عنوان
پدید آورنده
موضوع
رده
کتابخانه
محل استقرار
شماره کتابشناسی ملی
شماره
TLpq2423767658
زبان اثر
زبان متن نوشتاري يا گفتاري و مانند آن
انگلیسی
عنوان و نام پديدآور
عنوان اصلي
Intrusion Detection in IoT Systems Using Machine Learning Algorithms
نام عام مواد
[Thesis]
نام نخستين پديدآور
Basalan, Abdurrahman
نام ساير پديدآوران
Salam, Mohammad Abdus
وضعیت نشر و پخش و غیره
نام ناشر، پخش کننده و غيره
Southern University and Agricultural and Mechanical College
تاریخ نشرو بخش و غیره
2020
مشخصات ظاهری
نام خاص و کميت اثر
66
یادداشتهای مربوط به پایان نامه ها
جزئيات پايان نامه و نوع درجه آن
M.S.
کسي که مدرک را اعطا کرده
Southern University and Agricultural and Mechanical College
امتياز متن
2020
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
In recent years, Internet of Things (IoT) has grown up rapidly and tremendously. This growth has brought big and special problems. Two of the urgent topics of problems are security and privacy for IoT devices. Those devices are creating and gathering all data in their connections. For the security of IoT, detection of anomaly attacks is the first and crucial point for avoiding any interruption in the connection. Machine Learning algorithms have been rising and improving substantially year by year. Many classic tests can detect large amount of attacks in current time. However, those techniques are not enough for security since the types of attacks are changing and getting stronger frequently. In this study, we propose that how we can improve security level of IoT. Also, deep learning techniques, especially Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) have been applied in order to have better accuracy performance. Dataset is presumably one of the most important starting point for the use of those techniques. UNSW-NB15 dataset which is publicly available has been used for this study. Two different models are created in this study. One detects attack or no attack and another detects what type of attack or no attack. The combinations of LSTM and CNN algorithms have 98.2% accuracy which is best performance within the selected algorithms.
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Artificial intelligence
موضوع مستند نشده
Computer science
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )
مستند نام اشخاص تاييد نشده
Basalan, Abdurrahman
مستند نام اشخاص تاييد نشده
Salam, Mohammad Abdus
دسترسی و محل الکترونیکی
نام الکترونيکي
مطالعه متن کتاب وضعیت انتشار
فرمت انتشار
p
اطلاعات رکورد کتابشناسی
نوع ماده
[Thesis]
کد کاربرگه
276903
اطلاعات دسترسی رکورد
سطح دسترسي
a
تكميل شده
Y
