Related papers: Fuzzy approach on modelling cyber attacks patterns…
A design-centric modeling approach was proposed to model the behaviour of the physical processes controlled by Industrial Control Systems (ICS) and study the cascading impact of data-oriented attacks. A threat model was used as input to…
Transferability-based adversarial attacks exploit the ability of adversarial examples, crafted to deceive a specific source Intrusion Detection System (IDS) model, to also mislead a target IDS model without requiring access to the training…
In this paper, we examine the factors that influence the success of false data injection (FDI) attacks in the context of both cyber and physical styles of reinforcement. Many works consider the FDI attack in the context of the ability to…
Recently, the Distributed Denial of Service (DDOS) attacks has been used for different aspects to denial the number of services for the end-users. Therefore, there is an urgent need to design an effective detection method against this type…
A growing number of Internet of Things (IoT) devices are used across consumer, medical, and industrial domains. They interact with their environment through sensors and actuators and connect to networks such as the Internet. Because sensors…
Fuzzing is an effective technique for discovering software vulnerabilities by generating random test inputs and executing them against the target program. However, fuzzing large and complex programs remains challenging due to difficulties…
Indiscriminate data poisoning attacks aim to decrease a model's test accuracy by injecting a small amount of corrupted training data. Despite significant interest, existing attacks remain relatively ineffective against modern machine…
This study evaluates the application of predictive analytics for real-time cyber-attack detection and response, focusing on how statistical and machine learning methods can improve decision-making in Security Operations Centers (SOCs).…
This paper models a decision support system to predict the occurance of suicide attack in a given collection of cities. The system comprises two parts. First part analyzes and identifies the factors which affect the prediction. Admitting…
Until two decades ago, industrial networks were deemed secure due to physical separation from public networks. An abundance of successful attacks proved that assumption wrong. Intrusion detection solutions for industrial application need to…
Fuzzing has proven to be very effective for discovering certain classes of software flaws, but less effective in helping developers process these discoveries. Conventional crash-based fuzzers lack enough information about failures to…
Cyberattacks on enterprise networks exploit complex dependencies among infrastructure, services, and applications, which challenge traditional analysis methods that focus on attack paths or network topology in isolation. In this study, we…
In big data systems, the infrastructure is such that large amounts of data are hosted away from the users. In such a system information security is considered as a major challenge. From a customer perspective, one of the big risks in…
The objective of this is to develop a Fuzzy aided Application layer Semantic Intrusion Detection System (FASIDS) which works in the application layer of the network stack. FASIDS consist of semantic IDS and Fuzzy based IDS. Rule based IDS…
The increasing reliance on diffusion models for generating synthetic images has amplified concerns about the unauthorized use of personal data, particularly facial images, in model training. In this paper, we introduce a novel identity…
The prevalence of cyberattacks on Industrial Control Systems (ICS) has highlighted the necessity for robust security measures and incident response to protect critical infrastructure. This is prominent when Operational Technology (OT)…
Phishing is an online identity theft technique where attackers steal users personal information, leading to financial losses for individuals and organizations. With the increasing adoption of smartphones, which provide functionalities…
While digitization of distribution grids through information and communications technology brings numerous benefits, it also increases the grid's vulnerability to serious cyber attacks. Unlike conventional systems, attacks on many…
Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial…
The threat of attack faced by cyber-physical systems (CPSs), especially when they play a critical role in automating public infrastructure, has motivated research into a wide variety of attack defence mechanisms. Assessing their…