Qualification: 
Ph.D, MS, B-Tech
srirams@am.amrita.edu

Dr. Sriram Sankaran currently serves as an Assistant Professor at the Center for Cybersecurity Systems and Networks at Amrita Vishwa Vidyapeetham, India. He obtained M. S and Ph. D degrees in Computer Science and Engineering at the University at Buffalo, The State University of New York, USA. Previously, he received B. Tech (Hons) in Computer Science and Engineering from Malaviya National Institute of Technology, Jaipur formerly known as Regional Engineering College

 

 

Publications

Publication Type: Conference Proceedings

Year of Publication Title

2018

N. K, Sankaran, S., and Achuthan, K., “A Novel Multi-factor Authentication Protocol for Smart Home Environments”, International Conference on Information Systems Security (ICISS), vol. 11281. Springer, Cham, 2018.[Abstract]


User authentication plays an important role in smart home environments in which devices are interconnected through the Internet and security risks are high. Most of the existing research works for remote user authentication in smart homes fail in one way or the other in combating common attacks specifically smartphone capture attack. Robust authentication method which can uniquely identify the smartphones of users can thwart unauthorized access through the physical capture of smartphones. Existing studies demonstrate that Photo Response Non-Uniformity (PRNU) of a smartphone can be used to uniquely identify the device with an error rate less than 0.5%. Based on these results, we propose a multi-factor user authentication protocol based on Elliptic Curve Cryptography (ECC) and secret sharing for smart home environments. We leverage face biometric and PRNU to make it resilient to common attacks. Moreover, the proposed protocol achieves mutual authentication among all participating entities and thereby ensures the legitimacy of all the participating entities. Subsequently, a session key is established for secure communication between the users and the devices. Our analysis of the proposed protocol shows that it provides significantly better security than the existing schemes with a reasonable overhead. In addition, it provides better usability by alleviating the burden of users from memorizing passwords and carrying additional mechanisms such as smart cards.

More »»

2018

S. Sanju, Sankaran, S., and Achuthan, K., “Energy Comparison of Blockchain Platforms for Internet of Things”, IEEE International Symposium on Smart Electronic Systems (iSES). 2018.

2018

S. Sankaran, Sivamohan, S., and K, N., “LHPUF: Lightweight Hybrid PUF for Enhanced Security in Internet of Things”, IEEE International Symposium on Smart Electronic Systems (iSES). 2018.

2018

S. Sankaran and Gupta, M., “Game Theoretic Modeling of Power-Performance trade-offs for Mobile Devices”, Proceedings of International Symposium on Embedded Computing and System Design (ISED). 2018.

2018

S. Roy, Sankaran, S., Singh, P., Sridhar, R., and , “CONTEXT-SEC: Balancing Energy Consumption and Security of Mobile Devices (Accepted) ”, 2018 Ninth International Green and Sustainable Computing (IGSC) Workshops. 2018.

2018

S. Sankaran and Gupta, M., “Towards a Hybrid Model for CPU Usage Prediction of Smartphone Users(Accepted)”, International Conference on Advanced Computing and Communications (ADCOM) 2018 . 2018.

2018

S. Roy, Sankaran, S., Singh, P., and Sridhar, R., “Modeling Context-Adaptive Energy-Aware Security in Mobile Devices (Accepted)”, 43rd Conference on Local Computer Networks Workshops (LCN Workshops). 2018.

2018

S. Sankaran, Sanju, S., and Dr. Krishnashree Achuthan, “Towards Realistic Energy Profiling of Blockchains for securing Internet of Things”, IEEE International Conference on Distributed Computing Systems (ICDCS) 2018. pp. 1454-1459, 2018.[Abstract]


Internet of Things (IoTs) offers a plethora of opportunities for remote monitoring and communication of everyday objects known as things with applications in numerous domains. The advent of blockchains can be a significant enabler for IoTs towards conducting and verifying transactions in a secure manner. However, applying blockchains to IoTs is challenging due to the resource constrained nature of the embedded devices coupled with significant delay incurred in processing and verifying transactions in the blockchain. Thus there exists a need for profiling the energy consumption of blockchains for securing IoTs and analyzing energy-performance trade-offs. Towards this goal, we profile the impact of workloads based on Smart Contracts and further quantify the power consumed by different operations performed by the devices on the Ethereum platform. In contrast to existing approaches that are focused on performance, we characterize performance and energy consumption for real workloads and analyse energy-performance trade-offs. Our proposed methodology is generic in that it can be applied to other platforms. The insights obtained from the study can be used to develop secure protocols for IoTs using blockchains.

More »»

2018

J. J and Sankaran, S., “Towards a Decision-Centric approach for securing Cyber Physical Systems”, 10th International Conference on Communication Systems and Networks (COMSNETS) 2018. p. 500‐502, 2018.[Abstract]


The emerging discipline of Cyber Physical Systems (CPS) integrate the interdisciplinary fields of computing, networking and control to offer solutions to real world problems. CPS solutions typically include security mechanisms that defend against attack attempts and initiate countermeasures to thwart the attacker objectives. To minimize the system performance overhead, the optimal decision would be to initialize the security mechanism in response to attack attempts in contrast to sustained operation. In this work, we use Markov Decision Processes (MDP) to decide the threshold upon which the system initiates the security mechanism. The system may be initialized at the threshold to minimize the overall operating costs. The proposed model can be further used to develop a decision-centric security architecture for CPS that balances the trade-off between system performance and security.

More »»

2017

S. Anil Kumar, J, J., and Sankaran, S., “Towards efficient resource provisioning in Vehicular Networks”, IEEE Biennial International Conference on Technological Advancements in Power & Energy (TAPEnergy) 2017. 2017.[Abstract]


The growing technological advancements in the fields of computation and communication technologies has enabled a communication network of vehicles, interacting among themselves to facilitate safe and efficient traffic in urban environments, termed as Vehicular Ad Hoc Network (VANET). VANETs depend on computational units called Road Side Units (RSUs), deployed along the highway to enable connectivity to moving vehicles in the network. Developing mechanisms for efficient resource provisioning of RSUs are of significant importance for energy efficiency in Vehicular networks. Towards this goal, we develop a model to dynamically resize computational resources of RSUs based on vehicle density. The proposed model utilizes queuing theory to determine the optimum number of computational units required to handle data exchanges depending on the vehicle density. Preliminary results in MATLAB/Simulink environment show feasibility and effectiveness of the proposed solution for achieving energy efficient operation in VANETs.

More »»

2017

S. Sankaran and Gupta, M., “Towards Modeling Vehicular Networks with Power-Performance trade-offs”, IEEE International Conference on Advanced Networks and Telecommunication Systems (ANTS) . 2017.[Abstract]


Vehicular networks are gaining increasing significance due to real-time communication and decision-making capabilities of vehicles and their interaction with road-side units. Power Management is critical for roadside units since they are typically powered on for servicing requests from vehicles. In this work, we envision low-power proxy servers to act on behalf of roadside units during periods of minimal activity to enable roadside units to be powered down resulting in power savings. However there exists a need for modeling of vehicular networks with roadside units and proxy servers for analyzing power-performance trade-offs. Towards this goal, we develop a queueing model to understand the impact of highway traffic on the power consumed by roadside units and proxy servers and further propose a threshold based approach for power savings. Our experiments conducted using real traces demonstrate that the proposed approach is traffic-aware in that it balances the trade-off between power consumption and delay.

More »»

2017

T. V. Ram and Sankaran, S., “Towards policy-driven power management for cloud computing”, 2017 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS). IEEE, Bhubaneswar, India, 2017.[Abstract]


Cloud computing enables users to rent computing resources on-demand towards meeting the needs of diverse applications. However, scaling of resources may incur significant impact on performance and power consumption which are the two key concerns for cloud service providers. The major goal of cloud providers is to develop policies for balancing the conflicting objectives of maximizing performance and minimizing energy consumption. Towards this goal, we analyze the impact of scale-up and scale-out techniques for varying cloud workloads through an OpenStack implementation. Our analysis reveals that these techniques vary with the nature of applications that run on the cloud as a result of which policies need to be developed on a per-application basis. We develop a threshold-based policy which determines the optimal trade-off depending on the application profile. Our proposed policy is generic and can be applied to other workloads thus facilitating efficient management of resources.

More »»

2017

A. Rajan, Jithish, J., and Sankaran, S., “Sybil attack in IOT: Modelling and defenses”, 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, Udupi, India, 2017.[Abstract]


Internet of Things (IoT) is an emerging paradigm in information technology (IT) that integrates advancements in sensing, computing and communication to offer enhanced services in everyday life. IoTs are vulnerable to sybil attacks wherein an adversary fabricates fictitious identities or steals the identities of legitimate nodes. In this paper, we model sybil attacks in IoT and evaluate its impact on performance. We also develop a defense mechanism based on behavioural profiling of nodes. We develop an enhanced AODV (EAODV) protocol by using the behaviour approach to obtain the optimal routes. In EAODV, the routes are selected based on the trust value and hop count. Sybil nodes are identified and discarded based on the feedback from neighbouring nodes. Evaluation of our protocol in ns-2 simulator demonstrates the effectiveness of our approach in identifying and detecting sybil nodes in IoT network.

More »»

2017

J. Jithish and Sankaran, S., “Securing networked control systems: Modeling attacks and defenses”, 2017 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia). IEEE, Bangalore, India, 2017.[Abstract]


Networked Control Systems (NCS) have emerged as a viable solution to effectively manage critical infrastructures in smart cities and modern industrial settings. The networked architecture of NCS that facilitates the communication between its distributed components makes them vulnerable to cyber attacks. The vulnerabilities in the communication network coupled with safety critical nature of data necessitates the need to develop models to analyze the impact of cyber attacks on system stability and performance. In this work, we develop an analytical model for Denial of Service (DoS) and Deception attacks in NCS. Based on the insights from the model, we propose a mechanism based on symmetric key encryption to secure NCS from such attacks. The comparison of our security mechanism with the standard reference signal demonstrates that our approach is successful in securing the NCS with minimal performance overhead.

More »»

2017

J. Jithish and Sankaran, S., “A Rule-Based System for Smart Home Energy Prediction”, Development Aspects of Intelligent Systems (DIAS) co-located with Innovations in Software Engineering 2017. 2017.

2017

J. J and Sankaran, S., “A Neuro-Fuzzy Approach for Domestic Water Usage Prediction”, Proceedings of IEEE Region 10 Symposium (TENSYMP). 2017.[Abstract]


The unconstrained rise in water usage as a result of population growth, rapid urbanization and climate change has become an issue of paramount concern for policy makers across the globe. Consequently, fresh water as a renewable but finite resource must be managed efficiently to sustain domestic and productive activities. Efficient water management strategies must be developed to address the challenges of increased demand without undermining long term sustainability. Developing such strategies necessitates a multidisciplinary approach incorporating policy planning and applied technology to efficiently manage water resources for maximizing economic growth and promoting social welfare. Towards this goal, we develop a hybrid intelligent system for domestic water usage prediction based on Adaptive Neuro-Fuzzy Inference System (ANFIS). The proposed system is trained in a supervised manner to model the relationship between environmental factors and domestic water consumption. The system forecasts domestic water usage based on environmental factors particularly atmospheric pressure, temperature, relative humidity and wind speed. Evaluation of the system on a real smart home dataset demonstrates that the system predicts domestic water consumption with higher accuracy.

More »»

2017

J. Jithish and Sankaran, S., “A Hybrid Adaptive Rule Based System For Smart Home Energy Prediction”, CEUR Workshop Proceedings, vol. 1819. CEUR-WS, 2017.[Abstract]


The increase in energy prices combined with the environmental impact of energy production has made energy efficiency a key component towards the development of smart homes. An efficient energy management strategy for smart homes results in minimized electricity consumption leading to cost savings. Towards this goal, we investigate the impact of environmental factors on home energy consumption. Home energy demand is observed to be affected by environmental factors such as temperature, wind speed and humidity which are inherently uncertain. Analyzing the impact of these factors on electricity consumption is challenging due to the unpredictability of weather conditions and non-linear relationship between environmental factors and electricity demand. For demand estimation based on these time varying factors, a hybrid intelligent system is developed that integrates the adaptability of neural networks and reasoning of fuzzy systems to predict daily electricity demand. A smart home dataset is utilized to build an unsupervised artificial neural network known as the Self-Organizing Map (SOM). We further develop a fuzzy rule based system from the SOM to predict home energy demand. Evaluation of the system shows a strong correlation between home energy demand and environmental factors and that the system predicts home energy consumption with higher accuracy. Copyright ©2017 for the individual papers by the papers' authors.

More »»

2017

A. Raj, Jithish, J., and Sankaran, S., “Modelling The Impact Of Code Obfuscation On Energy Usage”, CEUR Workshop Proceedings, vol. 1819. CEUR-WS, 2017.[Abstract]


Advancements in computing and communication technologies have given rise to low-cost embedded devices with applications in diverse domains such as Smarthome, industrial automation, healthcare, transportation etc. These devices are power-constrained which emphasizes the need for lightweight security solutions. Code obfuscation has been demonstrated to provide time-limited protection of source code from inference or tampering attacks. However, size of the obfuscated code increases with increase in code size which can have a negative impact on energy consumption. In particular, different transformations of the source code result in varying amounts of energy consumption for embedded devices. In this work, we model the impact of algorithms for code obfuscation on energy usage for embedded devices and analyze the energy-security-performance trade-offs. The insights from our analysis can be used to develop techniques depending on the needs of the applications thus facilitating efficient energy usage. Copyright ©2017 for the individual papers by the papers' authors.

More »»
PDF iconModeling-the-Impact-of-Code-Obfuscation-on-Energy-Usage.pdf

2016

S. Sankaran, “Modeling the Performance of IoT Networks”, IEEE International Conference on Advanced Networks and Telecommunication Systems (ANTS). IEEE, Bangalore, India, 2016.[Abstract]


Internet of Things (IoTs) is gaining increasing significance due to real-time communication and decision making capabilities of sensors integrated into everyday objects. Predicting performance in IoTs is critical for detecting performance bottlenecks, designing optimal sleep/wake-up schedules and application-aware performance tuning. However, performance prediction becomes a significant challenge in IoTs due to varying needs of applications coupled with the resource constrained nature of sensors. In this work, we analyze the impact of factors affecting performance in IoT networks using simulation based models. Further, an analytical framework is developed to model the impact of individual node behavior on overall performance using Markov chains. In particular, we derive steady state transition probabilities of transmit and receive states using protocol execution traces and further utilize them towards predicting per-flow throughput. Our proposed model is generic in that it can be applied across domains. Accuracy of the model is evaluated by comparing the predictions with the actual estimates obtained using simulations.

More »»
PDF iconModeling-the-Performance-of-IoT-Networks.pdf

2016

S. Sankaran, “Lightweight Security Framework For IoTs Using Identity Based Cryptography”, International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, Jaipur, India, 2016.[Abstract]


Internet of Things (IoTs) is gaining increasing significance due to real-time communication and decision making capabilities of sensors integrated into everyday objects. Securing IoTs is one of the foremost concerns due to the ubiquitous nature of the sensors coupled with the increasing sensitivity of user data. Further, power-constrained nature of the IoTs emphasizes the need for lightweight security that can tailor to the stringent resource requirements of the sensors. In this work, we propose a lighweight security framework for IoTs using Identity based Cryptography. In particular, we develop a hierarchical security architecture for IoTs and further develop protocols for secure communication in IoTs using identity based cryptography. Our proposed mechanism has been evaluated using simulations conducted using Contiki and RELIC. Evaluation shows that our proposed mechanism is lightweight incurring lesser overhead and thus can be applied in IoTs.

More »»
PDF iconLightweight-Security-Framework-For-IoTs-Using-Identity-Based-Cryptography.pdf

2016

S. Sankaran, “Predictive Modeling based Power Estimation for Embedded Multicore Systems”, ACM International Conference on Computing Frontiers (CF). ACM Digital Library, Como, Italy, pp. 370-375, 2016.[Abstract]


The increasing number of cores in embedded devices results in improved performance compared to single-core systems. Further, the unique characteristics of these systems provide numerous opportunities for power management which require models for power estimation. In this work, a statistical approach that models the impact of the individual cores and memory hierarchy on overall power consumed by Chip Multiprocessors is developed using Performance Counters. In particular, we construct a per-core based power model using SPLASH2 benchmarks by leveraging concurrency for multicore systems. Our model is simple and technology independent and as a result executes faster incurring lesser overhead. Evaluation of the model shows a strong correlation between core-level activity and power consumption and that the model predicts power consumption for newer observations with minimal errors. In addition, we discuss a few applications where the model can be utilized towards estimating power consumption.

More »»
PDF iconPredictive-Modeling-based-Power-Estimation-for-Embedded-Multicore-Systems.pdf

2015

S. Sankaran and Sridhar, R., “Modeling and Analysis of Routing for IoT Networks”, International Conference on Computing and Network Communications (CoCoNet). IEEE, Trivandrum, India, 2015.[Abstract]


Internet of Things (IoTs) is gaining increasing significance due to real-time communication and decision making capabilties of sensors integrated into everyday objects. IoTs are power and bandwidth-constrained with applications in smarthome, healthcare, transportation and industrial domains. Routing bears significant importance in IoTs where sensors acting as hosts deliver data to the gateways which in turn impacts power consumption. Thus there exists a need for modeling and analysis of routing in IoT networks towards predicting power consumption. In this work, we develop an analytical model of a naive flooding based routing protocol using Markov chains. In particular, we derive steady state transition probabilities of transmit and receive states using protocol execution traces and further utilize them towards predicting power consumption. Our approach to modeling is generic in that it can be applied to routing protocols across domains. Evaluation of the model shows that the predicted values for power consumption lie closer to the actual observations obtained using ns-2 simulation thus resulting in minimal mean square errors.

More »»
PDF iconModeling-and-Analysis-of-Routing-in-IoT-Networks.pdf

2013

S. Sankaran and R, S., “Energy Modeling for Mobile Devices Using Performance Counters”, 56th International Midwest Symposium on Circuits and Systems. IEEE , Columbus, OH; United States, pp. 441-444, 2013.[Abstract]


The increasing complexity of mobile applications coupled with growing user demands lead to rapid battery drain in mobile devices. However, battery technology cannot keep up with these trends thus making power management one of the foremost concerns. While system-level approaches to power management exist, the energy impact of applications on individual system components needs to be better understood for energy efficient system design. In this work, we develop energy models for mobile devices using performance counters and estimate the power consumption of system components for numerous embedded applications. Our models provide enhancements in I/O towards estimating I/O energy and cache to incorporate energy consumed during cache refill and write-back in the energy estimation process. We further compare our power estimates with existing models and demonstrate the uniqueness of our model.

More »»
PDF iconEnergy-Modeling-of-Mobile-Devices-using-Performance-Counters.pdf

2013

S. Sankaran and Sridhar, R., “User-Adaptive Energy-aware Security for Mobile Devices”, IEEE Conference on Communications and Network Security (CNS). IEEE, National Harbor, MD, USA, 2013.[Abstract]


Advancements in computing and communication technologies have given rise to low-cost embedded devices with applications in diverse domains such as Smarthome, industrial automation, healthcare, transportation etc. These devices are power-constrained which emphasizes the need for lightweight security solutions. Code obfuscation has been demonstrated to provide time-limited protection of source code from inference or tampering attacks. However, size of the obfuscated code increases with increase in code size which can have a negative impact on energy consumption. In particular, different transformations of the source code result in varying amounts of energy consumption for embedded devices. In this work, we model the impact of algorithms for code obfuscation on energy usage for embedded devices and analyze the energy-security-performance trade-os. The insights from our analysis can be used to develop techniques depending on the needs of the applications thus facilitating efficient energy usage.

More »»
PDF iconUser-Adaptive-Energy-aware-Security-for-Mobile-Devices.pdf

2009

S. Sankaran, Husain, M. Iftekhar, and Sridhar, R., “IDKEYMAN: An Identity-Based Key Management Scheme for Wireless Ad Hoc Body Area Networks”, Proceedings of Annual Symposium on Information Assurance (ASIA). 2009.[Abstract]


Wireless Ad hoc Body Area Networks are primarily used in health-care applications for patient monitoring purposes. Publisher-Subscriber driven Body Area Networks enable publishers (medical sensors attached to patients) to disseminate medical data to numerous mobile heterogeneous subscribers (doctors or caregivers) through a subscription mechanism. Such an environment raises serious security concerns due to the privacy critical medical data coupled with the resource constraints of individual body sensors. To address this problem, we present an identity based key management scheme using Identity-Based Encryption (IBE). IBE facilitates faster key set-up in addition to being lightweight and energy-efficient. The proposed scheme uses IBE to set up pair-wise symmetric keys to preserve data confidentiality and integrity. Our prototype and evaluation of the proposed model validate the approach.

More »»
PDF iconIDKEYMAN-An-Identity-Based-Key-Management-Scheme-for-Wireless-Ad-Hoc-Body-Area-Networks.pdf

Publication Type: Journal Article

Year of Publication Title

2018

H. Min, Kim, T., Heo, J., Cerny, T., Sankaran, S., Ahmed, B. S., and Jung, J., “Pattern matching based sensor identification layer for an android platform”, Wireless Communications and Mobile Computing, vol. 2018, p. 11, 2018.[Abstract]


As sensor-related technologies have been developed, smartphones obtain more information from internal and external sensors. This interaction accelerates the development of applications in the Internet of Things environment. Due to many attributes that may vary the quality of the IoT system, sensor manufacturers provide their own data format and application even if there is a well-defined standard, such as ISO/IEEE 11073 for personal health devices. In this paper, we propose a client-server-based sensor adaptation layer for an Android platform to improve interoperability among nonstandard sensors. Interoperability is an important quality aspect for the IoT that may have a strong impact on the system especially when the sensors are coming from different sources. Here, the server compares profiles that have clues to identify the sensor device with a data packet stream based on a modified Boyer-Moore-Horspool algorithm. Our matching model considers features of the sensor data packet. To verify the operability, we have implemented a prototype of this proposed system. The evaluation results show that the start and end pattern of the data packet are more efficient when the length of the data packet is longer.

More »»

2018

J. J and Sankaran, S., “A Bio-Inspired approach to secure Networked Control Systems against Adversarial Delays”, Intelligent and Fuzzy Systems, 2018.