, Mathias Musahl, Athanasios Kanatas, Stefanos Gritzalis
Summary: This paper proposes a Privacy and Data Protection Framework for eHealth/M-Health systems to meet GDPR requirements and protect the rights of data subjects. The framework supports the combination of privacy by design principles with GDPR requirements, and provides a validation process to ensure the fulfillment of data protection objectives.
COMPUTER SCIENCE AND INFORMATION SYSTEMS
(2021)
Proceedings Paper
Computer Science, Information Systems
Dimitra Georgiou, Costas Lambrinoudakis
TRUST, PRIVACY AND SECURITY IN DIGITAL BUSINESS, TRUSTBUS 2020
(2020)
Proceedings Paper
Computer Science, Information Systems
Bridget Khursheed, Nikolaos Pitropakis, Sean McKeown, Costas Lambrinoudakis
TRUST, PRIVACY AND SECURITY IN DIGITAL BUSINESS, TRUSTBUS 2020
(2020)
Proceedings Paper
Computer Science, Information Systems
Zafeiroula Georgiopoulou, Eleni-Laskarina Makri, Costas Lambrinoudakis
COMPUTER SECURITY, ESORICS 2019
(2020)
Proceedings Paper
Computer Science, Information Systems
Eleni-Laskarina Makri, Zafeiroula Georgiopoulou, Costas Lambrinoudakis
COMPUTER SECURITY, ESORICS 2019
(2020)
Proceedings Paper
Computer Science, Information Systems
Nikolaos Pitropakis, Marios Logothetis, Gennady Andrienko, Jason Stefanatos, Eirini Karapistoli, Costas Lambrinoudakis
COMPUTER SECURITY, ESORICS 2019
(2020)
Proceedings Paper
Computer Science, Interdisciplinary Applications
George Drivas, Argyro Chatzopoulou, Leandros Maglaras, Costas Lambrinoudakis, Allan Cook, Helge Janicke
2020 IEEE 44TH ANNUAL COMPUTERS, SOFTWARE, AND APPLICATIONS CONFERENCE (COMPSAC 2020)
(2020)
Article
Computer Science, Information Systems
Dimitra Georgiou, Costas Lambrinoudakis
Article
Computer Science, Information Systems
Zafeiroula Georgiopoulou, Eleni-Laskarina Makri, Costas Lambrinoudakis
INFORMATION AND COMPUTER SECURITY
(2020)
Article
Computer Science, Information Systems
Eleni-Laskarina Makri, Zafeiroula Georgiopoulou, Costas Lambrinoudakis
INFORMATION AND COMPUTER SECURITY
(2020)
Proceedings Paper
Computer Science, Information Systems
Costas Lambrinoudakis
TRUST, PRIVACY AND SECURITY IN DIGITAL BUSINESS
(2018)
Proceedings Paper
Engineering, Electrical & Electronic
Panagiotis Pantazopoulos, Sammy Haddad, Costas Lambrinoudakis, Christos Kalloniatis, Konstantinos Maliatsos, Athanasios Kanatas, Andras Varadi, Matthieu Gay, Angelos Amditis
2018 IEEE 19TH INTERNATIONAL SYMPOSIUM ON A WORLD OF WIRELESS, MOBILE AND MULTIMEDIA NETWORKS (WOWMOM)
(2018)
Article
Computer Science, Information Systems
Kashan Ahmed, Syed Khaldoon Khurshid, Sadaf Hina
Summary: This paper mainly introduces the construction of the cyber threat intelligence knowledge graph and the information extraction technique. By using joint extraction technique, it solves the problem of traditional techniques becoming ineffective due to the increasing size of CTI data. Experimental results show that this technique outperforms state-of-the-art models in knowledge triple extraction on CTI data and improves the F1 score.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Xinlong He, Yang Xu, Sicong Zhang, Weida Xu, Jiale Yan
Summary: This paper proposes a new membership inference attack method in federated learning, which utilizes data poisoning and sequence prediction confidence. The attack is effective and results in minimal overall model performance degradation.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Tieming Chen, Huan Zeng, Mingqi Lv, Tiantian Zhu
Summary: In this paper, the authors propose a deep learning based dynamic malware detection method called CTIMD, which integrates threat knowledge from CTIs into the learning process of API call sequences with runtime parameters. Experimental results show that CTIMD outperforms existing methods in terms of performance.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Wonwoo Choi, Minjae Seo, Seongman Lee, Brent Byunghoon Kang
Summary: This paper proposes SUM, a backward-edge control flow protection scheme for ARM Cortex-M processors. It combines MPU and the overlooked hardware feature FaultMask to achieve efficient and robust protection. The empirical evaluation shows minimal runtime overhead for the proposed solution.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Liliana Ribeiro, Ines Sousa Guedes, Carla Sofia Cardoso
Summary: Phishing susceptibility is influenced by individual and contextual factors. The study found that individuals who perceive themselves as capable of detecting phishing and those who use online services more frequently are more susceptible to phishing. However, technology competencies and other individual variables do not predict phishing susceptibility.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Wenjie Wang, Yuanhai Shao, Yiju Wang
Summary: In this paper, we investigate the adversarial perturbations of twin support vector machines (TWSVMs) and propose an optimization framework, which provides explicit solutions to increase the interpretability of the conclusion and convenience for calculation.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Snofy D. Dunston, V. Mary Anita Rajam
Summary: This paper proposes a novel adversarial attack technique that can synthesize adversarial images to mislead deep learning models, and also studies interpretability plots. The research findings show that the proposed attack technique influences the interpretability plots, regardless of the success of the attack.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Junchen Li, Guang Cheng, Zongyao Chen, Peng Zhao
Summary: Protocol Reverse Engineering (PRE) is a direct approach for analyzing unknown traffic. This paper proposes a method for clustering unknown traffic based on private protocol labels, and the experimental results demonstrate its advantages on real-world network traffic.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Rafal Kozik, Massimo Ficco, Aleksandra Pawlicka, Marek Pawlicki, Francesco Palmieri, Michal Choras
Summary: The inclusion of Explainability of Artificial Intelligence (xAI) has become a mandatory requirement for designing and implementing reliable, interpretable, and ethical AI solutions. However, it has been shown that xAI can enable successful adversarial attacks in the domain of fake news detection, leading to a decrease in AI security. This paper presents an attack scheme that uses an explainable solution to reshape the structure of the original message, allowing the adversary to manipulate the model's prediction while keeping the message's meaning intact.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Benyuan Yang, Lili Luo, Zhimeng Wang
Summary: Interoperation is widely used in practical industrial applications, but merging local access control policies may lead to security violations. Dealing with these issues in a multidomain environment is critical, but finding the maximum secure interoperation among individual systems poses a challenge due to the large number of entities and access involved.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Binghui Zou, Chunjie Cao, Longjuan Wang, Sizheng Fu, Tonghua Qiao, Jingzhang Sun
Summary: The ongoing struggle between security researchers and malware has led to the exploration of using convolutional neural networks and capsule networks for classification and identification of malware. However, training these networks requires a significant amount of data and parameters, and the research on capsule networks is still in its early stages, posing challenges.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Hongsong Chen, Xingyu Li, Wenmao Liu
Summary: Multivariate time-series anomaly detection is crucial for maintaining normal operation of physical equipment. Recent advances have been made in this field, but two challenges have limited the model's ability to generalize. To address these challenges, a multivariate time-series anomaly detection model consisting of a characterization network and a forecasting network is proposed. Experimental results demonstrate that this method outperforms baseline methods in terms of detection performance and robustness.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Roberto Doriguzzi-Corin, Domenico Siracusa
Summary: This paper discusses the application of federated learning in the field of cybersecurity and proposes an adaptive mechanism-based federated learning solution for DDoS attack detection in dynamic cybersecurity scenarios. Through experiments, it is demonstrated that the proposed solution outperforms state-of-the-art federated learning algorithms in terms of convergence time and accuracy.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Antonio Giovanni Schiavone
Summary: The usage of HTTPS protocol is crucial for secure communication with websites, ensuring the confidentiality, integrity, and authenticity of online data transmissions. The Municipality2HTTPS research project analyzed the implementation of HTTPS in Italian municipalities' websites and identified areas for improvement.
COMPUTERS & SECURITY
(2024)
Article
Computer Science, Information Systems
Domna Bilika, Nikoletta Michopoulou, Efthimios Alepis, Constantinos Patsakis
Summary: Voice Assistants (VAs) are widely used in smart devices, but are vulnerable to attacks, as shown by experiments with popular VAs revealing successful attack rates exceeding 30% and statistical variations among vendors, calling for additional countermeasures to protect user information.
COMPUTERS & SECURITY
(2024)