Biblio
Software Defined Network (SDN) is a revolutionary networking paradigm which provides the flexibility of programming the network interface as per the need and demand of the user. Software Defined Network (SDN) is independent of vendor specific hardware or protocols and offers the easy extensions in the networking. A customized network as per on user demand facilitates communication control via a single entity i.e. SDN controller. Due to this SDN Controller has become more vulnerable to SDN security attacks and more specifically a single point of failure. It is worth noticing that vulnerabilities were identified because of customized applications which are semi-independent of underlying network infrastructure. No doubt, SDN has provided numerous benefits like breaking vendor lock-ins, reducing overhead cost, easy innovations, increasing programmability among devices, introducing new features and so on. But security of SDN cannot be neglected and it has become a major topic of debate. The communication channel used in SDN is OpenFlow which has made TLS implementation an optional approach in SDN. TLS adoption is important and still vulnerable. This paper focuses on making SDN OpenFlow communication more secure by following extended TLS support and defensive algorithm.
A covert channel is a communication channel that is subjugated for illegal flow of information in a way that violates system security policies. It is a dangerous, invisible, undetectable, and developed security attack. Recently, Packet length covert channel has motivated many researchers as it is a one of the most undetectable network covert channels. Packet length covert channel generates a covert traffic that is very similar to normal terrific which complicates the detection of such type of covert channels. This motivates us to introduce a machine learning based detection scheme. Recently, a machine learning approach has proved its capability in many different fields especially in security field as it usually brings up a reliable and realistic results. Based in our developed content and frequency-based features, the developed detection scheme has been fully trained and tested. Our detection scheme has gained an excellent degree of detection accuracy which reaches 98% (zero false negative rate and 0.02 false positive rate).
A lot of research in security of cyber physical systems focus on threat models where an attacker can spoof sensor readings by compromising the communication channel. A little focus is given to attacks on physical components. In this paper a method to detect potential attacks on physical components in a Cyber Physical System (CPS) is proposed. Physical attacks are detected through a comparison of noise pattern from sensor measurements to a reference noise pattern. If an adversary has physically modified or replaced a sensor, the proposed method issues an alert indicating that a sensor is probably compromised or is defective. A reference noise pattern is established from the sensor data using a deterministic model. This pattern is referred to as a fingerprint of the corresponding sensor. The fingerprint so derived is used as a reference to identify measured data during the operation of a CPS. Extensive experimentation with ultrasonic level sensors in a realistic water treatment testbed point to the effectiveness of the proposed fingerprinting method in detecting physical attacks.
To add multiple layers of security our present work proposes a method for integrating together cryptography and Steganography for secure communication using an image file. We have used here combination of cryptography and steganography that can hide a text in an image in such a way so as to prevent any possible suspicion of having a hidden text, after RSA cipher. It offers privacy and high security through the communication channel.
Demand response management (DRM) is one of the main features in smart grid, which is realized via communications between power providers and consumers. Due to the vulnerabilities of communication channels, communication is not perfect in practice and will be threatened by jamming attack. In this paper, we consider jamming attack in the wireless communication for smart grid. Firstly, the DRM performance degradation introduced by unreliable communication is fully studied. Secondly, a regret matching based anti-jamming algorithm is proposed to enhance the performance of communication and DRM. Finally, numerical results are presented to illustrate the impacts of unreliable communication on DRM and the performance of the proposed anti-jamming algorithm.