Search results for "Tietoturva"
showing 10 items of 184 documents
Security Assessment of a Distributed, Modbus-based Building Automation System
2017
Building automation systems were designed in an era when security was not a concern as the systems were closed from outside access. However, multiple benefits can be found in connecting such systems over the Internet and controlling a number of buildings from a single location. Security breaches towards building automation systems are increasing and may cause direct or indirect damages to the target organization or even the residents of the building. This work presents an approach to apply a method of data flow recognition and environment analysis to building automation through a case study on a distributed building automation system utilizing the Modbus protocol at the sites and presents s…
On Detection of Network-Based Co-residence Verification Attacks in SDN-Driven Clouds
2017
Modern cloud environments allow users to consume computational and storage resources in the form of virtual machines. Even though machines running on the same cloud server are logically isolated from each other, a malicious customer can create various side channels to obtain sensitive information from co-located machines. In this study, we concentrate on timely detection of intentional co-residence attempts in cloud environments that utilize software-defined networking. SDN enables global visibility of the network state which allows the cloud provider to monitor and extract necessary information from each flow in every virtual network in online mode. We analyze the extracted statistics on d…
Towards a Security Competence of Software Developers
2020
Software growth has been explosive as people depend heavily on software on daily basis. Software development is a human-intensive effort, and developers' competence in software security is essential for secure software development. In addition, ubiquitous computing provides an added complexity to software security. Studies have treated security competences of software developers as a subsidiary of security engineers' competence instead of software engineers' competence, limiting the full knowledge of the security competences of software developers. This presents a crucial challenge for developers, educators, and users to maintain developers' competences in security. As a first step in pushi…
Finding Software Bugs in Embedded Devices
2021
AbstractThe goal of this chapter is to introduce the reader to the domain of bug discovery in embedded systems which are at the core of the Internet of Things. Embedded software has a number of particularities which makes it slightly different to general purpose software. In particular, embedded devices are more exposed to software attacks but have lower defense levels and are often left unattended. At the same time, analyzing their security is more difficult because they are very “opaque”, while the execution of custom and embedded software is often entangled with the hardware and peripherals. These differences have an impact on our ability to find software bugs in such systems. This chapt…
Stopping injection attacks with code and structured data
2018
Injection attacks top the lists of the most harmful software vulnerabilities. Injection vulnerabilities are both commonplace and easy to exploit, which makes development of injection protection schemes important. In this article, we show how injection attacks can be practically eliminated through the use of structured data paired with cryptographic verification codes upon transmission. peerReviewed
State of the Art Literature Review on Network Anomaly Detection
2018
As network attacks are evolving along with extreme growth in the amount of data that is present in networks, there is a significant need for faster and more effective anomaly detection methods. Even though current systems perform well when identifying known attacks, previously unknown attacks are still difficult to identify under occurrence. To emphasize, attacks that might have more than one ongoing attack vectors in one network at the same time, or also known as APT (Advanced Persistent Threat) attack, may be hardly notable since it masquerades itself as legitimate traffic. Furthermore, with the help of hiding functionality, this type of attack can even hide in a network for years. Additi…
A Novel Deep Learning Stack for APT Detection
2019
We present a novel Deep Learning (DL) stack for detecting Advanced Persistent threat (APT) attacks. This model is based on a theoretical approach where an APT is observed as a multi-vector multi-stage attack with a continuous strategic campaign. To capture these attacks, the entire network flow and particularly raw data must be used as an input for the detection process. By combining different types of tailored DL-methods, it is possible to capture certain types of anomalies and behaviour. Our method essentially breaks down a bigger problem into smaller tasks, tries to solve these sequentially and finally returns a conclusive result. This concept paper outlines, for example, the problems an…
State of the Art Literature Review on Network Anomaly Detection with Deep Learning
2018
As network attacks are evolving along with extreme growth in the amount of data that is present in networks, there is a significant need for faster and more effective anomaly detection methods. Even though current systems perform well when identifying known attacks, previously unknown attacks are still difficult to identify under occurrence. To emphasize, attacks that might have more than one ongoing attack vectors in one network at the same time, or also known as APT (Advanced Persistent Threat) attack, may be hardly notable since it masquerades itself as legitimate traffic. Furthermore, with the help of hiding functionality, this type of attack can even hide in a network for years. Additi…
Artificial Intelligence for Cybersecurity: A Systematic Mapping of Literature
2020
Due to the ever-increasing complexities in cybercrimes, there is the need for cybersecurity methods to be more robust and intelligent. This will make defense mechanisms to be capable of making real-time decisions that can effectively respond to sophisticated attacks. To support this, both researchers and practitioners need to be familiar with current methods of ensuring cybersecurity (CyberSec). In particular, the use of artificial intelligence for combating cybercrimes. However, there is lack of summaries on artificial intelligent methods for combating cybercrimes. To address this knowledge gap, this study sampled 131 articles from two main scholarly databases (ACM digital library and IEEE…
Family Matters : Abusing Family Refresh Tokens to Gain Unauthorised Access to Microsoft Cloud Services Exploratory Study of Azure Active Directory Fa…
2022
Azure Active Directory (Azure AD) is an identity and access management service used by Microsoft 365 and Azure services and thousands of third-party service providers. Azure AD uses OIDC and OAuth protocols for authentication and authorisation, respectively. OAuth authorisation involves four parties: client, resource owner, resource server, and authorisation server. The resource owner can access the resource server using the specific client after the authorisation server has authorised the access. The authorisation is presented using a cryptographically signed Access Token, which includes the identity of the resource owner, client, and resource. During the authorisation, Azure AD assigns Ac…