Mohsin Hashim

Mathematical Analysis of the Dynamics of Visceral Leishmaniasis in the Sudan

In this paper we develop a mathematical model to study the dynamics of visceral leishmaniasis in the Sudan. To develop this model we consider the dynamics of the disease between three different populations, human, reservoir and vector populations. The model is analyzed at equilibrium and the stability of the equilibria is analyzed. The basic reproduction number is derived, and the threshold conditions for disease elimination established. Results show that the disease can be eliminated under certain conditions. Simulations of the model show that human treatment helps in disease control, and its synergy with vector control will more likely result in the elimination of the disease.

Improved fixed-base comb method for fast scalar multiplication

Computing elliptic-curve scalar multiplication is the most time consuming operation in any elliptic-curve cryptosystem. In the last decades, it has been shown that pre-computations of elliptic-curve points improve the performance of scalar multiplication especially in cases where the elliptic-curve point P is fixed. In this paper, we present an improved fixed-base comb method for scalar multiplication. In contrast to existing comb methods such as proposed by Lim and Lee or Tsaur and Chou, we make use of a width-ω non-adjacent form representation and restrict the number of rows of the comb to be greater or equal ω. The proposed method shows a significant reduction in the number of required elliptic-curve point addition operation. The computational complexity is reduced by 33 to 38,% compared to Tsaur and Chou method even for devices that have limited resources. Furthermore, we propose a constant-time variation of the method to thwart simple-power analysis attacks.

Accurate signature generation for polymorphic worms using principal component analysis

Internet worms pose a major threat to Internet infrastructure security, and their destruction causes loss of millions of dollars. Therefore, the networks must be pro-tected as much as possible to avoid losses. In this paper we propose accurate system for signature generation for Zero-day polymorphic worms. We have designed a novel double-honeynet system, which is able to detect new worms that have not been seen before. We apply Princi-pal Component Analysis (PCA) to determine the most significant substrings that are shared between po-lymorphic worm instances. The experimental results show that the PCA has successfully detected polymorphic worms with zero false positives and zero false negatives.

Polymorphic Worm Detection Using Double-Honeynet

Internet worms are increasing every year, and they increasingly threaten the availability and integrity of Internet-based services. Polymorphic worms evade signature-based Intrusion Detection Systems (IDSs) by varying their payload on every infection attempt. In this paper, we propose a system for automated signature generation for Zero-day polymorphic worms. We have designed a novel double-honeynet system, which is able to detect new worms that have not been seen before. The system is based on an efficient algorithm that uses worms binary representation for pattern matching. The system is able to generate accurate signatures for single and multiple worms.