Cyber-Physical Systems Security—A Survey <s> c) Customers' information: <s> Our study analyzes the security and privacy properties of an implantable cardioverter defibrillator (ICD). Introduced to the U.S. market in 2003, this model of ICD includes pacemaker technology and is designed to communicate wirelessly with a nearby external programmer in the 175 kHz frequency range. After partially reverse-engineering the ICD's communications protocol with an oscilloscope and a software radio, we implemented several software radio-based attacks that could compromise patient safety and patient privacy. Motivated by our desire to improve patient safety, and mindful of conventional trade-offs between security and power consumption for resource-constrained devices, we introduce three new zero-power defenses based on RF power harvesting. Two of these defenses are human-centric, bringing patients into the loop with respect to the security and privacy of their implantable medical devices (IMDs). Our contributions provide a scientific baseline for understanding the potential security and privacy risks of current and future IMDs, and introduce human-perceptible and zero-power mitigation techniques that address those risks. To the best of our knowledge, this paper is the first in our community to use general-purpose software radios to analyze and attack previously unknown radio communications protocols. <s> BIB001 </s> Cyber-Physical Systems Security—A Survey <s> c) Customers' information: <s> Household smart meters that measure power consumption in real-time at fine granularities are the foundation of a future smart electricity grid. However, the widespread deployment of smart meters has serious privacy implications since they inadvertently leak detailed information about household activities. In this paper, we show that even without a priori knowledge of household activities or prior training, it is possible to extract complex usage patterns from smart meter data using off-the-shelf statistical methods. Our analysis uses two months of data from three homes, which we instrumented to log aggregate household power consumption every second. With the data from our small-scale deployment, we demonstrate the potential for power consumption patterns to reveal a range of information, such as how many people are in the home, sleeping routines, eating routines, etc. We then sketch out the design of a privacy-enhancing smart meter architecture that allows an electric utility to achieve its net metering goals without compromising the privacy of its customers. <s> BIB002 </s> Cyber-Physical Systems Security—A Survey <s> c) Customers' information: <s> Wearable and implantable medical devices are being increasingly deployed to improve diagnosis, monitoring, and therapy for a range of medical conditions. Unlike other classes of electronics and computing systems, security attacks on these devices have extreme consequences and must, therefore, be analyzed and prevented with utmost effort. Yet, very little work exists on this important topic and the security vulnerabilities of such systems are not well understood. We demonstrate security attacks that we have implemented in the laboratory on a popular glucose monitoring and insulin delivery system available on the market, and also propose defenses against such attacks. Continuous glucose monitoring and insulin delivery systems are becoming increasingly popular among patients with diabetes. These systems utilize wireless communication links, which are frequently utilized as a portal to launch security attacks. Our study shows that both passive attacks (eavesdropping of the wireless communication) and active attacks (impersonation and control of the medical devices to alter the intended therapy) can be successfully launched using public-domain information and widely available off-the-shelf hardware. The proposed attacks can compromise both the privacy and safety of patients. We propose two possible defenses against such attacks. One is based on rolling-code cryptographic protocols, and the other is based on body-coupled communication. Our security analysis shows that the proposed defenses have the potential to mitigate the security risks associated with personal healthcare systems. <s> BIB003
Attackers can analyze network traffic in smart grids between smart meters and data centers to infer private information about customers. For example, an attacker can determine if a target is available at home at particular times and dates. In addition, it is also possible to deduce lifestyle in terms of sleeping times and quality, preferred home appliances, and many more BIB002 . d) Untargeted malware: In 2003, the Slammer worm resulted in disabling the traffic between field devices and substations. Although that malware was not intended to affect the energy sector, it still had an effect because of the interconnectedness of the smart grid networks. The malware consumed a significant amount of the time-critical traffic, but did not cause service outages  . 3) Medical Devices Attacks: Most, if not all, of the reported attacks on medical devices have been performed in experimental environments. However, the possibility of the attacks in this section, should raise an alarm to stimulate the efforts in improving security in medical devices. Although some attacks are specific to certain devices, such as insulin pumps, the same attack techniques could be applicable to other IMDs and wearable devices. This is the case because of the similarities in the communication links and hardware components. a) Replay attacks: By exploiting a vulnerability in an insulin pump, replaying eavesdropped packets is possible by incorporating a previously intercepted device's PIN BIB003 . In addition, replay attacks could result in misinformed decisions regarding insulin injection  . For example, by replaying an old CGM packet to an insulin pump, a patient will receive a dishonest reading of the glucose level, and therefore will decide, mistakenly, to inject the wrong amount of insulin. Such wrong decision could result in critical health condition. b) Privacy invasion: Attacks violating patients' privacy have different goals and consequences. For example, for the remote control attack on the insulin pump in BIB003 , an attacker needs to learn the device type, PIN, and legitimate commands sent from the remote control. The authors successfully performed this attack and revealed three types of privacyrelated information, namely, the devices' existence, its type, and finally the PIN. In addition, Halperin et al. BIB001 demonstrated similar attacks on an ICD medical device such as revealing patient's personal and medical information and the device's unique information.