The proposition of balanced and explainable surrogate method for network intrusion detection in streamed real difficult data
4th Oct 2021Handling the data imbalance problem is one of the crucial steps in a machine learning pipeline. The research community is well aware of the effects of data imbalance on machine learning algorithms. At the same time, there is a rising need for explainability of AI, especially in difficult, high-stake domains like network intrusion detection. In this paper, the effects of data balancing procedures on two explainability procedures implemented to explain a neural network used for network intrusio...
Preprocessing Pipelines Including Block-Matching Convolutional Neural Network for Image Denoising to Robustify Deep Reidentification against Evasion Attacks
4th Oct 2021Artificial neural networks have become the go-to solution for computer vision tasks, including problems of the security domain. One such example comes in the form of reidentification, where deep learning can be part of the surveillance pipeline. The use case necessitates considering an adversarial setting—and neural networks have been shown to be vulnerable to a range of attacks. In this paper, the preprocessing defences against adversarial attacks are evaluated, including block-matching conv...
Hybroid: Toward Android Malware Detection and Categorization with Program Code and Network Traffic
21st Sep 2021Android malicious applications have become so sophisticated that they can bypass endpoint protection measures. Therefore, it is safe to admit that traditional anti-malware techniques have become cumbersome, thereby raising the need to develop efficient ways to detect Android malware. In this paper, we present Hybroid, a hybrid Android malware detection and categorization solution that utilizes program code structures as static behavioral features and network traffic as dynamic behavioral feat...
Development of the Information Security Management System Standard for Public Sector Organisations in Estonia
20th Sep 2021Standardisation gives us a common understanding or processes to do something in a commonly accepted way. In information security management, it means to achieve the appropriate security level in the context of known and unknown risks. Each government’s goal should be to provide digital services to its citizens with the acceptable level of confidentiality, integrity and availability. This study elicits the EU countries’ requirements for information security management system (ISMS) standards a...
Security Risk Estimation and Management in Autonomous Driving Vehicles
20th Sep 2021Autonomous vehicles (AV) are intelligent information systems that perceive, collect, generate and disseminate information to improve knowledge to act autonomously and provide its required services of mobility, safety, and comfort to humans. This paper combines the security risk management (ISSRM) and operationally critical threat, asset, and vulnerability evaluation (OCTAVE allegro) methods to define and assess the AV protected assets, security risks, and countermeasures.
Information Security Analysis in the Passenger-Autonomous Vehicle Interaction
20th Sep 2021Autonomous vehicles (AV) are becoming a part of humans’ everyday life. There are numerous pilot projects of driverless public buses; some car manufacturers deliver their premium-level automobiles with advanced self-driving features. Thus, assuring the security of a Passenger–Autonomous Vehicle interaction arises as an important research topic, as along with opportunities, new cybersecurity risks and challenges occur that potentially may threaten Passenger’s privacy and safety on the roads. Th...
Risk-Oriented Design Approach For Forensic-Ready Software Systems
20th Sep 2021Digital forensic investigation is a complex and time-consuming activity in response to a cybersecurity incident or cybercrime to answer questions related to it. These typically are what happened, when, where, how, and who is responsible. However, answering them is often very laborious and sometimes outright impossible due to a lack of useable data. The forensic-ready software systems are designed to produce valuable on-point data for use in the investigation with potentially high evidence val...
A Novel Approach for Network Intrusion Detection Using Multistage Deep Learning Image Recognition
10th Aug 2021The current rise in hacking and computer network attacks throughout the world has heightened the demand for improved intrusion detection and prevention solutions. The intrusion detection system (IDS) is critical in identifying abnormalities and assaults on the network, which have grown in size and pervasiveness. The paper proposes a novel approach for network intrusion detection using multistage deep learning image recognition. The network features are transformed into four-channel (Red, Gree...
Method for Dynamic Service Orchestration in Fog Computing
30th Jul 2021Fog computing is meant to deal with the problems which cloud computing cannot solve alone. As the fog is closer to a user, it can improve some very important QoS characteristics, such as a latency and availability. One of the challenges in the fog architecture is heterogeneous constrained devices and the dynamic nature of the end devices, which requires a dynamic service orchestration to provide an efficient service placement inside the fog nodes. An optimization method is needed to ensure th...