Illegitimate Flows Research Articles

Sensitive information leakage analysis of database code by abstract interpretation

An information system stores outside data in the backend database to process them efficiently and protects sensitive data from illegitimate flow or unauthorised users. However, most information systems are made in such a way that the sensitive information stored in a database may be leaked explicitly or implicitly during data processing along with the control structure of the program to the output channels. Therefore, sensitive data leakage is one of the crucial security threat. In this paper, the main objective is to detect the illegitimate flow of confidential information in an information system. We propose a framework to detect sensitive information leakage through the data-flow paths of an information system. In particular, to compute the precise set of data-flow paths, we use the non-relational abstract property of the interval domain and the relational abstract property of the polyhedra domain that enables the framework to produce efficient security analysis results.

Optimal deployment of virtual network functions for securing telecommunication networks against distributed denial of service attacks: A robust optimization approach

Distributed Denial of Service (DDoS) cyberattacks represent a major security risk for network operators and internet service providers. They thus need to invest in security solutions to protect their network against DDoS attacks. The present work focuses on deploying a network function virtualization based architecture to secure a network against an on-going DDoS attack. We assume that the target, sources and volume of the attack have been identified. However, due to 5G network slicing, the exact routing of the illegitimate flow in the network is not known by the internet service provider. We seek to determine the optimal number and locations of virtual network functions in order to remove all the illegitimate traffic while minimizing the total cost of the activated virtual network functions. We propose a robust optimization framework to solve this problem. The uncertain input parameters correspond to the amount of illegitimate flow on each path connecting an attack source to the target and can take values within a predefined uncertainty set. In order to solve this robust optimization problem, we develop an adversarial approach in which the adversarial sub-problem is solved by a Branch & Price algorithm. The results of our computational experiments, carried out on medium-size randomly generated instances, show that the proposed solution approach is able to provide optimal solutions within short computation times.

Cochain-SC: An Intra- and Inter-Domain Ddos Mitigation Scheme Based on Blockchain Using SDN and Smart Contract

With the exponential growth in the number of insecure devices, the impact of Distributed Denial-of-Service (DDoS) attacks is growing rapidly. Existing DDoS mitigation schemes are facing obstacles due to low flexibility, lack of resources, and high cost. The new emerging technologies, such as blockchain, introduce new opportunities for low-cost, efficient and flexible DDoS attacks mitigation across multiple domains. In this paper, we propose a blockchain-based approach, called Cochain-SC, which combines two levels of mitigation, intra-domain and inter-domain DDoS mitigation. For intra-domain, we propose an effective DDoS mitigation method in the context of software defined networks (SDN); it consists of three schemes: (1) Intra Entropy-based scheme (I-ES) to measure, using sFlow, the randomness of data inside the domain; (2) Intra Bayes-based scheme (I-BS) to classify, based on entropy values, illegitimate flows; and (3) Intra-domain Mitigation (I-DM) scheme to effectively mitigate illegitimate flows inside the domain. For inter-domain, we propose a collaborative DDoS mitigation scheme based on blockchain; it uses the concept of smart contracts (i.e., Ethereum’s smart contracts) to facilitate the collaboration among SDN-based domains (i.e., Autonomous System: AS) to mitigate DDoS attacks. For this aim, we design a novel and secure scheme that allows multiple SDN-based domains to securely collaborate and transfer attack information in a decentralized manner. Combining intra- and inter-domain DDoS mitigation, Cochain-SC allows an efficient mitigation along the path of an ongoing attack and an effective mitigation near the origin of the attack. This allows reducing the enormous cost of forwarding packets, across multiple domains, which consist mostly of useless amplified attack traffic. To the best of our knowledge, Cochain-SC is the first scheme that proposes to deal with both intra-domain and inter-domain DDoS attacks mitigation combining SDN, blockchain and smart contract. The implementation of Cochain-SC is deployed on Ethereum official test network Ropsten. Moreover, we conducted extensive experiments to evaluate our proposed approach; the experimental results show that Cochain-SC achieves flexibility, efficiency, security, cost effectiveness, and high accuracy in detecting illegitimate flows, making it a promising approach to mitigate DDoS attacks.