Digital 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...More>>
Publications & Demonstrators
All accepted publications from SPARTA partners under its funding as well as videos presenting some of the work done under SPARTA
Publications
A Novel Approach for Network Intrusion Detection Using Multistage Deep Learning Image Recognition
Toldinas, Jevgenijus, Algimantas Venčkauskas, Robertas Damaševičius, Šarūnas Grigaliūnas, Nerijus Morkevičius, and Edgaras Baranauskas
The 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...More>>
Domains: network intrusion detection; deep learning; image representation
Method for Dynamic Service Orchestration in Fog Computing
Morkevicius, Nerijus, Algimantas Venčkauskas, Nerijus Šatkauskas, and Jevgenijus Toldinas
Fog 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...More>>
Domains: QoS, Fog Computing
SI‐AKAV: Secure integrated authentication and key agreement for cellular‐connected IoT devices in vehicular social networks
Alireza Esfahani, Jérémie Decouchant, Marcus Völp, Shahid Mumtaz, Kostromitin Konstantin Igorevich
Vehicular social networking (VSN), as a novel communication paradigm, exploits opportunistic encounters among vehicles for mobile social networking, collaborative content dissemination, and to provide a variety of services for users and their vehicles. VSNs promise to solve problems such as the ever‐increasing number of road accidents, or traffic congestion, by...More>>
Domains: Vehicular social networking
Securing Organization’s Data: A Role-Based Authorized Keyword Search Scheme with Efficient Decryption
Nazatul Haque Sultan, Maryline Laurent, Vijay Varadharajan
For better data availability and accessibility while ensuring data secrecy, organizations often tend to outsource their encrypted data to the cloud storage servers, thus bringing the challenge of keyword search over encrypted data. In this paper, we propose a novel authorized keyword search scheme using Role-Based Encryption (RBE) technique in...More>>
Domains: Security and privacy, Privacy-preserving protocols, Management and querying of encrypted data
Self-secured PUF: Protecting the Loop PUF by Masking
Tebelmann, L., Danger, J. L., & Pehl, M.
Physical Unclonable Functions (PUFs) provide means to gen-erate chip individual keys, especially for low-cost applications such as theInternet of Things (IoT). They are intrinsically robust against reverseengineering, and more cost-effective than non-volatile memory (NVM).For several PUF primitives, countermeasures have been proposed to mit-igate side-channel weaknesses. However, most mitigation techniques re-quire...More>>
Domains: Physically Unclonable Function, Side-Channel Analysis, RO PUF, Loop PUF, Masking, Countermeasure, IoT
Ensemble-Based Classification Using Neural Networks and Machine Learning Models for Windows PE Malware DetectionNeural Networks
Damaševičius, Robertas; Venčkauskas, Algimantas; Toldinas, Jevgenijus; Grigaliūnas, Šarūnas
The security of information is among the greatest challenges facing organizations and institutions. Cybercrime has risen in frequency and magnitude in recent years, with new ways to steal, change and destroy information or disable information systems appearing every day. Among the types of penetration into the information systems where confidential...More>>
Domains: Neural Networks, Machine Learning, Malware
Information Sharing in Cyber Defence Exercises
Eduardas Kutka, Aušrius Juozapavičius, Linas Bukauskas, Agnė Brilingaitė
Availability and easy access to sophisticated cyber penetration testing tools enable exploitation of vulnerabilities in different systems globally. Repetitive nature and recognisable signatures of attacks raise demand for effective information sharing. Timely warnings about cyber incidents in other systems make it possible to identify related attacks locally. International cyber community...More>>
Domains: Cyber defence exercises, Incident information sharing, Indicators of compromise, Collaborative defence
Machine Learning for Driver Detection through CAN bus
Fabio Martinelli, Francesco Mercaldo, Antonella Santone
In last years vehicular network safety and security are attracting interest from both industries and researchers. In this paper, starting from a set of features gathered from the in-vehicle CAN bus, we show how machine learning algorithms can be useful to discriminate between the car owner and impostors. Furthermore, we...More>>
Domains: Automated vehicles, Machine Learning