Sökning: "obfuscation"

Visar resultat 1 - 5 av 27 uppsatser innehållade ordet obfuscation.

  1. 1. ETF Cost Obfuscation

    D-uppsats, Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

    Författare :Ole Holte; Hans-Kristian Leite; [2022]
    Nyckelord :Exchange Traded Funds; Expense Ratios; Tracking Errors; Index Investing; Asset Management;

    Sammanfattning : Index-tracking ETFs have gained popularity by both retail and institutional investors over the past years while costs in the form of fees have declined due to competitive pressures. Index-tracking funds are relatively homogenous products with only the goal of replicating an index as close as possible. LÄS MER

  2. 2. Increased evasion resilience in modern PDF malware detectors : Using a more evasive training dataset

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

    Författare :Oscar Ekholm; [2022]
    Nyckelord :Malware Analysis; Malicious PDF; Malware Detection; Machine Learning; Evasion; Analys av skadlig programvara; Skadlig PDF; Detektion av skadlig programvara; Maskininlärning; Undanflykt;

    Sammanfattning : The large scale usage of the PDF coupled with its versatility has made the format an attractive target for carrying and deploying malware. Traditional antivirus software struggles against new malware and PDF's vast obfuscation options. In the search of better detection systems, machine learning based detectors have been developed. LÄS MER

  3. 3. What's the Deal with Stegomalware? : The Techniques, Challenges, Defence and Landscape

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

    Författare :Kristoffer Björklund; [2021]
    Nyckelord :Stegomalware; steganography; information hiding; covert channel;

    Sammanfattning : Stegomalware is the art of hiding malicious software with steganography. Steganography is the technique of hiding data in a seemingly innocuous carrier. The occurrence of stegomalware is increasing, with attackers using ingenious techniques to avoid detection. LÄS MER

  4. 4. Random projections in a distributed environment for privacy-preserved deep learning

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

    Författare :Malcolm Bagger Toräng; [2021]
    Nyckelord :Random projections; Generative adversarial networks; Privacy metrics; Deep learning; Obfuscation.; Slumpmässiga projektioner; Generativa kontroversiella nätverk; Privatiserings-mått; Djupinlärning; Obfuskering.;

    Sammanfattning : The field of Deep Learning (DL) only over the last decade has proven useful for increasingly more complex Machine Learning tasks and data, a notable milestone being generative models achieving facial synthesis indistinguishable from real faces. With the increased complexity in DL architecture and training data, follows a steep increase in time and hardware resources required for the training task. LÄS MER

  5. 5. Is it possible to reverse engineer obfuscated bytecode back to source code?

    Kandidat-uppsats, KTH/Hälsoinformatik och logistik

    Författare :Gustav Smedberg; Jenny Malmgren; [2020]
    Nyckelord :;

    Sammanfattning : AbstractThere are a lot of old software in the world that has not been supported or kept up todate and would need to be updated to seal security vulnerabilities, as well as to updatefunctions in the program. In those cases where the source code has been lost ordeliberately deleted, would it be possible to use reverse engineering to retrieve thesource code?This study aims to show what java bytecode is and how it is used, as well as how oneis able to go from java bytecode back to source code in a process called Reverse Engineering. LÄS MER