Sökning: "Intrusion Detection System IDS"

Visar resultat 1 - 5 av 28 uppsatser innehållade orden Intrusion Detection System IDS.

  1. 1. A Concept for an Intrusion Detection System over Automotive Ethernet

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Hanna Lindwall; Pontus Ovhagen; [2020]
    Nyckelord :Intrusion Detection System; Deep Packet Inspection; Specification-based Detection; Anomaly-based Detection; V2G; Automotive Ethernet.; Technology and Engineering;

    Sammanfattning : A modern automotive vehicle is a complex technical system, containing many electronic, mechanical, and software parts. Typically, a high-end vehicle contains 70 or more electronic control units (ECUs) on average. LÄS MER

  2. 2. DDoS datasets : Use of machine learning to analyse intrusion detection performance

    Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Stefanos Kiourkoulis; [2020]
    Nyckelord :;

    Sammanfattning : Threats of malware, attacks and intrusion have been around since the very conception ofcomputing. Yet, it was not until the sudden growth of the internet that awareness of security anddigital assets really started to pick up steam. LÄS MER

  3. 3. Analyzing Radial Basis Function Neural Networks for predicting anomalies in Intrusion Detection Systems

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Sai Shyamsunder Kamat; [2019]
    Nyckelord :anomaly; cyber security; evaluation; machine learning; radial basis function; random forest classifier; supervised learning; anomali; cybersäkerhet; utvärdering; maskininlärning; radialbaserad funktion; slumpmässig skogsklassificering; övervakad inlärning;

    Sammanfattning : In the 21st century, information is the new currency. With the omnipresence of devices connected to the internet, humanity can instantly avail any information. However, there are certain are cybercrime groups which steal the information. LÄS MER

  4. 4. Machine Learning for a Network-based Intrusion Detection System : An application using Zeek and the CICIDS2017 dataset

    M1-uppsats, KTH/Hälsoinformatik och logistik

    Författare :Vilhelm Gustavsson; [2019]
    Nyckelord :Machine Learning; Flow-based traffic characterization; Intrusion Detection System IDS ; Zeek; Bro; CICIDS2017; Scikit-Learn; Maskininlärning; Flödesbaserad trafik-karaktärisering; Intrångsdetekteringssystem IDS ; Zeek; Bro; CICIDS2017; Scikit-Learn;

    Sammanfattning : Cyber security is an emerging field in the IT-sector. As more devices are connected to the internet, the attack surface for hackers is steadily increasing. Network-based Intrusion Detection Systems (NIDS) can be used to detect malicious traffic in networks and Machine Learning is an up and coming approach for improving the detection rate. LÄS MER

  5. 5. Secure Self-Reconfiguring Services to Mitigate DoS Attacks

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Silvan Zeller; [2019]
    Nyckelord :Rule-Based IDS; Runtime Verification; Domain Attacks; Self-Reconfiguring Systems;

    Sammanfattning : Protecting web services from cyber attacks is a complex problem requiring many layers of defense and mitigation strategies. Out of the diverse range of attacks, denial of service (DoS) attacks on the business logic – or the domain – are poorly studied and no widely accepted general-purpose software product to prevent these attacks exists today. LÄS MER