Ph.D. Theses
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Browsing Ph.D. Theses by Author "Anarım, Emin."
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Item DDoS attack detection using signal processing and statistical approaches(Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2021., 2021.) Erhan, Derya.; Anarım, Emin.DDoS attacks cause a variety of changes in the properties of the attributes in the network traffic. Modeling these changes using signal processing and statistical ap proaches provides detection of these attacks. This thesis focuses on detecting DDoS attacks using time series analysis, sparse signal representation methods, and statistical modeling. We also investigate the effect of DDoS attacks on traffic features in a sta tistical manner. In addition, we propose two simple but effective network-based DDoS attack detection methods based on the statistical signal processing approach, using the advantage of statistical changes in traffic features. We propose a novel DDoS detection framework using the Matching Pursuit algo rithm to detect resource depletion type DDoS attacks. We use multiple characteristics of network traffic simultaneously to detect low-density DDoS attacks efficiently. The proposed method uses the dictionary produced from the parameters of the network traf fic using the K-SVD algorithm. Dictionary generation using network traffic provides legitimate and attack traffic models and adds adaptability to the proposed method to network traffic. We also implement DDoS detection approaches that use Matching Pursuit and Wavelet techniques and compare them using two different data sets. Addi tionally, we offer a hybrid DDoS detection framework that combines these approaches with a decision-making mechanism using an artificial neural network. We evaluate the proposed methods with two different data sets. In the hybrid intrusion detection sys tem with more than one attack, the detection performances of other approaches have decreased. In contrast, the proposed method achieves true-positive rates higher than 99% with a false positive rate lower than 0.7%.Item Model based multiple audio sequence alignment(Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2015., 2015.) Başaran, Doğaç.; Anarım, Emin.; Cemgil, Ali Taylan.It is increasingly more common that an occasion is recorded by multiple individuals with the proliferation of recording devices such as smart phones. When properly aligned, these recordings may provide several audio and visual perspectives to a scene which leads to several applications in restoring, remastering and remixing frameworks in various fields. In this study, we interpret the problem of aligning multiple unsynchronized audio sequences in a probabilistic framework. In this manner, we propose a novel, model based approach where we define a template generative model. We define 6 different generative models using this template covering basically all kinds of features (real valued, positive, binary and categorical). Proper scoring functions that evaluates the quality of an alignment are derived from each model where we are able to penalize non-overlapping alignments and alignment of a single sequence against a pre-aligned sequences. Having defined a cost or score function, a heuristic sequential search algorithm and a Gibbs sampler approach are proposed to find the optimum alignment of sequences on the surfaces defined by derived score functions. In addition we propose a multi resolution alignment algorithm where we combine Sequential Monte Carlo (SMC) samplers and proposed sequential search method. The models and appropriate features are exhaustively evaluated with artificial and real-life data sets. The simulation results suggest that the approach is able to handle difficult, ambiguous scenarios and partial matchings where simple baseline methods such as correlation fail.Item Novel time-series based DDOS attack detection schemes for traditional networks and software defined networks(Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2021., 2021.) Fouladi, Ramin Fadaei.; Anarım, Emin.Distributed Denial of Service (DDoS) attacks are always one of the most signifi cant threats for computer networks since they affect the user satisfaction by degrading the availability of on-line services. Although some countermeasures such as Intrusion Detection Systems (IDSs) provide effective mechanisms to discriminate various types of DDoS attacks, they become impotent of detection when bogus packets similar to normal ones are dispatched by the attacker. One promising approach for the DDoS detection in traditional networks is to use the time-series representation of the network traffic while analyzing the incoming packets. Particularly, discriminating features are extracted from the representation of the traffic flow in order to be used with several data analytic techniques such as statistical measures or machine learning algorithms. In this thesis, we first improve the previous works in the literature for the traditional networks by introducing three methods using frequency domain analysis and statistical measures. Later, we extend our findings for SDNs and we propose three different DDoS detection and countermeasure schemes for SDN by employing: (i) Auto-Regressive Integrated Moving Average and a dynamic thresholding method, (ii) Discrete Wavelet Transform and Auto-Encoder Networks, and (iii) Continuous Wavelet Transform and Convolu tional Neural Network. Experimental results show that proposed schemes have high detection and low false alarm rates. Finally, we compare proposed schemes in terms of their attack detection performance and computational complexity cost analysis.Item Security and privacy analysis of authentication protocols in RFID systems(Thesis (Ph.D.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2011., 2011.) Ergüler, İmran.; Anarım, Emin.Radio Frequency IDentification (RFID) technology continues to flourish as an inherent part of virtually every ubiquitous environment. However, it became clear that the public— implying the industry— seriously needs mechanisms emerging the security and privacy issues for increasing RFID applications. This thesis examines security and privacy of RFID authentication protocols and presents three main contributions. First, we show that RFID protocols having unbalanced states for which tag identification is performed in different order of computational complexities are subject to side-channel attacks and do not preserve the RFID privacy. Second, we introduce a timing attack such that if the database querying in tag identification is performed through a static process, RFID protocol is vulnerable to the proposed attack that could easily jeopardize the system’s untraceability criteria. We formulate success probability of our attack and demonstrate its success on some well known protocols. Finally, we analyze security of RFID delegation systems and present an unnoticed security flaw that makes tag impersonation attack possible. To overcome these weakness, we give some possible countermeasures.Item Sparse signal recovery from incomplete and perturbed data(Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2016., 2016.) Şenyuva, Rıfat Volkan.; Anarım, Emin.Sparse signal recovery consists of algorithms that are able to recover undersampled high dimensional signals accurately. These algorithms require fewer measurements than traditional Shannon/Nyquist sampling theorem demands. Sparse signal recovery has found many applications including magnetic resonance imaging, electromagnetic inverse scattering, radar/sonar imaging, seismic data collection, sensor array processing and channel estimation. The focus of this thesis is on electromagentic inverse scattering problem and joint estimation of the frequency o set and the channel impulse response in OFDM. In the electromagnetic inverse scattering problem, the aim is to nd the electromagnetic properties of unknown targets from measured scattered eld. The reconstruction of closely placed point-like objects is investigated. The application of the greedy pursuit based sparse recovery methods, OMP and FTB-OMP, is proposed for increasing the reconstruction resolution. The performances of the proposed methods are compared against NESTA and MT-BCS methods. Simulations show that the FTBOMP method increases the resolution of the regular OMP and is superior to NESTA for less noisy measurements. OFDM is a multicarrier modulation technique that is very sensitive to frequency synchronization and channel estimation errors. Frequency o set destroys the orthogonality of the OFDM carriers and results in intercarrier inteference that causes severe performance degradation. A new approach that represents the channel impulse response as a 1-block sparse signal in a dictionary built by concatenating subspaces of frequency o set values is proposed. Thus the frequency o set and the channel impulse response can be jointly estimated. Only one OFDM training block is used and noise or channel statistics are not required. Its performance is close to maximum likelihood estimation and does not depend on frequency o set. v OZET EKS_IK VE BOZUK VER_ILER _ILE SEYREK S_INYAL GER_IC ATIMI Seyrek sinyal geri cat m , yuksek boyutlu sinyalleri az say da ornek uzerinden tekrar olu sturabilen yontemlerden meydana gelir. Bu yontemler ile sinyal geri cat m i cin gereksinim duyulan ornek say s , geleneksel Shannon/Nyquist ornekleme teoremine k yasla cok daha az say dad r. Seyrek sinyal geri cat m manyetik rezonans goruntuleme, elektromanyetik ters sa c l m problemi, radar/sonar goruntuleme, sismik veri toplama, sensor dizi i sleme ve kanal kestirimi olmak uzere bir cok uygulamada kullan lmaktad r. Bu tez cal smas n n oda g elektromanyetik ters sa c l m problemi ve OFDM i cin frekans kaymas n n ve kanal yan t n n birlikte kestirilmesidir. Ters sa c l m probleminde sa c lan elektromanyetik alandan hedef cisimlerin ozelliklerinin belirlenmesi ama clanmaktad r. Bu kapsamda birbirine yak n konumland r lm s nokta cisimlerin yerlerinin bulunmas incelenmi stir. Bu problemdeki geri cat m cozunurlu gunun iyile stirilmesi i cin a cgozlu geri cat m yontemlerinden dikgen uyum kovalama OMP ve esnek a ga c arama yap l FTB-OMP yontemleri onerilmi stir. Onerilen yontemlerin ba sar mlar NESTA ve MTBCS yontemleri ile kar s la st r lm st r. Yap lan benzetimler FTB-OMP yonteminin OMP geri