بنيت خوارزميات التعمية الحديثة بالاعتماد على الفرضية الآتية: «تعتمد الطرائق التقليدية في تحليـل
المعميات (التحليل الخطي، التحليل التفاضلي،.....) على خصائص احتمالية تجعل أمـن المعمـي يـزداد
بشكل أسي مع عدد دورات المعمي». لذلك فهذه المعميات ليس لها المناعة المطلوبـة ضـد الهجمـات
الجيرية التي أصبحت أقوى بعد تطوير خوارزمية XSL .في هذا البحث سوف نقدم بعض الطرائق لرفع
مناعة المعمي AES ضد الهجمات الجبرية ثم سندرس تأثير هذا التعديل في مناعة المعمي.
The security of several recently proposed ciphers relies on the fact:" that
the classical methods of cryptanalysis (e.g. linear or differential attacks) are
based on probabilistic characteristics, which makes their security grow
exponentially with the number of rounds".
So they haven’t the suitable immunity against the algebraic attacks which
becomes more powerful after XSL algorithm. in this research we will try some
method to increase the immunity of AES algorithm against the algebraic
attacks then we will study the effect of this adjustment.
References used
Daemen, J., and Rijmen, V. (2001). "The Design of rijndael AES – The advanced encryption standard", Springer
"Announcing the advanced encryption standard (AES)",Federal Information Processing Standards Publication 197, 2001 URL:http://www.csrc.nist.gov/publications/fips/fips197/fips-197.pdf
Rukhin, A., Soto, J., Nechvatal, J., Smid, M., Barker, E., Leigh, S., Levenson, M., Vangel, M., Banks, D., Heckert, A., and Dray, J. (2001)."A statiistiical test suiite for random and pseudorandom number generators for cryptographiic appliicatiions", URL:http://www.csrc.nist.gov/publications/nistpubs/800-22/sp-800-22-051501.pdf
Deep neural networks are vulnerable to adversarial attacks, where a small perturbation to an input alters the model prediction. In many cases, malicious inputs intentionally crafted for one model can fool another model. In this paper, we present the
Deep learning is at the heart of the current rise of artificial intelligence. In the field of Computer Vision, it has become the workhorse for applications ranging from self-driving cars to surveillance and security. Whereas deep neural networks have
We propose the first general-purpose gradient-based adversarial attack against transformer models. Instead of searching for a single adversarial example, we search for a distribution of adversarial examples parameterized by a continuous-valued matrix
We testified in the last years immense jumps and many developments in all of the life domains, specially in a field of the informatics and telecommunications.
Therefor the digital information and the telecommunications and its kinds, became the ner
Wireless sensor network have become widely used in many civil and military issues.
Like all other network, it is exposed to attacks but its simplicity structured (CPU &
memory) prevent the traditional defense technic to be applied, so they need a s