A New Intelligent Steganalysis Method for Waveform Audio Files

Yavanoğlu, Uraz; OzCakmak, Burak; Milletsever, Ozlem

doi:10.1109/icmla.2012.150

Cited by 6 publications

(3 citation statements)

References 37 publications

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“…So, it has the ability of associating input data that is depend on single or multiple parameters to the output data. ANNs identify the patterns and correlations of the input data and in this way, learn through their architectures, transfer functions and learning algorithms by gathering knowledge [14,15].…”

Section: Previous Studiesmentioning

confidence: 99%

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Predicting Next Location of Twitter Users for Surveillance

Gunduz

Yavanoğlu

Sağıroğlu

2013

2013 12th International Conference on Machine Learning and Applications

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In this study a novel approach that uses location based social networks for next location prediction in the field of technical surveillance and digital forensics is proposed. With the help of proposed methodology, search area for the potential criminals will be narrowed so that the spent time, money and effort by the law enforcement officers will be minimized. After collecting enough past location information for Foursquare users, the whole data is trained by means of Artificial Neural Networks. After training process, predicting the next location of the wantedperson is carried out. Prediction process is made region-based, so it is tried to predict the region of the potential criminals' next geographical location. The experimental results have shown that the proposed approach and developed system might achieve the prediction goal with only 3% error rate, and proposed methodology can be used by law enforcement officers for forensic surveillance and similar criminal acts.

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Section: Previous Studiesmentioning

confidence: 99%

“…Therefore, many different types of ANN are developed. Multilayered Perceptron (MLP) is the mostly used ANN architecture, among them [15].…”

Section: Previous Studiesmentioning

confidence: 99%

Predicting Next Location of Twitter Users for Surveillance

Gunduz

Yavanoğlu

Sağıroğlu

2013

2013 12th International Conference on Machine Learning and Applications

Self Cite

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“…Mevcut bazı steganografi yazılımlarıyla WAV dosyaları içerisine yapılan gömme işlemini tespit etmeye yönelik bir yöntem geliştirilmiştir [22]. Yapay sinir ağlarıyla Dalga Şekli Ses Dosya Biçimi (WAV-Waveform Audio File Format) dosyalarındaki anormallikleri analiz ederek %75 başarı oranıyla steganografik içerik olup olmadığını tespit eden bir sistem sunulmuştur [24].…”

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Steganografi Tabanlı Yeni Bir Klasör Kilitleme Yaklaşımı ve Yazılımı Geliştirilmesi

Atici¹,

Sağıroğlu²

2016

Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

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ÖZETBu makalede, steganografi tabanlı yeni bir kişisel güvenlik yaklaşımı sunulmuş ve pratik olarak kullanımı için ise bir klasör kilitleme yazılımı (STKK) geliştirilmiştir. Sunulan yaklaşım kullanıcılara, bilgisayardaki tüm dosyaların güvenliği için esnek ve güvenilir çözümler sunmaktadır. Steganografik çözümlerin yanı sıra AES, DES ve 3DES gibi bilinen kriptografik yaklaşımların da geliştirilen yazılıma eklenmesi ile güvenlik arttırılmıştır. Deneysel sonuçlar, geliştirilen çözümün steganalize karşı dayanıklı olduğunu ve tüm dosya tiplerini desteklediği için kişisel güvenliğin artırılmasına katkı sağlayacağını göstermektedir.Anahtar Kelimeler: Steganografi, steganaliz, güvenlik, klasör kilitleme yazılımı, kriptografi, DES, 3DES, AES DEVELOPMENT OF A NEW FOLDER LOCK APPRAOCH AND SOFTWARE BASED ON STEGANOGRAPHY ABSTRACTThis paper introduces a new personal security approach based on steganography. In order to achieve the task, a folder-lock software (STKK) was developed. The proposed approach provides more flexible solutions to the users to secure all files in the computer. In addition to steganographic solutions, cryptographic approaches such as AES, DES and 3DES are also added to the developed software. The experimental results have shown that the developed solution is robust against steganalysis and might provide better personel security by supporting all file types.

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