Sökning: "intrusion detection systems"

Visar resultat 1 - 5 av 44 uppsatser innehållade orden intrusion detection systems.

  1. 1. Industrial Internet of Things : En analys av hot och sårbarheter i industriella verksamheter

    Kandidat-uppsats, Högskolan i Halmstad/Akademin för informationsteknologi; Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Daniel Johnsson; Lina Krohn; [2019]
    Nyckelord :Internet of Things; Industrial Internet of Things; SCADA; Industrial Control Systems;

    Sammanfattning : Today the digital evolution is progressing rapidly. This entails both pros and cons concerning the security of devices. Despite the evolution, security has been left in the dark. This results in threats and vulnerabilities in devices, which could potentially be used by a hacker with the purpose of exploiting information. LÄS MER

  2. 2. 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

  3. 3. 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

  4. 4. Information-Theoretic Framework for Network Anomaly Detection: Enabling online application of statistical learning models to high-speed traffic

    Master-uppsats, KTH/Matematisk statistik

    Författare :Gabriel Damour; [2019]
    Nyckelord :Network Security; Distributed Denial of Service; DDoS; DoS; Anomaly Detection; Intrusion Detection; Attack Source Identification; Information Theory; Statistical Learnin; Nätverkssäkerhet; Distribuerad Överbelastningsattack; DDoS; DoS; Anomalidetektering; Intrångsdetektering; Identifiering av Attackkällor; Informationsteori; Maskininlärning;

    Sammanfattning : With the current proliferation of cyber attacks, safeguarding internet facing assets from network intrusions, is becoming a vital task in our increasingly digitalised economies. Although recent successes of machine learning (ML) models bode the dawn of a new generation of intrusion detection systems (IDS); current solutions struggle to implement these in an efficient manner, leaving many IDSs to rely on rule-based techniques. LÄS MER

  5. 5. Comparison of systems to detect rogue access points

    Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM); Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Författare :Alexander Lennartsson; Hilda Melander; [2019]
    Nyckelord :Network Intrusion Detection; Rogue Access Points; WirelessScanner; Wireless Lan Controller; Software Comparisons;

    Sammanfattning : A hacker might use a rogue access point to gain access to a network, this poses athreat to the individuals connected to it. The hacker might have the potential to leakcorporate data or steal private information. The detection of rogue access points istherefore of importance to prevent any damage to both businesses and individuals. LÄS MER